An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.     

A unified method for optimal arbitrary pole placement

We consider the classic problem of pole placement by state feedback. We offer an eigenstructure assignment algorithm to obtain a novel parametric form for the pole-placing feedback matrix that can deliver any set of desired closed-loop eigenvalues, with any desired multiplicities. This parametric formula is then exploited to introduce an unconstrained nonlinear optimisation algorithm to obtain a feedback matrix that delivers the desired pole placement with optimal robustness and minimum gain. Lastly we compare the performance of our method against several others from the recent literature.     

Influence of Grain Size on Ferroelastic Toughening and Piezoelectric Behavior of Lead Zirconate Titanate

Lead zirconate titanate specimens, at composition Zr_{48.9+- 1.0}/ Ti_51.1+-1.0 of grain sizes ranging from 0.5 to 15 (μm were prepared by hot pressing. The fracture toughness showed a 40% increase in the fine-grained specimens. Poling produced anisotropy in the fracture toughness. A tensor representation for the fracture toughness, now a function of the crack plane normal and the poling direction, is developed. The maximum and minimum values in the toughness tensor are shown to be related to the unpoled toughness by a simple phenomenological relationship. We also find that the piezoelectric coefficient, d₃₃ , shows a slight increase for the fine-grained specimens, which is in conflict with the general view that smaller-grained materials can sustain vanishingly small values of spontaneous polarization.     

A spatio‐temporal water quality assessment of the Beas and Sutlej Rivers at the Harike Wetland: A Ramsar site in Punjab,India

Lakes play a vital role in regulating water storage, flow of river water, and ultimately maintaining a balanced ecosystem. Spatial and temporal variations in physicochemical parameters of water in Harike Wetland, a Ramsar site in the northwestern state of Punjab, India, were studied. This study was conducted on a monthly basis from January to December 2015. The water quality was studied at ten locations from sites 1 to 10 upstream, central and downstream from Harike Lake for ten physicochemical parameters, including temperature, pH, electrical conductivity, turbidity, dissolved oxygen concentration biological oxygen demand, nitrate and phosphate concentrations and salinity. The findings of this study revealed that, except for temperature and pH, all parameters exhibited relatively higher values for the Sutlej River, compared with the Beas River, with sampling sites 5 to site 7 exhibiting intermediate results. The mean seasonal temperature variations ranged from 16.9 to 26.6 °C, the pH from 7.7 to 8.2, electrical conductivity from 223 to 303 μS cm^?1 and TDS concentration from 148.7 to 180.4 ppm. Correlation analysis was conducted to assess the relations between the variables. The electrical conductivity exhibited a high positive correlation with salinity and biological oxygen demand, whereas it correlated negatively with the dissolved oxygen concentration. Box and whisker plots were also plotted for the study results to better examine the data distribution.     

Formation of Nanocrystalline Calcia by the Decomposition of Calcite

Formation of nanocrystalline calcia from calcite has been studied in situ via transmission electron microscopy. The crystallographic transformation occurred via two mechanisms: the first is by distortion of the cleaved rhombohedron of calcite, formed by {104} planes in hexagonal coordinates, into a cube. This produced a microstructure of oriented, elongated nanocrystals of calcia with planar boundaries. In the second mechanism, the micrometer-sized parent calcite particles broke up into nano-sized grains as the decomposition began, leading to irregularly shaped, randomly oriented nanocrystals of calcia.     

Studies on chemical resistance of polyesters

Chlorendic anhydride based polyester ( I ,) tetrachlorophthalic anhydride based polyester ( II ), dibromoneopentyl glycol based polyester ( III ,) general purpose polyester ( IV ,) blend of dibromoneopentyl glycol based polyester with general purpose polyester ( V ,) chlorendic anhydride and dibromoneopentyl glycol based polyester ( VI ), and a blend of chlorendic anhydride based polyester and dibromoneopentyl glycol based polyester ( VII ) were prepared and their chemical resistance and moisture absorption studied in various reagents, acid, alkali, and water, at 25 and 65°C. It is found that the polyester ( III ) is the least affected in the presence of the acids. In 20% NaOH, there was a decrease in weight for all polyesters at both the temperatures compared to the control except the polyester ( VII ). Increase in weight of all the polyesters was observed during the absorption of moisture both at 25 and 65°C. The increase was higher at higher temperature. Polyester ( III ) thus shows the least absorption of moisture.     

IEVCA: An efficient image encryption technique for IoT applications using 2-D Von-Neumann cellular automata

Multimedia Tools and Applications - Present era is marked by exponential growth in transfer of multimedia data through internet. Most of the Internet-of-Things(IoT) applications send images to...     

On the applicability of diploid genetic algorithms in dynamic environments

Diploid genetic algorithms (DGAs) promise robustness as against simple genetic algorithms which only work towards optimization. Moreover, these algorithms outperform others in dynamic environments. The work examines the theoretical aspect of the concept by examining the existing literature. The present work takes the example of dynamic TSP to compare greedy approach, genetic algorithms and DGAs. The work also implements a greedy genetic approach for the problem. In the experiments carried out, the three variants of dominance were implemented and 115 runs proved the point that none of them outperforms the other.     

Design of Barrages with Genetic Algorithm Based Embedded Simulation Optimization Approach

Barrages are hydraulic structures constructed across rivers to divert flow into irrigation canals or power generation channels. The most of these structures are founded on permeable foundation. The optimum cost of these structures is nonlinear function of factors that cause the seepage forces under the structure. There is, however, no procedure to ascertain the basic barrage parameters such as depth of sheet piles or cutoffs and the length and thickness of floor in a cost–effective manner. In this paper, a nonlinear optimization formulation (NLOF), which consists of an objective function of minimizing total cost, is solved using genetic algorithm (GA). The mathematical model that represents the subsurface flow is embedded in the NLOF. The applicability of the approach has been illustrated with a typical example of barrage profile. The results obtained in this study shows drastic cost savings when the proposed NLOF is solved using GA than that of using classical optimization technique and conventional method. A parametric analysis has also been performed to study the effect of varying soil and hydrological conditions on design parameters and on over all cost.     

Entanglement sudden death and birth in qubit–qutrit systems under Dzyaloshinskii–Moriya interaction

We study entanglement dynamics of qubit–qutrit pair under Dzyaloshinskii–Moriya (DM) interaction. The qubit–qutrit pair acts as a closed system and one external qubit serve as the environment for the pair. The external qubit interact with qubit of closed system via DM interaction. This interaction frequently kills the entanglement between qubit–qutrit pair, which is also periodically recovered. On the other hand two parameter class of state of qubit–qutrit pair also affected by DM interaction and one parameter class of state remains unaffected. The frequency of occurrence of entanglement sudden death and entanglement sudden birth in two parameter class of state is half than qubit–qutrit pure state. We used our quantification of entanglement as negativity measure.