State complexity of unique rational operations

For each basic language operation we define its “unique” counterpart as being the operation that results in a language whose words can be obtained uniquely through the given operation. These unique operations can arguably be viewed as combined basic operations, placing this work in the popular area of state complexity of combined operations on regular languages. We study the state complexity of unique rational operations and we provide upper bounds and empirical results meant to cast light into this matter. Equally important, we hope to have provided a generic methodology for estimating their state complexity.     

Recommendation engine based on derived wisdom for more similar item neighbors

Information Systems and e-Business Management - Collaborative filtering (CF) is a popular and widely accepted recommendation technique. CF is an automated form of word-of-mouth communication...     

基于数据点松紧度的局部线性嵌入算法

局部线性嵌入算法（LLE）是流形学习中非线性数据降维的重要方法之一。考虑数据点分布大多呈现不均匀性,LLE对近邻点的选取方式将会导致大量的信息丢失。根据其不足,提出一种基于数据点松紧度的局部线性嵌入改进算法——tLLE算法,针对数据点分布不均匀的数据集,tLLE算法能有效地进行维数约简,且具有比LLE更好的降维效果。在人造数据和现实数据上的嵌入以及分类识别结果表明了tLLE算法的有效性。     

Alternative search techniques for face detection using location estimation and binary features

The sliding window approach is the most widely used technique to detect an object from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the scanning speed also depends on a number of different factors (such as the grid spacing, and the scale at which the image is searched). When the scanning grid spacing is larger than the tolerance of the trained classifier it suffers from low detections. In this paper, we present a technique to reduce the number of missed detections when fewer subwindows are processed in the sliding window approach for face detection. This is achieved by using a small patch to predict the location of the face within a local search area. We use simple binary features and a decision tree for location estimation as it proved to be efficient for our application. We also show that by using a simple interest point detector based on quantized gradient orientation, as the front-end to the proposed location estimation technique, we can further improve the performance. Experimental evaluation on several face databases show better detection rate and speed with our proposed approach when fewer number of subwindows are processed compared to the standard scanning technique.     

Additive manufacturing of barium titanate based ceramic heaters with positive temperature coefficient of resistance (PTCR)

Lanthanum/manganese doped barium titanate (BT) based PTCR functional heater elements/structures were fabricated with desirable electrical properties for the first time using Additive Manufacturing (AM). 3D printed components of varying size and shape and prototype honeycomb lattices with high density were achieved through AM. Aqueous, less organic containing (2.5 wt% additives versus 10–30 wt% added typically), eco-friendly ink formulations were developed with suitable rheological properties for 3D printing. For BT prints, the sintered densities of the 3D ceramic parts were found to be >99% TD, highest reported value so far. The microstructure, electrical properties and heating characteristics of the printed PTCR components were studied in detail and their thermal stability evaluated using infrared imaging and benchmarked against commercial PTCR heating element. The heating behaviour of the solid and porous 3D printed components was demonstrated to be similar, paving the way for light weight (?47% reduction in weight) heaters suitable for automotive/aerospace applications and less materials wastage during device fabrication.     

A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data

Machine Learning - Covariance estimation for high-dimensional datasets is a fundamental problem in machine learning, and has numerous applications. In these high-dimensional settings the number of...     

Use of Endostemon tereticaulis (Pear.) M.Ashby and Hyptis spicigera Lam. Plant Extracts as Corrosion Green Inhibitors for Mild Steel in 1M HCl: Electrochemical and Surface Morphological Studies

Protection of Metals and Physical Chemistry of Surfaces - In the present study, we evaluated the effect of corrosion inhibition of ethanol extracts from Endostemon tereticaulis and Hyptis spicigera...     

Optimization of inoculum to substrate ratio for bio-energy generation in co-digestion of tannery solid wastes

The inoculum to substrate (I/S) ratio is an important factor which influences the anaerobic digestion process. In this study, the effect of different I/S ratios on the performance of co-digestion of fleshings along with mixture of sludge generated during treatment of tannery wastewater was investigated. The parameters studied were biogas generation, volatile solids reduction, volatile fatty acid (VFA) production, and the stability of the digestion process based on VFA to alkalinity ratio was evaluated for various I/S ratios. Economical significance of I/S ratio as related to the volume of the anaerobic digester and the potential benefit of bio-energy generated are discussed in detail.