Some results on generalized residual entropy

Shannon’s entropy plays an important role in the context of information theory. Since this entropy is not applicable to a system which has survived for some units of time, the concept of residual entropy has been developed in the literature. Here we generalize the residual entropy by choosing a convex function ? with ?(1) = 0. In this paper, some orderings and aging properties have been defined in terms of the generalized residual entropy function and their properties have been studied. Quite a few results available in the literature have been generalized and some distributions (viz. uniform, exponential, Pareto, power series, finite range) have been characterized through the generalized residual entropy.     

Symbolic dynamic filtering and language measure for behavior identification of mobile robots

This paper presents a procedure for behavior identification of mobile robots, which requires limited or no domain knowledge of the underlying process. While the features of robot behavior are extracted by symbolic dynamic filtering of the observed time series, the behavior patterns are classified based on language measure theory. The behavior identification procedure has been experimentally validated on a networked robotic test bed by comparison with commonly used tools, namely, principal component analysis for feature extraction and Bayesian risk analysis for pattern classification.     

Recent Advances in Boron Nitride Based Hybrid Polymer Nanocomposites

Boron nitride (BN) is an eminent inorganic compound having many interesting characteristics such as improved oxidation resistance, mechanical strength, good thermal conductivity (TC), higher bandgap, high chemical stability, thermal stability, high hydrophobicity, and electrical insulation. The use of BN as a filler in polymers is a well-established strategy to tailor the properties of polymer composites. Recent studies depict an interesting urge to reap the synergistic effect of various nanofillers with BN in the form of hybrids. Hence the consolidation of the works on BN based hybrid fillers would definitely attract researchers so that these new filler systems could be transformed into useful polymer nanocomposites in future. This review article focuses on the synthesis and characterization of various boron nitride based hybrids in detail. Moreover, the review also throws light on different BN hybrid reinforced polymer nanocomposites (PNCs) and their thermal, electrical, electronic as well as biomedical applications in a detailed manner. Thus the review anticipates serving as a tool toward understanding the recent trends in the field of boron nitride hybrid based ternary polymer composites.     

Evaluation of Concurrent Flaw Populations in Silicon Carbide in Terms of a Modified Weibull Distribution Function

Concurrent surface- and edge-flaw populations are often observed in strength testing of ceramics The overall strength distribution in such ceramic samples has been analyzed in terms of a modified Weibull distribution function. The junction provides an upper and lower strength limit and is characterized by two shape and location parameters. To evaluate the parameters of the distribution function, the type of flaw that causes failure need not be identified. The applicability of the function has been evaluated in terms of experimental results on SiC specimens. The analysis also shows that the relative values of shape parameters determine which flaw type dominates.     

Modeling of microstrip antennas using neural networks techniques: A review

Artificial neural networks modeling have recently acquired enormous importance in microwave community especially in analyzing and synthesizing of microstrip antennas (MSAs) due to their generalization and adaptability features. A trained neural model estimates response very fast, which is nearly equal to its measured and/or simulated counterpart. Thus, it completely bypasses the repetitive use of conventional models as these models need rediscretization for every minor changes in the geometry, which itself is a time‐consuming exercise. The purpose of this article is to review this emerging area comprehensively for both analyzing and synthesizing of the MSAs. During reviewing process, some untouched cases are also observed, which are essentially required to be resolved for antenna designers. Unique and efficient neural networks‐based solutions are suggested for these cases. The proposed neural approaches are validated by fabricating and characterizing of the prototypes too. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:747–757, 2015.     

Differential response of glaciers with varying debris cover extent: evidence from changing glacier parameters

Supraglacial debris (SGD) cover on mountain glaciers is known to greatly influence various glacier processes and alter their response to climate change. In this study, vital glacier parameters of five glaciers with varying debris coverage (about 7–26%), located in Zanskar basin, Ladakh Himalaya, were monitored using Landsat imagery (from 1977 to 2013) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM). Results reveal how varying amounts of SGD induce categorically distinct responses on glaciers, sharing same geographical settings. The clean glaciers (CG) in the area were found to have higher retreat rates (about 8–19 m year^?1), comparable areal shrinkage (about 13–15%), higher accumulation area ratios (AARs) (>0.5), rapid increase in SGD (about 1.6–3.0-fold), and association with increasing numbers of peri- and proglacial lakes (2–8 per glacier). The debris-covered glaciers (DCG) showed minimal frontal changes (about 2–5 m year^?1), higher areal shrinkage (about 14–21%), low AARs (<0.5), slow SGD changes (about ≤1.2-fold), and association with increasing numbers of peri- and supraglacial lakes (SGLs) (2–39 per glacier). Moreover, while changes in SGD had a strong negative correlation with changes in glacier area, retreat rates, and AAR, they were positively related with increase in area of SGLs.     

Rényi information measure for a used item

Recently, in the literature, a measure of tail heaviness has been proposed based on Rényi entropy. This measure is very useful in the sense that it can be used to measure tail heaviness even for the distributions for which the kurtosis measure does not exist. Nadarajah and Zografos [Nadarajah, Zografos, Information Sciences 153 (2003), 119-138] have derived the expression for this measure for different univariate continuous distributions. But, this measure can only be used for the lifetime of a new item. In case of used item, this measure needs some modification. In this paper, we have modified the measure accordingly so that it can be used in the case of used item and also for the new item. We have also derived expressions for this measure for sixteen different univariate distributions and ten other standard distributions derived from the general distributions used in reliability and survival analysis. The most of the results obtained in the literature in this direction can be obtained as particular cases of our general results.     

Identification of statistical patterns in complex systems via symbolic time series analysis

Identification of statistical patterns from observed time series of spatially distributed sensor data is critical for performance monitoring and decision making in human-engineered complex systems, such as electric power generation, petrochemical, and networked transportation. This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability. The core concept of pattern identification is built upon the principles of Symbolic Dynamics, Automata Theory, and Information Theory. To this end, a symbolic time series analysis method has been formulated and experimentally validated on a special-purpose test apparatus that is designed for data acquisition and real-time analysis of fatigue damage in polycrystalline alloys.     

Optimization of substrates for Bioelectricity production by Ochrobactrum pseudintermedium KF026284 in a single chambered microbial fuel cell

A new strain of bacterium Ochrobactrum pseudintermedium KF026284 was isolated from a single chambered microbial fuel cell operated with rumen fluid. The bacterium produced maximum power density of 114 mW/m² (0.7 V, 0.6 mA) when nutrient broth was used as the growth medium. The optimization of electricity generation by O. pseudintermedium KF026284 was carried out using various substrates like cellulose, cellobiose, starch, sucrose, and glucose. The bacterium when fed with cellobiose showed an appreciable and sustainable electricity generation with a power density of 150 mW/m² from the 5th day and a maximum power density of 247 mW/m² on the 11th day.