Consideration of Trends in Evaluating Inter-basin Water Transfer Alternatives within a Fuzzy Decision Making Framework

Evaluation of water supply schemes is an essential task for meeting the goals of inter-basin water transfer project system management. In general, water supply operation involves multi-objective and multifactor optimization and decision. In recent years, multicriterion decision making (MCDM) has emerged as an effective methodology due to its ability to combine quantitative and qualitative criteria for selection of the best alternative. This paper presents a new optimization method using fuzzy pattern recognition to appraise the water supply decision schemes in inter-basin diversion systems. The proposed method is capable to incorporate not only the will of the decision-makers but also the future development trend of water resources and water supply demand and makes the optimization results more reasonable and applicable. One case study for the Xi-River-to -Tanghe Reservoir Water Transfer Project System in China is presented to demonstrate the application of this method.     

Land‐use classification of multispectral aerial images using artificial neural networks

During the past decade, there have been significant improvements in remote sensing technologies, which have provided high‐resolution data at shorter time intervals. Considerable effort has been directed towards developing new classification strategies for analysing this imagery, but the use of artificial intelligence‐based analysis techniques has been somewhat limited. The aim of this study was to develop an artificial neural network (ANN)‐based technique for the classification of multispectral aerial images for land use in agricultural and environmental applications. The specific land‐use classes included water, forest, and several types of agricultural fields. Multispectral images at a 1‐m resolution were obtained for the state of Georgia, USA from a Geographic Information Systems (GIS) data clearinghouse. These false‐colour images contained green, red and infrared true‐colour information. Three approaches were used for the preparation of the inputs to the ANN. These included histograms of the pixel intensities, textural parameters extracted from the image, and matrices of the pixels for spatial information. A probabilistic neural network was used. Seven hundred images were used for model development and 175 for independent model evaluation. The overall accuracy for the evaluation data set was 74% for the histogram approach, 71% for the spatial approach and 89% for the textural approach. The evaluation of ANNs based on various combinations of all three approaches did not show an improvement in accuracy. We also found that some approaches could be used selectively for certain classes. For example, the textural approach worked best for forest classes. For future studies, edge detection prior to classification, with more careful selection of each class, should be included for land‐use classification of multispectral images.     

Self-adaptive differential evolution for feature selection in hyperspectral image data

Hyperspectral images are captured from hundreds of narrow and contiguous bands from the visible to infrared regions of electromagnetic spectrum. Each pixel of an image is represented by a vector where the components of the vector constitute the reflectance value of the surface for each of the bands. The length of the vector is equal to the number of bands. Due to the presence of large number of bands, classification of hyperspectral images becomes computation intensive. Moreover, higher correlation among neighboring bands increases the redundancy among them. As a result, feature selection becomes very essential for reducing the dimensionality. In the proposed work, an attempt has been made to develop a supervised feature selection technique guided by evolutionary algorithms. Self-adaptive differential evolution (SADE) is used for feature subset generation. Generated subsets are evaluated using a wrapper model where fuzzy k-nearest neighbor classifier is taken into consideration. Our proposed method also uses a feature ranking technique, ReliefF algorithm, for removing duplicate features. To demonstrate the effectiveness of the proposed method, investigation is carried out on three sets of data and the results are compared with four other evolutionary based state-of-the-art feature selection techniques. The proposed method shows promising results compared to others in terms of overall classification accuracy and Kappa coefficient.     

Resolving Deep Sub-Wavelength Scattering of Nanoscale Sidewalls Using Parametric Microscopy

The quantitative optical measurement of deep sub-wavelength features with sub-nanometer sensitivity addresses the measurement challenge in the semiconductor fabrication process. Optical scatterings from the sidewalls of patterned devices reveal abundant structural and material information. We demonstrated a parametric indirect microscopic imaging (PIMI) technique that enables recovery of the profile of wavelength-scale objects with deep sub-wavelength resolution, based on measuring and filtering the variations of far-field scattering intensities when the illumination was modulated. The finite-difference time-domain (FDTD) numerical simulation was performed, and the experimental results were compared with atomic force microscopic (AFM) images to verify the resolution improvement achieved with PIMI. This work may provide a new approach to exploring the detailed structure and material properties of sidewalls and edges in semiconductor-patterned devices with enhanced contrast and resolution, compared with using the conventional optical microscopy, while retaining its advantage of a wide field of view and relatively low cost.     

Impact of frozen storage on polyacetylene content, texture and colour in carrots disks

This study investigated the effect of freezing method (slow or blast freezing) with or without blanching during storage at −20 °C on the levels of three polyacetylenes, falcarinol (FaOH), falcarindiol (FaDOH), falcarindiol-3-acetate (FaDOAc) in carrot disks. The quality of the carrot disks was also assessed using instrumental texture and colour measurements. Blast frozen carrot disks retained higher amounts of polyacetylenes compared to their slow frozen counterparts. Whilst the levels of retention of total polyacetylenes was higher in unblanched than blanched disks prior to freezing there was a sharp decrease in the levels of polyacetylenes in unblanched frozen carrots during the storage period for 60 days at −20 °C. FaDOH was observed to be the most susceptible to degradation during frozen storage of unblanched carrot disks, followed by FaOH and FaDOAc. The changes in the level of polyacetylenes during storage were adequately described by using Weibull model. The texture and colour were also found to decrease during frozen storage compared to fresh carrots.     

TFET on Selective Buried Oxide (SELBOX) Substrate with Improved ION/IOFF Ratio and Reduced Ambipolar Current

Silicon - This paper proposes a new structure for tunnel field effect transistor on a selective buried oxide (SELBOX) substrate. An extensive simulation study and a comparative performance analysis...     

Nanoscale surface modifications to control capillary flow characteristics in PMMA microfluidic devices

Polymethylmethacrylate (PMMA) microfluidic devices have been fabricated using a hot embossing technique to incorporate micro-pillar features on the bottom wall of the device which when combined with either a plasma treatment or the coating of a diamond-like carbon (DLC) film presents a range of surface modification profiles. Experimental results presented in detail the surface modifications in the form of distinct changes in the static water contact angle across a range from 44.3 to 81.2 when compared to pristine PMMA surfaces. Additionally, capillary flow of water (dyed to aid visualization) through the microfluidic devices was recorded and analyzed to provide comparison data between filling time of a microfluidic chamber and surface modification characteristics, including the effects of surface energy and surface roughness on the microfluidic flow. We have experimentally demonstrated that fluid flow and thus filling time for the microfluidic device was significantly faster for the device with surface modifications that resulted in a lower static contact angle, and also that the incorporation of micro-pillars into a fluidic device increases the filling time when compared to comparative devices.     

Transport in deformable food materials: A poromechanics approach

A comprehensive poromechanics-based modeling framework that can be used to model transport and deformation in food materials under a variety of processing conditions and states (rubbery or glassy) has been developed. Simplifications to the model equations have been developed, based on driving forces for deformation (moisture change and gas pressure development) and on the state of food material for transport. The framework is applied to two completely different food processes (contact heating of hamburger patties and drying of potatoes). The modeling framework is implemented using total Lagrangian mesh for solid momentum balance and Eulerian mesh for transport equations, and validated using experimental data. Transport in liquid phase dominates for both the processes, with hamburger patty shrinking with moisture loss for all moisture contents, while shrinkage in potato stops below a critical moisture content.     

Effect of suspension characteristics on the performance of thermal barrier coatings deposited by suspension plasma spray

This paper investigates the influence of suspension characteristics on microstructure and performance of suspensions plasma sprayed (SPS) thermal barrier coatings (TBCs). Five suspensions were produced using various suspension characteristics, namely, type of solvent and solid load content, and the resultant suspensions were utilized to deposit five different TBCs under identical processing conditions. The produced TBCs were evaluated for their performance i.e. thermal conductivity, thermal cyclic fatigue (TCF) and thermal shock (TS) lifetime. This experimental study revealed that the differences in the microstructure of SPS TBCs produced using varied suspensions resulted in a wide-ranging overall TBC performance. All TBCs exhibited thermal conductivity lower than 1 W/(m. K) except water-ethanol mixed suspension produced TBC. The TS lifetime was also affected to a large extent where 10 wt % solid loaded ethanol and 25 wt % solid loaded water suspensions produced TBCs exhibited the highest and the lowest lifetime, respectively. On the contrary, TCF lifetime was not as significantly affected as thermal conductivity and TS lifetime, and all ethanol suspensions showed marginally better TCF lifetime than water and ethanol-water mixed suspensions deposited TBCs.