Predicting the colour properties of viscose knitted fabrics using soft computing approaches

The aim of this paper was to predict the colour strength of viscose knitted fabrics by using fuzzy logic (FL) model based on dye concentration, salt concentration and alkali concentration as input variables. Moreover, the performance of fuzzy logic (FL) model is compared with that of artificial neural network (ANN) model. In addition, same parameters and data have been used in ANN model. From the experimental study, it was found that dye concentration has the main and greatest effects on the colour strength of viscose knitted fabrics. The coefficient of determination (R²), root mean square (RMS) and mean absolute errors (MAE) between the experimental colour strength and that predicted by FL model are found to be 0.977, 1.025 and 4.61%, respectively. Further, the coefficient of determination (R²), root mean square (RMS) and mean absolute errors (MAE) between the experimental colour strength and that predicted by ANN model are found to be 0.992, 0.726 and 3.28%, respectively. It was found that both ANN and FL models have ability and accuracy to predict the fabric colour strength effectively in non-linear domain. However, ANN prediction model shows higher prediction accuracy than that of Fuzzy model.     

A 20 K GaAs array with 10 K of embedded SRAM

A 20000-gate GaAs array with 10 K of embedded RAM is presented. The array contains eight scannable fully registered 256×256 RAM macros which have a minimum cycle time of 3.5 ns. The RAM features a scan mode, which can be used to configure the registers into a serial shifter. There is also a RAM test mode which allows independent functional and speed testing of all eight RAMs, easing the task of RAM verification for a given user personalization. The RAM array was fabricated using an advanced high-performance GaAs semiconductor E /D MESFET process featuring self-aligned gates and requiring only 12 masks. Introductory discussion of the Vitesse GaAs process, basic GaAs MESFET characteristics, and GaAs circuit design are provided. The gate array portion contains 20736 user-configurable cells with 10-ps gate delays which are tailored for direct-coupled FET logic (DCFL). The I/O can be personalized for ECL, TTL, or GaAs levels. There are 392 pads on the 13.8-mm×7.7-mm die with a maximum of 256 used for signal I/O. The RAM array is packaged in a multilayer ceramic 344-pin leaded chip carrier (LDCC). Typical power dissipation at 80% utilization is 14 W     

Ballistic Deficits for Ionization Chamber Pulses in Pulse Shaping Amplifiers

In order to understand the dependence of the ballistic deficit on the shape of rising portion of the voltage pulse at the input of a pulse shaping amplifier, we have estimated the ballistic deficits for the pulses from a two-electrode parallel plate ionization chamber as well as for the pulses from a gridded parallel plate ionization chamber. These estimations have been made using numerical integration method when the pulses are processed through the CR-RCⁿ (n=1-6) shaping network as well as when the pulses are processed through the complex shaping network of the ORTEC Model 472 spectroscopic amplifier. Further, we have made simulations to see the effect of ballistic deficit on the pulse-height spectra under different conditions. We have also carried out measurements of the ballistic deficits for the pulses from a two-electrode parallel plate ionization chamber as well as for the pulses from a gridded parallel plate ionization chamber when these pulses are processed through the ORTEC 572 linear amplifier having a simple CR-RC shaping network. The reasonable matching of the simulated ballistic deficits with the experimental ballistic deficits for the CR-RC shaping network clearly establishes the validity of the simulation technique     

Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles

Abstract

The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.     

An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors

The complex behavior of various occurrences in turning has made the tool condition and process monitoring with a conventional tool-sensor setup difficult. An additional passive tool arrangement has been adopted to circumvent the multifaceted mechanism of different occurrences and thus to investigate them by measuring the acoustic emission (AE), and vibration signals produced thereof. The investigation shows that both the AE and the radial vibration component, V_y can independently assess the chip formation effect on cutting process and tool state. The tangential vibration component, V_z can effectively evaluate the rate of flank wear progression whereas the resultant vibration components are efficient in measuring the surface roughness of workpiece in turning. The feed directional vibration, V_x is always maximal regardless of cutting variables, tool wear, surface roughness, and chip formation type. The application of vibration sensor can eliminate the necessity of the additional passive tool setup, and jointly with the AE sensor can investigate the process and cutting tool condition more promisingly.     

GIS based surface hydrological modelling in identification of groundwater recharge zones

Digital elevation model (DEM) is a storehouse of a variety of hydrological information along with terrain characteristics. In recent years, automatic extraction of drainage network from DEM with the help of Geographical Information System (GIS) has become possible and is now being practised the world over for hydrological studies. In the present study, a comparative analysis of the drainage network derived from DEM and drainage extracted from surveyed topographical maps has been carried out. A comparative analysis based on nearest neighbour analysis on an intersection theme of two drainage networks showed that there is clustering (randomness<1) existing at places which show potential groundwater recharge zones. The suitable groundwater recharge zones identified in the drainage comparative analysis also show good correlation with the suitable recharge maps derived from remote sensing and GIS based procedure. In this study, two different watersheds (a) Dwarkeshwar in Bankura district, West Bengal, India, and (b) Kethan in Vidisha districts of Madhya Pradesh, India have been taken to analyse for identification of suitable groundwater recharge zones. The drainage comparative analysis approach developed and tested successfully in the present study is quick and reliable for the identification of suitable groundwater recharge zones particularly in a hard rock terrain.     

Effects of neutralization on the structure and properties of an ionomer

The structure, morphology, and properties of an ionomer, poly(ethylene‐acrylic‐acid) neutralized by zinc salts (PI) depend on the free carboxylic acid content. In this work, metal acetates (Na, Zn, and Al acetates) were used to control the neutralization levels. A wide range of techniques were used, such as spectroscopic Fourier transform infrared spectroscopy (FTIR), thermal [thermogravimetric analysis, modulated differential scanning calorimetry (MDSC), and dynamic mechanical analysis (DMA)], mechanical (tensile measurement), and small angle neutron scattering (SANS). The melt rheological properties of the samples were also examined. The results show that metal acetate neutralizes free acrylic acid in the ionomer, which has the primary role in controlling ionic association. The number of ionic groups in ionic domains and multiplets in the matrix is dependent on the neutralization level. Metal valence determines the ionic domain or multiplet structure (FTIR), further properties of PI. Dynamic mechanical properties, the ionic transition behaviour, and the mechanical properties are improved compared with PI using monovalent cation (Na⁺), but decreased using trivalent cation (Al³⁺) or shows less significant changes due to steric effects. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Experimental investigation and empirical modeling of the dry electric discharge machining process

Dry electric discharge machining (EDM) is an environment-friendly modification of the oil EDM process in which liquid dielectric is replaced by a gaseous medium. In the current work, parametric analysis of the process has been performed with tubular copper tool electrode and mild steel workpiece. Experiments have been conducted using air as the dielectric medium to study the effect of gap voltage, discharge current, pulse-on time, duty factor, air pressure and spindle speed on material removal rate (MRR), surface roughness (R_a) and tool wear rate (TWR). First, a set of exploratory experiments has been performed to identify the optimum tool design and to select input parameters and their levels for later stage experiments. Empirical models for MRR, R_a and TWR have then been developed by performing a designed experiment based on the central composite design of experiments. Response surface analysis has been done using the developed models. Analysis of variance (ANOVA) tests were performed to identify the significant parameters. Current, duty factor, air pressure and spindle speed were found to have significant effects on MRR and R_a. However, TWR was found to be very small and independent of the input parameters.     

Defect‐Mediated Polarization Switching in Ferroelectrics and Related Materials: From Mesoscopic Mechanisms to Atomistic Control

The plethora of lattice and electronic behaviors in ferroelectric and multiferroic materials and heterostructures opens vistas into novel physical phenomena including magnetoelectric coupling and ferroelectric tunneling. The development of new classes of electronic, energy‐storage, and information‐technology devices depends critically on understanding and controlling field‐induced polarization switching. Polarization reversal is controlled by defects that determine activation energy, critical switching bias, and the selection between thermodynamically equivalent polarization states in multiaxial ferroelectrics. Understanding and controlling defect functionality in ferroelectric materials is as critical to the future of oxide electronics and solid‐state electrochemistry as defects in semiconductors are for semiconductor electronics. Here, recent advances in understanding the defect‐mediated switching mechanisms, enabled by recent advances in electron and scanning probe microscopy, are discussed. The synergy between local probes and structural methods offers a pathway to decipher deterministic polarization switching mechanisms on the level of a single atomically defined defect.     

Cell Culture on MEMS Platforms: A Review

Microfabricated systems provide an excellent platform for the culture of cells, and are an extremely useful tool for the investigation of cellular responses to various stimuli. Advantages offered over traditional methods include cost-effectiveness, controllability, low volume, high resolution, and sensitivity. Both biocompatible and bio-incompatible materials have been developed for use in these applications. Biocompatible materials such as PMMA or PLGA can be used directly for cell culture. However, for bio-incompatible materials such as silicon or PDMS, additional steps need to be taken to render these materials more suitable for cell adhesion and maintenance. This review describes multiple surface modification strategies to improve the biocompatibility of MEMS materials. Basic concepts of cell-biomaterial interactions, such as protein adsorption and cell adhesion are covered. Finally, the applications of these MEMS materials in Tissue Engineering are presented.