Modeling and analysis for the development of Lightweight Piezoceramic Composite Actuators (LIPCA)

This paper focuses on the modeling and analysis of Lightweight Piezoceramic Composite Actuators (LIPCA) for developmental purposes. A simple analytical model and a numerical model for predicting the displacement of the actuators due to both an applied input voltage and transverse load to the piezoelectric ceramic layer are presented. The analytical model describing the laminated beam actuation results in two primary design parameters, an actuation coefficient of a laminated beam C_ulb and the bending stiffness of a laminated beam EI_lb. The C_ulb is a parameter when maximum displacement is required. The bending stiffness affects the displacement performance when a transverse load is applied to the actuators. An experiment was performed to verify the proposed laminated beam model. The numerical model, a NASTRAN finite element model, is used to assess the effect of initial dome heights of actuators on the displacement. An increase in the initial dome height produces a positive effect for the low anisotropic actuators and gives a negative effect for the high anisotropic actuators. In conclusion, the results indicate that designing to maximize the C_ulb, the EI_lb, and the initial dome height of the low anisotropic actuators could generate LIPCA-type actuators with larger displacement and higher force.     

Optimisation of food grade mixed surfactant‐based l‐ascorbic acid nanoemulsions using response surface methodology

Co‐surfactant free l‐ascorbic acid (LAA) nanoemulsions were prepared using mixed surfactants (Soya lecithin and Tween 80). Response surface methodology (RSM) was used to optimise the emulsifying conditions for LAA nanoemulsions. The effects of water proportion (6%–14% w/w), homogenisation pressure (80–160 MPa), surfactant concentrations (4%–12% w/w) and laa concentration (0.5–1.3 w/w) on responses (size of droplets and nanoemulsion stability) were investigated. RSM results showed that the values of responses can be successfully predicted through second‐order polynomial model. The coefficients of determinations for droplet size and nanoemulsion stability were 0.9375 and 0.9027, respectively. The optimum preparation conditions for l‐LAA nanoemulsion were 9.04% water proportion, 114.48 MPa homogenisation pressure, 7.36% surfactant concentration and 1.09% LAA concentration. At the end of one month storage study, the retention of LAA in optimised nanoemulsions stored at 4°C and 25°C were 74.4% and 66.7%, respectively. These results may provide valuable contributions for food and pharmaceutical industry to develop delivery system for food additives and nutraceutical components.     

Ambiguity in the MMPI.

MMPI items were rated for ambiguity on a 5-point scale and were also answered under standard instructions by male and female introductory psychology students. Lower ambiguity ratings of female Ss were interpreted in terms of role or habit patterns of females in our culture. Mean ambiguity values for selected MMPI scales revealed high ambiguity for both sexes, independent of order effects, for items keyed on the K, Pd, Pt, Ma, and Welsh A scales, and low ambiguity for items on the L, F, Hs, Mf, and Welsh R scales. Significant intercorrelations were found between total ambiguity scores of individual Ss and scores on Hs, Si, and Sc, with a negative relationship between ambiguity and K. These results suggest a relationship between ego control and perceived ambiguity in the items. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On efficient construction and evaluation of runs rules–based control chart for known and unknown parameters under different distributions

In this study, we have considered two design structures of control chart by covering the situations of known and unknown parameters, variety of probability distributions, and runs rules. The design structures are dependent on constants which generally considered hard to compute analytically. For construction of constants and also for evaluating performance of the design structures through performance measures, we have illustrated Monte Carlo simulation procedure/algorithm for researcher and practitioners. Furthermore, based on the Monte Carlo simulation procedures, we have established a program in R language to compute values of different constants and performance measures. Results illustrated that design structures for known and unknown parameters under variety of runs rules and probability distributions have outstanding performance in contrast to existing structures. Moreover, design structure for unknown parameters behaves alike the design structure for known parameters. This indicates that design structure for unknown parameters has the ability to resolve the issue of runs rules which generally occur when parameters are estimated. Besides, two real‐life examples have been included in which physicochemical characteristic of groundwater and plasticizer characteristic of petrochemical process are monitored through design structures.     

A secure and low‐energy zone‐based wireless sensor networks routing protocol for pollution monitoring

Sensor networks can be used in many sorts of environments. The increase of pollution and carbon footprint are nowadays an important environmental problem. The use of sensors and sensor networks can help to make an early detection in order to mitigate their effect over the medium. The deployment of wireless sensor networks (WSNs) requires high‐energy efficiency and secures mechanisms to ensure the data veracity. Moreover, when WSNs are deployed in harsh environments, it is very difficult to recharge or replace the sensor's batteries. For this reason, the increase of network lifetime is highly desired. WSNs also work in unattended environments, which is vulnerable to different sort of attacks. Therefore, both energy efficiency and security must be considered in the development of routing protocols for WSNs. In this paper, we present a novel Secure and Low‐energy Zone‐based Routing Protocol (SeLeZoR) where the nodes of the WSN are split into zones and each zone is separated into clusters. Each cluster is controlled by a cluster head. Firstly, the information is securely sent to the zone‐head using a secret key; then, the zone‐head sends the data to the base station using the secure and energy efficient mechanism. This paper demonstrates that SeLeZoR achieves better energy efficiency and security levels than existing routing protocols for WSNs. Copyright © 2016 John Wiley & Sons, Ltd.     

Stream Flow Forecasting of Poorly Gauged Mountainous Watershed by Least Square Support Vector Machine,Fuzzy Genetic Algorithm and M5 Model Tree Using Climatic Data from Nearby Station

Forecasting stream flow is a very importance issue in water resources planning and management. The ability of three soft computing methods, least square support vector machine (LSSVM), fuzzy genetic algorithm (FGA) and M5 model tree (M5T), in forecasting daily and monthly stream flows of poorly gauged mountainous watershed using nearby hydro-meteorological data is investigated in the current study. In the first application, monthly stream flows of Hunza river are forecasted using local stream flow data of Hunza and precipitation and temperature data of nearby station. LSSVM provides slightly better forecasts than the FGA and M5T models. Stream flow and temperature inputs generally give better forecasts compared to other inputs. In the second application, daily stream flows of Hunza river are forecasted using local stream flow data of Hunza and precipitation and temperature data of nearby station. Better results are obtained from the models comprising only stream flow inputs. In general, a better accuracy is obtained from LSSVM models in relative to the FGA and M5T. The results indicate that the monthly and daily stream flows of Hunza can be accurately forecasted by using only nearby climatic data. In the third application, daily stream flows of Hunza river are forecasted using local stream flow and climatic data and the models’ accuracy is slightly increased in relative to the previous applications. LSSVM generally performs superior to the FGA and M5T in forecasting daily stream flow of Hunza river using local stream flow and climatic inputs.     

Investigation of Magnetic,Magnetocaloric, and Critical Properties of La<Subscript>0.5</Subscript>Ba<Subscript>0.5</Subscript>MnO<Subscript>3</Subscript> Manganite

We present an extensive study of the magnetic properties of a novel La_0.5Ba_0.5MnO₃ perovskite material prepared by the hydrothermal method. The explored sample was structurally studied by the x-ray diffraction (XRD) method which confirms the formation of a pure cubic phase of a perovskite structure with Pm3m space group. The magnetic properties were probed by employing temperature M (T) and external magnetic field M (μ_oH) dependence of magnetization measurements. A magnetic phase transition from ferromagnetic to paramagnetic phase occurs at 339 K in this sample. The maximum magnetic entropy change (\(\left | {{\Delta } S}_{M}^{\max } \right |\)) took a value of 1.4 J kg^??1 K^??1 at the applied magnetic field of 4.0 T for the explored sample and has also been found to occur at Curie temperature (T_C). This large entropy change might be instigated from the abrupt reduction of magnetization at T_C. The magnetocaloric effect (MCE) is maximum at T_C as represented by M (μ_oH) isotherms. The relative cooling power (RCP) is 243.2 J kg^??1 at μ_oH =?4.0 T. Moreover, the critical properties near T_C have been probed from magnetic data. The critical exponents δ, β, and γ with values 3.82, 0.42, and 1.2 are close to the values predicted by the 3D Ising model. Additionally, the authenticity of the critical exponents has been confirmed by the scaling equation of state and all data fall on two separate branches, one for T < T_C and the other for T > T_C, signifying that the critical exponents obtained in this work are accurate.