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The flow of fuel and oxidant through a PEMFC is analyzed for prediction of maldistribution. Flow distribution of both fuel and oxidant from the port to the individual cells critically control the performance of a PEMFC stack in combination. The distribution of fluids was simulated by analytical approach utilizing flow channeling model of a manifold. A detailed numerical modeling is also carried out considering flow in each cell between the electrodes as flow through an equivalent porous medium offering identical resistance. The results show a close match between the analytical and numerical results'. The parametric study reveals that flow rate and port size plays major role determining maldistribution of the ,fluids', which can be considerably skewed when large numbers of cells are stacked for larger power output.

A detailed experimental study on flow maldistribution from port to channel of a plate heat exchanger is presented. In general, flow maldistribution brings about an increase in pressure drop across the heat exchanger. This increase is found to depend on flow rate, number of channels and port size. Experiments show that analytical predictions of pressure drop including maldistribution effect are quite accurate for practical purposes. The results indicate that under identical conditions, maldistribution is more severe in Z-type plate heat exchanger compared to U type. Experiments are also carried out under nonisothermal realistic operating conditions, which show increased flow maldistribution at elevated temperature. Finally predictions are made for industrial plate heat exchangers, which show the limitation of adding additional plates beyond a certain limit. An insight to the physical aspects of maldistribution and its possible reduction through proper design strategy is also indicated. [DOI: 10.1115/1.1779664]

In recent times, the medical imaging becomes an indispensable tool in clinical practice. Due to the large volume of medical images, compression is needed to lessen the redundancies in the image and also to represent the image in shorter manner for effective transmission. In this paper, Linde–Buzo–Gray (LBG) algorithm was developed with vector quantization (VQ) for compressing the images, and it results in decent image quality. To further increase the image quality, optimization techniques [particle swarm optimization (PSO) and firefly algorithm (FA)] were used in LBG method to optimize the codebook for generating the global codebook. In the proposed work, LBG method was used to get the local codebooks and the obtained local codebooks were optimized by utilizing PSO. The optimized codebooks from PSO were again optimized by using FA that results in good quality of the image. In the experimental phase, the performance of the proposed work was compared with individual optimization techniques like PSO and FA. From the experimental study, the proposed work showed 1.2–6 dB improvement in image compression related to other existing approaches. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is the trending domain in addressing the inadequate bands for communication, and spectrum sensing is the hectic challenge need to be addressed extensively. In the conventional CRs, the communication is restricted to the secondary users (SUs) in the allocated bands causing the underutilization of the available band. Thus, with the aim to afford higher throughput and spectrum efficiency, this paper introduces the hybrid mixture model for spectrum sensing in the multiple-input–multiple-output (MIMO) systems and the effectiveness is evaluated based on the evaluation parameters, such as detection probability and probability of false alarm. The signal received through the orthogonal frequency-division multiplexing (OFDM) antenna is employed for analyzing the spectral availability for which the energy and Eigen statistics of the signal is generated, which forms the input to the Hybrid mixture model. The developed Hybrid mixture model is the integration of the Gaussian Mixture Model (GMM) and Whale Elephant-Herd Optimization (WEHO). The GMM is subjected to the optimal tuning using the WEHO, which is the modification of the standard Whale Optimization Algorithm (WOA) with the Elephant-Herd Optimization (EHO). The analysis reveals that the proposed spectrum sensing model acquired the maximal detection probability and minimal false alarm probability of 99.9% and 46.4%, respectively. The proposed hybrid mixture model derives the spectrum availability and ensures the effective communication in CR without any interference. [ABSTRACT FROM AUTHOR]

For the past few years, the automated addressing of changes in remote sensing images plays a significant role. However, the change detection (CD) model often suffers from the issue of speckle noise. More investigations have been proceeded to overcome this obstacle. This paper also considers the same issue and proposes a new CD model in synthetic aperture radar (SAR) images. Here, two SAR images that are captivated at different times will be considered as the input of the detection process. At first, discrete wavelet transform is incurred for image fusion, where the coefficients are optimally selected through a hybrid model that hybridizes the gray wolf optimization and dragonfly (DA) optimization. At last, the fused images after inverse transform are clustered via the fuzzy c-mean (FCM) clustering approach, and a similarity measure is performed between the segmented image and the ground truth image. The proposed model, wolf hunting-based DA with FCM, compares its performance over other conventional methods in terms of measures like accuracy, specificity, sensitivity, precision, negative predictive value, F 1 score and Matthews correlation coefficient. Similarly, the negative measures are false positive rate, false negative rate and false discovery rate, and the betterment is proven. [ABSTRACT FROM AUTHOR]

An experimental and theoretical study of the effect of flow maldistribution from port to channel on the thermal performance of single and multipass plate heat exchangers is presented. The results indicate that under identical conditions, maldistribution is more severe in Z-type late heat exchanger compared to U type.

Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air & attacks low immune bodies. Recently, several techniques are applied to diagnosis the TB diseases. Unfortunately, diagnosing TB is still a major challenge. In recent years, a variety of techniques have been developed. In this paper, texture feature set is obtained using three different categories like statistical, structural and gray level dependent features. After that, the feature selection scheme is carried out and TB classification is done using GANN classifier. In GA-NN, genetic algorithm and neural network are combined to do the classification process. Once the abnormal TB is classified via GA-NN classifier, the TB region is identified via morphological operator. Experimental results demonstrate that the proposed method outperforms than the existing method. [ABSTRACT FROM AUTHOR]

This paper investigates the new detailed adaptive noise canceller (ANC) system for Electrocardiogram (ECG) enhancement with robustness based on multiband structured sub band adaptive filter (MSAF). The proposed design is probably a new realization form of algorithm which guaranteed a more stable transformation and solves the structured problems in conventional sub band adaptive filter (SAF). The objective of the examination is to give arrangement keeping in mind the end goal to improve the execution of ANC as far as filter parameters which are procured with the assistance of uniform filter banks (UFB) and non uniform filter banks (NUFB) structured MSAF's using LMS algorithm. Computer simulation demonstrates that the proposed system gives improved performance and achieves good adaptation. NUFB structured MSAF algorithms are applied on ECG records obtained from standard MIT-BIH data base and the performance is compared with UFB structured MSAF algorithms in terms of parameters SNR, MSE, RMSE and distortion. The SNR for various NUFB structured MSAF's was found to be higher than the UFB structured MSAF's. The five channel NUFB structures with decimation factors (16, 16, 8, 4, 2) has on average SNR of 17.67064 dB is obtained using LMS algorithm which is superior to existing algorithms. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is a global health problem and an infectious disease for people with low immunity and HIV/AIDS patients. Unfortunately diagnosing tuberculosis is still a major challenge. In any medical diagnosis, classifier plays an important role. In order to improve the speed of the classifier; it is required to use the selected features. To reduce the dimensionality of feature vector the authors have used RST based Multi Kernel Fuzzy C-Means (MKFCM) method for selecting features which are indispensable. Features those are not selected are treated as redundant or superfluous and are removed from the final feature vector. The performance of proposed methodology is analyzed in terms of accuracy, performance curve and regression plots. As a result, the suggested method gives the better performance. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present an image compression method using feedforward backpropagation neural networks. Medical imaging is an efficient source for better diagnosis of the disease and also helps in assessing the severity of the disease. But due to the increasing size of the medical images, transferring and storage of images require huge bandwidth and storage space. Therefore, it is essential to derive an effective compression algorithm, which have minimal loss, time complexity, and increased reduction in size. With the concept of Neural Network, data compression can be achieved by producing an internal data representation. The training algorithm and development architecture gives less distortion and considerable compression ratio and also keeps up the capability of hypothesizing and is becoming important. The performance metrics of three algorithms, Levenberg Marquardt algorithm, Resilient backpropagation algorithm, and Gradient Decent algorithm have been computed on Magnetic Resonance Imaging (MRI) images and it is observed that Levenberg Marquardt algorithm is more accurate when compared to the other two algorithms. [ABSTRACT FROM AUTHOR]

The finline based transmission line is used for realization of wide band pass filter. In this paper designing a bandpass filter for wide bandwidth, based on parallel coupled unilateral three finline structures. A design graph for symmetric three unilateral finline structures is presented for the design of bandpass filter. A bandpass filter of order 3 having center frequency of 10 GHz with fractional bandwidth of 20% is designed fabricated and measured. This wide bandpass filter is converted into symmetric and asymmetric dual band pass filters with the help of metamaterials (Split Ring Resonators SRR) on the other side of the finline structure is simulated with High Frequency Structure Simulator (HFSS) and fabricated. Transmission (S21) and reflection (S11) parameters of measured results compared with simulated results. [ABSTRACT FROM AUTHOR]

In the present world, there is a great necessity to have reliable and quality power distribution, and so there is great scope for research on automation of distribution system. The main objective of this paper is to analyze and comprehend different machine learning and image processing based algorithms to find a practical solution for automated inspection of overhead power line insulators. This method is a relatively new approach for. This paper also highlights the constraints and limitations that are present in the various existing methodologies to achieve the objective. Traditionally the workers who inspect these lines check them in close proximity by going for foot-patrolling and pole-climbing. With an incredible expansion of power distribution network even to remote areas, previously mentioned methods do not seem to be viable. The development of an efficient method of condition monitoring by using image processing followed by machine learning techniques is found to be a suitable method and thus emerging as a feasible option for real-time implementation. The few techniques like artificial neural networks (ANN), Hidden Markov Model (HMM), k-means clustering, Wavelet transform features, S-transform features, and support vector machines (SVM) applied in the domain of condition monitoring of the insulators were presented. [ABSTRACT FROM AUTHOR]

In this paper, the construction of new lifting based wavelets by a new method of calculating lifting coefficients is presented. First of all, new basis functions are utilized to ease new orthogonal traditional wavelets. Then by using the decomposing poly-phase matrix the lifting steps are calculated using a simplified method. The interesting feature of lifting scheme is that the construction of wavelet is derived in spatial domain only; hence the difficulty in the design of traditional wavelets is avoided. Lifting scheme was used to generate second generation wavelets which are not necessarily translation and dilation of one particular function. Short and sharp basis functions are chosen so as to obtain the non-uniform nature of usual image classes. Implemented wavelets are applied on a number of medical images. It was found that the compression ratio (CR) and Peak Signal to Noise Ratio (PSNR) are far ahead of that are obtained with the popular traditional wavelets as well as the successful 5/3 and 9/7 lifting based wavelets. Set Partitioning in Hierarchical Trees (SPIHT) is used to incorporate compression. [ABSTRACT FROM AUTHOR]

Multi carrier systems such as OFDM, MC-CDMA (Multi Carrier code division multiple access) exhibits better bit error performances (BER) in frequency selective fading channels, but the main disadvantage of MC CDMA systems is the degradation of its performance due to multiple access interference (MAI). Frequency division multi-carrier code division multiple access (FD-MC-CDMA), exploits the available frequency diversity benefits and reduces MAI. In this paper we proposed maximum likelihood (ML) Multi User detection (MUD) using genetic algorithms for FD-MC-CDMA systems frequency in frequency selective fading channels. Experimental results confirmed that the proposed detection algorithm is effective with less computational load compared to existing estimation algorithms. [ABSTRACT FROM AUTHOR]

This paper presented a theoretical and numerical assessment for nonidentical segmented exponential-(NISE-) convex and NISE concave serrated plane CATRs by changing number of serrations. The investigation was based on diffraction theory and, more specifically, on the diffraction formulation of Fresnel. The compact antenna test range (CATR) provides uniform illumination within the Fresnel region to the test antenna. Application of serrated edges has been shown to be a good method to control diffraction at the edges of the reflectors. In this paper, the Fresnel fields of NISE-convex and NISE-concave serrated CATRs are analyzed using physical optics (PO) technique. The PO analysis is applied in this paper for plane reflector serrated CATR only. The same analysis is applied to any type of reflector. In this paper, lens-based reflector is not considered. It is observed that NISE-concave serrated CATR gives less ripple and enhanced quiet zone width than NISE-convex. [ABSTRACT FROM AUTHOR]

For perfect diagnosis of brain tumour, it is necessary to identify tumour affected regions in the brain in Magnetic Resonance Imaging (MRI) images effectively and compression of these images for transmission over a communication channel at high speed with better visual quality to the experts. An attempt has been made in this paper for identifying tumour regions with optimal thresholds which are optimized with the proposed Hybrid Bacteria Foraging Optimization Algorithm (BFOA) and Particle Swarm Optimization (PSO) named (HBFOA-PSO) by maximizing the Renyi's entropy and Kapur's entropy. BFOA may be trapped into local optimal problem and delay in execution time (convergence time) because of random chemotaxis steps in the procedure of algorithm and to get global solution, a theory of swarming is commenced in the structure of HBFOA-PSO. Effectiveness of this HBFOA-PSO is evaluated on six different MRI images of brain with tumours and proved to be better in Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Fitness Function. [ABSTRACT FROM AUTHOR]