Characterization and fracture behavior of bismuth–tin thermal fuse alloy wires produced by the Ohno continuous casting process

Bismuth–tin binary alloys containing high bismuth concentrations of 40 to 77% were continuously cast into wires of approximately 2 mm in diameter with casting speeds between 15 and 150 mm min^?1 using the Ohno Continuous Casting (OCC) process. The microstructure was examined and tensile tests were performed for wires cast at various speeds. It was found that for slowly cast wires containing large primary bismuth dendrites, bismuth fracture occurring along the (111) plane exerted a key role in wire fracture, while microstructures with refined bismuth dendrites exhibited a mixture of bismuth cracks and inter-phase decohesion, allowing the accommodation of larger strain before wire fracture. For wires with microstructures containing primary tin dendrites, inter-phase decohesion played a key role in wire fracture.     

An explicit predictor-corrector solver with application to seismic wave modelling

Wave-equation-based forward modelling using explicit finite-difference methods is a standard technique for calculating synthetic seismograms. The stability criterion restricts the size of the time step. In this paper a predictor–corrector method for solving the wave equation is described which allows the use of a larger time step. A stability analysis of the method is also carried out. Parallel implementation of the algorithm is described for a distributed computing environment which makes use of MPI and PVM message passing calls for communication between processors.     

A computational method for regularized long wave equation

Quintic spline technique and splitting method have been used to develop a new-finite difference method to solve regularized long wave (RLW) equation. The convergence and the stability of the proposed method are discussed. Then, it is used to model solitary wave motion and undular bore development by solving two test examples.     

Unconstrained handwritten document retrieval

With the ever-increasing growth of the World Wide Web, there is an urgent need for an efficient information retrieval system that can search and retrieve handwritten documents when presented with user queries. However, unconstrained handwriting recognition remains a challenging task with inadequate performance thus proving to be a major hurdle in providing robust search experience in handwritten documents. In this paper, we describe our recent research with focus on information retrieval from noisy text derived from imperfect handwriting recognizers. First, we describe a novel term frequency estimation technique incorporating the word segmentation information inside the retrieval framework to improve the overall system performance. Second, we outline a taxonomy of different techniques used for addressing the noisy text retrieval task. The first method uses a novel bootstrapping mechanism to refine the OCR’ed text and uses the cleaned text for retrieval. The second method uses the uncorrected or raw OCR’ed text but modifies the standard vector space model for handling noisy text issues. The third method employs robust image features to index the documents instead of using noisy OCR’ed text. We describe these techniques in detail and also discuss their performance measures using standard IR evaluation metrics.     

Contrast enhancement of MRI images using morphological transforms and PSO

Medical imaging plays a crucial role in correct extraction of the significant information for monitoring the patient’s health and providing the quality treatment. A deluge of medical images requires initial interpretation for the presence of any abnormality, however, the correct diagnosis requires the images to be of good quality. To cope with the problem of poor contrast in medical images, this paper presents a method based on morphological transforms to improve the quality of the images. The proposed method incorporates Particle Swarm Optimization to find an optimum value of a parameter which controls the enhancement of the resulting image. The proposed algorithm is executed on a set of MRI images for testing its efficacy. The experimental results are compared in terms of both qualitative and quantitative parameters. The mean opinion score is obtained with the help of experts, which clearly shows the better performance of the proposed method. Furthermore, the parameters like Contrast Improvement Ratio, signal-to-noise ratio, peak signal-to-noise ratio, PL, and Structural Similarity Index are evident of better performance of proposed method when compared with the state-of-the-art methods and few recent methods. The comparison shows that the performance of the proposed method based on morphological transforms incorporating Particle Swarm Optimization is better not only visually but also in terms of other evaluation parameters.

     

Constructivist Management of Knowledge,Communication and Enterprise Innovation: Lessons from Indian Experience

Prime movers of enterprise innovation are inside the organisation. The enterprise NIIT, studied in this paper, tells us how elicitation and recognition of knowledge and its contents set an enterprise on the move. Recognised knowledge is actionable. Each act of recognition is an addition to knowledge content, and such additions took place in NIIT through acts of communications and self-searching. These contents form a large collage that cannot be strewn into a single novelistic episode. Perspectives and context, motives and suggestions render to each member of the enterprise different disjoint appearances of knowledge. There are thus many knowledge systems and multiple narrations, each with small episode-like finality. Enterprise innovation is achieved not through any grand episodic integration of all knowledge contents, but by constructively eliciting further new contents of knowledge, and encouraging acts of communications and discourses on this new knowledge. Constructive management of knowledge and communication towards enterprise innovation has thus been defined. Through such constructive management, NIIT enabled itself innovationally and empowered its members in eliciting knowledge and acting communicatively. A critical feature of knowledge work is that it requires multidisciplinary expertise and mutual learning in order to achieve a complex synthesis of highly specialised state-of-the-art technologies and knowledge domains. A convivial work culture and a culture of communicative acts enable sharing of the non-informatised yet recognised contents of knowledge.