Radon Exhalation Rate Study of Sand Samples Collected from Sea Coast of Tirur,Kerala, India Using Track Etch Technique

The sand samples have been collecting from the sea coast (Unniyal beach) of Tirur of Malappuram district of Kerala state (India) by the grab sampling method. Radon exhalation rates have measured by “Sealed Can Technique” using LR-115 type II plastic track detector to estimate the health risk level in the environment. The value of radon activity varies from 444.44 to 2204.44 becquerel meter^?3 (Bq m^?3) with a geometric mean (G.M.)/standard deviation (S.D.) value of 1017.21 Bq m^?3/433.27. The value of mass exhalation rate for radon varies from 0.01 to 0.05 Bq kg^?1 h^?1 with a G.M./S.D. value of 0.024 Bq kg^?1 h^?1/0.010. The value of area exhalation rate for radon varies from 0.27 to 1.33 Bq m^?2 h^?1 with a G.M./S.D. value of 0.62 Bq m^?2 h^?1/0.26. The values of radon emanation ranged from 2.90?×?10^?3 to 2.98?×?10^?3 (%) with a G.M./S.D. value of 2.98?×?10^?3(%)/0.05. The alpha dose equivalent of the studied area is found and it varies from 0.68 to 1.66 milli sievert year^?1 (mSv yr^?1) with a G.M./S.D. value of 1.03 mSv yr^?1/0.24. Good positive correlation is observed between the effective radium content and area exhalation rate for sand samples. Therefore, the obtained result shows that this region is safe as for as the health risk effects of radium and radon exhalation rate are concerned.     

On Modeling the Medical Care Insurance Data via a New Statistical Model

Proposing new statistical distributions which are more flexible than the existing distributions have become a recent trend in the practice of distribution theory. Actuaries often search for new and appropriate statistical models to address data related to financial and risk management problems. In the present study, an extension of the Lomax distribution is proposed via using the approach of the weighted T-X family of distributions. The mathematical properties along with the characterization of the new model via truncated moments are derived. The model parameters are estimated via a prominent approach called the maximum likelihood estimation method. A brief Monte Carlo simulation study to assess the performance of the model parameters is conducted. An application to medical care insurance data is provided to illustrate the potentials of the newly proposed extension of the Lomax distribution. The comparison of the proposed model is made with the (i) Two-parameter Lomax distribution, (ii) Three-parameter models called the half logistic Lomax and exponentiated Lomax distributions, and (iii) A four-parameter model called the Kumaraswamy Lomax distribution. The statistical analysis indicates that the proposed model performs better than the competitive models in analyzing data in financial and actuarial sciences.     

An Optimized Neural Network with Bat Algorithm for DNA Sequence Classification

Recently, many researchers have used nature inspired metaheuristic algorithms due to their ability to perform optimally on complex problems. To solve problems in a simple way, in the recent era bat algorithm has become famous due to its high tendency towards convergence to the global optimum most of the time. But, still the standard bat with random walk has a problem of getting stuck in local minima. In order to solve this problem, this research proposed bat algorithm with levy flight random walk. Then, the proposed Bat with Levy flight algorithm is further hybridized with three different variants of ANN. The proposed BatLFBP is applied to the problem of insulin DNA sequence classification of healthy homosapien. For classification performance, the proposed models such as Bat levy flight Artificial Neural Network (BatLFANN) and Bat levy Flight Back Propagation (BatLFBP) are compared with the other state-of-the-art algorithms like Bat Artificial Neural Network (BatANN), Bat back propagation (BatBP), Bat Gaussian distribution Artificial Neural Network (BatGDANN). And Bat Gaussian distribution back propagation (BatGDBP), in-terms of means squared error (MSE) and accuracy. From the perspective of simulations results, it is show that the proposed BatLFANN achieved 99.88153% accuracy with MSE of 0.001185, and BatLFBP achieved 99.834185 accuracy with MSE of 0.001658 on WL5. While on WL10 the proposed BatLFANN achieved 99.89899% accuracy with MSE of 0.00101, and BatLFBP achieved 99.84473% accuracy with MSE of 0.004553. Similarly, on WL15 the proposed BatLFANN achieved 99.82853% accuracy with MSE of 0.001715, and BatLFBP achieved 99.3262% accuracy with MSE of 0.006738 which achieve better accuracy as compared to the other hybrid models.

     

Emotion Recognition from Occluded Facial Images Using Deep EnsembleModel

Facial expression recognition has been a hot topic for decades, but high intraclass variation makes it challenging. To overcome intraclass variation for visual recognition, we introduce a novel fusion methodology, in which the proposed model first extract features followed by feature fusion. Specifically, RestNet-50, VGG-19, and Inception-V3 is used to ensure feature learning followed by feature fusion. Finally, the three feature extraction models are utilized using Ensemble Learning techniques for final expression classification. The representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising accuracy. To evaluate the efficiency of the proposed model, we use two wild benchmark datasets Real-world Affective Faces Database (RAF-DB) and AffectNet for facial expression recognition. The proposed model classifies the emotions into seven different categories namely: happiness, anger, fear, disgust, sadness, surprise, and neutral. Furthermore, the performance of the proposed model is also compared with other algorithms focusing on the analysis of computational cost, convergence and accuracy based on a standard problem specific to classification applications.     

Classification of multi-lingual tweets,into multi-class model using Naïve Bayes and semi-supervised learning

Multimedia Tools and Applications - Twitter is a social media platform which has been proven to be a great tool for insights of emotions about products, policies etc. through a 280-character...     

Filter-Bank Modulation Based Signal Design and Transmission Techniques for Intensity Modulated MIMO Visible Light Communication Systems

Wireless Personal Communications - Current research in wireless communication undoubtedly points towards the tremendous advantages of using visible light as a spectrum for significantly boosting...     

Imidazolium ionic liquid incorporation on sulfonated poly(styrene‐isobutylene‐styrene) proton exchange membranes

Ionic liquids (ILs) with different anions and cations were incorporated in sulfonated poly(styrene‐isobutylene‐styrene) (SIBS) to modify its chemical, morphological, and transport properties for direct methanol fuel cell (DMFC) applications. Different loadings of IL and different solvents were studied to have a better understanding of the incorporation process and the ability of the solvent to affect the interaction of the IL with the sulfonated polymer. Morphological characterization with SAXS and AFM suggested changes caused by the incorporation of the IL and by the solvent used. FT‐IR spectra showed small variations in energy related to interactions of the IL with the sulfonic groups which caused thermogravimetric stabilization of the ionic domains. Other results suggest that water has a very significant effect on the morphology, interaction with the IL, and transport properties of the membranes. Optimal concentration of IL (～10 mol %) provides enough water to produce efficient proton conductivity (0.15 S/cm) and minimal methanol permeability (0.8 × 10^?6 cm²/s). © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 44900.     

Biological nitrogen and phosphorus removal and changes in microbial community structure in a membrane bioreactor: effect of different carbon sources

Bacterial community structures in four sequencing anoxic/anaerobic-aerobic membrane bioreactors (SAMs) that were fed with synthetic medium composed of different organic compounds in substrate as carbon source; acetate-dominant (acetate/propionate = 4/1), propionate-dominant (acetate/propionate = 1/4), glucose-dominant (glucose/acetate = 4/1) and methanol-dominant (methanol/acetate/propionate = 6/3/1) were analyzed by respiratory quinone profile and fluorescent in situ hybridization (FISH) techniques. The SAMs were operated at controlled pH range 7-8.5 and at constant temperature 25 degrees C. Total nitrogen (TN), total phosphorus (TP) and COD removal performances were also evaluated and compared. In addition, trans-membrane pressure was monitored to observe the impact of substrate composition on membrane fouling. The dominance of the mole fraction of ubiquinone (UQ-8) in the SAMs indicated dominance of the beta-subclass of Proteobacteria; however, its population comparatively decreased when the substrate was glucose dominant or methanol dominant. A relatively higher and stable enhanced biological phosphorus removal performance was observed when methanol-dominant substrate was used concurrently with an increase in the gamma-subclass of Proteobacteria. The population of the alpha-subclass of Proteobacteria slightly increased along with a decrease in phosphate removal activity when the substrate was glucose-dominant. Results from FISH analysis also supported the findings of the quinone profile. The trans-membrane pressure variation in the SAMs indicated that fouling was relatively rapid when propionate-dominant or methanol-dominant substrate was used and most stable when glucose-dominant substrate was used. A combination of methanol and acetate would be a better choice as an external carbon source when nutrients removals, as well as fouling, are considered in the membrane bioreactor- (MBR-) coupled biological nutrients removing (BNR) process.     

Generation of electrical energy using lead zirconate titanate (PZT-5A) piezoelectric material: Analytical,numerical and experimental verifications

Energy harvesting is the process of attaining energy from the external sources and transforming it into usable electrical energy. An analytical model of piezoelectric energy harvester has been developed to determine the output voltage across an electrical circuit when it is forced to undergo a base excitation. This model gives an easy approach to design and investigate the behavior of piezoelectric material. Numerical simulations have been carried out to determine the effect of frequency and loading on a Lead zirconate titanate (PZT-5A) piezoelectric material. It has been observed that the output voltage from the harvester increases when loading increases whereas its resonance frequency decreases. The analytical results were found to be in good agreement with the experimental and numerical simulation results.