Exploring Regional Profile of Drought History- a New Procedure to Characterize and Evaluate Multi-Scaler Drought Indices Under Spatial Poisson Log-Normal Model

Water Resources Management - Drought is recurrently occurring in many parts of the globe. In contrast to other natural hazards, drought has complex climatic characteristics. Several environmental...     

Role of Conducting Polymers in Enhancing TiO2-based Photocatalytic Dye Degradation: A Short Review

Research in the field of TiO₂-based photocatalysis has gained wide attention to address important energy and environmental problem. Lately, the use of conducting polymers as photosensitizers has proven to immensely enhance photodegradation by exhibiting excellent photocatalytic activity under both ultraviolet light and natural sunlight irradiation which is not possible using semiconductors alone. Considering the unique performance of conducting polymer-based nanocomposites in photocatalysis, the present review provides the recent advances in the development of ultraviolet and visible light-responsive conducting polymer-based TiO₂ nanocomposites for their potential application in environmental remediation. This review ends with a summary focusing on the challenges and new dimensions in this still emerging area of research.     

On a class of mixed EWMA-CUSUM median control charts for process monitoring

Monitoring of any manufacturing, production, or industrial process can be controlled and improved by removing these special cause of variations using control charts. Shewhart-type control charts are effective to control a large amount of special variations, whereas, cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) charts detect small and moderate variations efficiently in the process parameters. Monitoring of location parameter can be done with mean control charts under the assumption that the parameters are known or correctly estimated from in-control samples and data are free from outliers (but in practice data occasionally have outliers). In this study, we have proposed generalized mixed EWMA-CUSUM median control charts structures for known and unknown parameters based on auxiliary variables for detecting shifts in process location parameter. The proposed charts are compared with the corresponding charts for the mean, based on contaminated and uncontaminated data. Different performance measures are used to evaluate the performance of proposed control charts and revealed through results that the median-based charts are more sensitive to detect a shift in process location parameter in the presence of outliers. An illustrative example using real data is also shown for practical consideration.     

Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of various Neural Networks trained on a custom dataset. It can be automated into assisting designers, allowing them to focus on the other more complicated parts of the system they are designing by quickly generating what would rather be straightforward busywork. Over the past 20 years, the boom in how much the internet is used and the sheer volume of pages on it demands a high level of work and time to create them. For the efficiency of the process, we proposed a multi-model-based architecture on image captioning, consisting of Convolutional neural network (CNN) and Long short-term memory (LSTM) models. Our proposed approach trained on our custom-made database can be automated into assisting designers, allowing them to focus on the other more complicated part of the system. We trained our model in several batches over a custom-made dataset consisting of over 6300 files and were finally able to achieve a Bilingual Evaluation Understudy (BLEU) score for a batch of 50 hand-drawn images at 87.86%     

Microwave assisted synthesis and antimicrobial activity of Fe3O4-doped ZrO2 nanoparticles

Composites play important role in dental filling by controlling shrinkage along with correction in teeth's shape and position. Rehabilitation of severely worn dentition can be achieved using mechanically strong composites. This study aims to synthesize zirconia-based composites to be used as dental fillers. Effect of microwave powers (100–900?W) along with Fe₃O₄ doping are studied on the structural, mechanical and magnetic properties of stabilized zirconia. SEM and TEM reveal formation of spherical nanoparticles with diameter of ～30?nm. XRD results shows phase pure tetragonal zirconia (t-ZrO₂) at microwave power of 500?W without any post heat treatment. Crystallite size calculated from XRD data (～23?nm) matches well with the previously reported value for stabilization of t-ZrO₂. Microwave energy dissipation results in stresses causing volume shrinkage leading to monoclinic to tetragonal phase transformation with higher X-ray density and hardness of ～1347HV. VSM results show ferromagnetic response with low coercivity (600Oe) value and saturation magnetization (～2emu/g). It is worth mentioning here that this is one of its kind study reporting synthesis of room temperature stabilized Fe₃O₄ doped zirconia composites at microwave power of 500?W. Antibacterial studies reveal inhibition zone of ～32?mm against bacillus bacteria suggesting their potential use as dental filler.     

Bivariate Dispersion Control Charts for Monitoring Non‐Normal Processes

Multivariate control charts are well known to be more sensitive to the occurrence of variation in processes with two or more correlated quality variables than univariate charts. The use of separate univariate control charts to monitor multivariate process can be misleading as it ignores the correlation between the quality characteristics. The application of multivariate control charts allows for the simultaneous monitoring of the quality characteristics by forming a single chart. The charts operate on the assumption that process observations are normally distributed, but in practice this is not always the case. In this study, we examine and present multivariate dispersion control charts for detecting shifts in the covariance matrix of normal and non‐normal bivariate processes. These control charts, referred to as SMAX, QMAX, MDMAX and MADMAX, rely on dispersion estimates, such as the sample standard deviation (S), interquartile range (Q), average absolute deviation from median (MD) and median absolute deviation (MAD), respectively. We compare the performances of these charts to the existing multivariate generalized variance |S| and RMAX charts for bivariate processes using normal and non‐normal parent distributions. The average run length (ARL) measure is used for the evaluation and comparison of the charts. A real life and simulated datasets are used to demonstrate the application of the charts. Copyright © 2016 John Wiley & Sons, Ltd.     

On increasing the sensitivity of moving average control chart using auxiliary variable

In the statistical process control, the most useful tool to monitor the manufacturing processes in the industries is the control chart. Quality practitioners always desire the charting structure that identifies sustainable changes in the monitoring processes. The sensitivity of the control chart is improved when additional correlated auxiliary information about the study variable is introduced. The regression estimate in the form of auxiliary and supporting variables presents an unbiased and efficient statistic of the mean of the process variable. In this study, auxiliary information-based moving average (AB-MA) control chart is designed for efficient monitoring of shifts in the process location parameter. The performance of the AB-MA control chart is evaluated and compared with existing charts using average run length and other run length characteristics. The comparison reveals that the AB-MA control chart outperforms the competitors in detecting the small and medium changes in the process location parameter. The application of the proposal is also provided to implement it in real situation.