Effect of waste serpentine on the properties of basic insulating refractories

Basic insulating refractories were fabricated by the pressing route using dead-burned magnesia, pure calcined alumina, expanded perlite, and calcined waste serpentine as starting raw materials in four compositions from F1 to F4. Periclase and forsterite were major phases in F1 and F2 compositions, while spinel was also detected in the XRD patterns of F3 and F4 samples. Quantitative phase analysis showed that F4 sample sintered at 1450?°C has the highest forsterite content among all other samples. On the other hand, it has lower thermal conductivity compared to F1 to F3, and even lower than aluminosilicate IFBs with the same bulk density. It is concluded that forsterite is a highly insulating material, compared to periclase, corundum, periclase-spinel, aluminosilicates, such as mullite, etc.     

Upstream Cutoff and Downstream Filters to Control of Seepage in Dams

The finite element method was used in this study to investigate cutoff walls and downstream filters to control seepage, the exit hydraulic gradient, and uplift forces for dams. Experimental data was used for validating the numerical modelling. The effective parameters are the length of filter and its distance downstream from the dam, the depth of the cutoff walls, the upstream dam head, and the thickness of alluvial foundation. The results show that by increasing filter length, the exit hydraulic gradient, uplift force, and seepage are reduced. The optimum relative length of the filter is L/H?=?0.028 which results in a decrease of about 65% in the exit hydraulic gradient, a 35% decrease in seepage and 10% reduction in the uplift force at the upstream foundation and a 60% decrease in the uplift force at the downstream foundation. Increase of cutoff wall depth reduces the exit hydraulic gradient, uplift force, and seepage. Using two cutoff walls both upstream and downstream of the dam decreases seepage, hydraulic gradient, and uplift force 132%, 450% and 11% respectively. However, using an upstream cutoff and downstream filter decreases seepage, hydraulic gradient, and uplift force by 180%, 490%, and 119% respectively. Thus, based on this study, recommendations for suitable combinations of upstream cutoff and downstream filter are provided.

     

Broadband absorption enhancement in hole-transport- layer-free perovskite solar cell by grating structure

Recently, the hole transport layer-free planar perovskite solar cells (HTL-free PSCs) have attracted intense attention. However, the poor absorption of light in the wavelengths longer than 800 nm is an important challenge in all configurations of PSCs. In this study, the HTL-free PSC with a gold rectangular grating at back contact is proposed. In order to improve the performance of the solar cell, effects of grating dimensions and periodicity on the absorption of the active layer are numerically investigated. In the improved condition, an absorption enhancement of 25% in the range of 300—1 400 nm is obtained compared with the flat electrode-based structure. These improvements are attributed to the coupling of light to surface plasmon polariton (SPP) modes. Also, the electrical simulation results of the improved solar cell demonstrated short-circuit current density and power conversion efficiency of 27.72 mA/cm2 and 18%, respectively.     

PBSVM: Partitioning and biased support vector machine for vocal fold pathology assessment using labeled and unlabeled data sets

Most of the existing classification methods, used for voice pathology assessment, are built based on labeled pathological and normal voice signals. This paper studies the problem of building a classifier using labeled and unlabeled data. We propose a novel learning technique, called Partitioning and Biased Support Vector Machine Classification (PBSVM), which tries to utilize all the available data in two steps: (1) a new heuristically partition-based algorithm, which extracts high quality pathological and normal samples from an unlabeled set, and (2) a more principle approach based on biased formulation of support vector machine, which is fairly robust to mislabeling and unbalance data problem. Experiments with wavelet-based energy features extracted from sustained vowels show that the new recognition scheme is highly feasible and significantly outperform the baseline classical SVM classifier, especially in the situation where the labeled training data is small.     

The Term Vector Database: fast access to indexing terms for Web pages

We have built a database that provides term vector information for large numbers of pages (hundreds of millions). The basic operation of the database is to take URLs and return term vectors. Compared to computing vectors by downloading pages via HTTP, the Term Vector Database is several orders of magnitude faster, enabling a large class of applications that would be impractical without such a database. This paper describes the Term Vector Database in detail. It also reports on two applications built on top of the database. The first application is an optimization of connectivity-based topic distillation. The second application is a Web page classifier used to annotate results returned by a Web search engine.     

Graph structure in the Web

The study of the Web as a graph is not only fascinating in its own right, but also yields valuable insight into Web algorithms for crawling, searching and community discovery, and the sociological phenomena which characterize its evolution. We report on experiments on local and global properties of the Web graph using two AltaVista crawls each with over 200 million pages and 1.5 billion links. Our study indicates that the macroscopic structure of the Web is considerably more intricate than suggested by earlier experiments on a smaller scale.     

An Efficient Active Contour Model Through Curvature Scale Space Filtering

Active contour models can be successfully used in multimedia database retrieval systems if they have good accuracy and high speed. The majority of existing active contour models do not lock on to interest objects very accurately and quickly especially in complex images. The behavior of the active contour is generally controlled by its internal and external energies. Internal energy is composed of two parts; the first part acts to shorten the active contour as it iterates towards the interest object, while the second part is the curvature of the active contour and forces smoothness of active contour during its movement towards interest object. In this paper, first a reformulated internal energy is proposed to improve the computation of curvature at point v _i by making use of the three points v _{i – 1}, v _i and v _{i + 1}. Second, an accurate and high speed active contour model, SAC is proposed based on reformulating internal energy by removing the curvature part and using Gaussian filtering with low scale of smoothing. The SAC model has only one parameter that affects the internal energy of active contour and as a result of using the Curvature Scale Space (CSS)¹ technique for smoothing, the SAC model is more independent of model parameter setting and the initial snake.     

Reducing CO2 emission from exhaust gases using molten carbonate fuel cells: a new approach

The aim of this study is to couple molten carbonate fuel cell (MCFC) stack with integrated gasification combined cycle fed by refinery residues, to remove CO₂ from gas turbine exhaust gases that have CO₂ emission rate of 14,200 ton/year. By applying multi-objective optimisation (MOO) using genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. The MOO of the MCFC system regarding two scenarios is performed. The first scenario is minimisation of cost of electricity (COE) and CO₂ emission rate. Objective functions of the second scenario are the same as in the first scenario while CO₂ tax is taken into account. Results show that the second scenario has 29.5% lower average optimal COE and 2.5% lower average emission rate in comparison with the first scenario. A sensitivity analysis is also performed to study the effect of fuel price and CO₂ tax variations on optimal solutions.     

Geometric Patterns,Light and Shade: Quantifying Aperture Ratio and Pattern Resolution in the Performance of Shading Screens

This research focuses on the application and performance assessment of geometric patterns as shading screens and shows how the geometric patterns can function as a design agency, an environmental control system, and a cultural element. We begin with a brief review of the underlying rules of creating two-dimensional geometric patterns, and then look at how these patterns evolve as three-dimensional shading screens in buildings. We next discuss a predictive model for translating complex patterns to simple patterns concerning their perforation ratio, granularity, and morphology. This is followed by an experimental and simulation study for measuring the daylighting performance of some simple shading screens. The result of this phase assesses the agreement among experimental and numerical studies. Finally, we evaluate the performance of a screen inspired by a Persian pattern.