Temperature Distribution in Resin Impregnated Paper Insulation for Transformer Bushings

The overall reliability of a power transformer depends to a great extent on the sound operation of the bushings thereof. Oil impregnated paper (OIP) insulated bushings have been in use for a long time now. In many situations, it becomes necessary to avoid OIP insulation in bushings. In the recent past, a new technological breakthrough has been achieved whereby the OIP is replaced by epoxy resin impregnated crepe paper (RIP) insulation. This new system has several advantages over OIP and has now become the insulation of choice. However, its long time thermal and electrical performance need to be carefully assessed. This paper reports the results of a study of temperature distribution in the body of insulation, based on the ac conductivity of RIP insulation. A method of computing the maximum thermal voltage of this system is also given.

How to write a passable technical paper

In my job I see many students who have not learned to write a technical paper. When they do competent work, I want them to be able to write passable reports. This article is for them. There are well established principles for citing the relevant work of others; for not copying things without giving credit; for not stealing. If a reader feels you have copied anything, a figure, even a phrase, from elsewhere without citing its source, then you are guilty of plagiarism in the eyes of that reader. Committing plagiarism is so bad that I cannot do justice to it here. So I merely say: never do it. On, then, to writing your own honest and original material. Art requires talent. In contrast, through discipline and persistence alone, you can learn how to differentiate functions and ride bicycles. Similarly, you can write a passable technical paper. You just have to realize that your job does not end with research. Writing a passable paper involves extra work.

Model-theoretic approach to clustering

The paper deals with a model-theoretic approach to clustering. The approach can be used to generate cluster description based on knowledge alone. Such a process of generating descriptions would be extremely useful in clustering partially specified objects. A natural byproduct of the proposed approach is that missing values of attributes of an object can be estimated with ease in a meaningful fashion. An important feature of the approach is that noisy objects can be detected effectively, leading to the formation of natural groups. The proposed algorithm is applied to a library database consisting of a collection of books.

Analysis of the evanescent field coupling between a fiber and a planar waveguide using the explicit finite difference method with a nonuniform mesh (Journal Paper)

We investigate an optical waveguide system consisting of an unclad fiber core suspended at a constant distance parallel to the surface of a planar waveguide. The coupling and propagation of light in the combined system is studied using the three-dimensional explicit finite difference beam propagation method with a nonuniform mesh configuration. The power loss in the fiber and the field distribution in the waveguide are studied as a function of various parameters, such as index changes, index profile, and propagation distance, for the combined system.

A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks

Our study concerns an important current problem, that of diffusion of information in social networks. This problem has received significant attention from the Internet research community in the recent times, driven by many potential applications such as viral marketing and sales promotions. In this paper, we focus on the target set selection problem, which involves discovering a small subset of influential players in a given social network, to perform a certain task of information diffusion. The target set selection problem manifests in two forms: 1) top-k nodes problem and 2) lambda-coverage problem. In the top-k nodes problem, we are required to find a set of k key nodes that would maximize the number of nodes being influenced in the network. The lambda-coverage problem is concerned with finding a set of k key nodes having minimal size that can influence a given percentage lambda of the nodes in the entire network. We propose a new way of solving these problems using the concept of Shapley value which is a well known solution concept in cooperative game theory. Our approach leads to algorithms which we call the ShaPley value-based Influential Nodes (SPINs) algorithms for solving the top-k nodes problem and the lambda-coverage problem. We compare the performance of the proposed SPIN algorithms with well known algorithms in the literature. Through extensive experimentation on four synthetically generated random graphs and six real-world data sets (Celegans, Jazz, NIPS coauthorship data set, Netscience data set, High-Energy Physics data set, and Political Books data set), we show that the proposed SPIN approach is more powerful and computationally efficient. Note to Practitioners-In recent times, social networks have received a high level of attention due to their proven ability in improving the performance of web search, recommendations in collaborative filtering systems, spreading a technology in the market using viral marketing techniques, etc. It is well known that the interpersonal relationships (or ties or links) between individuals cause change or improvement in the social system because the decisions made by individuals are influenced heavily by the behavior of their neighbors. An interesting and key problem in social networks is to discover the most influential nodes in the social network which can influence other nodes in the social network in a strong and deep way. This problem is called the target set selection problem and has two variants: 1) the top-k nodes problem, where we are required to identify a set of k influential nodes that maximize the number of nodes being influenced in the network and 2) the lambda-coverage problem which involves finding a set of influential nodes having minimum size that can influence a given percentage lambda of the nodes in the entire network. There are many existing algorithms in the literature for solving these problems. In this paper, we propose a new algorithm which is based on a novel interpretation of information diffusion in a social network as a cooperative game. Using this analogy, we develop an algorithm based on the Shapley value of the underlying cooperative game. The proposed algorithm outperforms the existing algorithms in terms of generality or computational complexity or both. Our results are validated through extensive experimentation on both synthetically generated and real-world data sets.

Knowledge-based clustering

In the knowledge-based clustering approaches reported in the literature, explicit know ledge, typically in the form of a set of concepts, is used in computing similarity or conceptual cohesiveness between objects and in grouping them. We propose a knowledge-based clustering approach in which the domain knowledge is also used in the pattern representation phase of clustering. We argue that such a knowledge-based pattern representation scheme reduces the complexity of similarity computation and grouping phases. We present a knowledge-based clustering algorithm for grouping hooks in a library.

Assessing Degree of Novelty of Products to Ascertain Innovative Products

Substantial increase in competition compels design firms to develop new products at an increasingly rapid pace. This situation pressurizes engineering teams to develop better products and at the same time develop products faster [1]. Continuous innovation is a key factor to enable a company to generate profit on a continued basis, through the introduction of new products in the market – a prime intention for Product Lifecycle Management. Creativity, affecting a wide spectrum of business portfolios, is regarded as the crucial factor for designing products. A central goal of product development is to create products that are sufficiently novel and useful. This research focuses on the determination of novelty of engineering products. Determination of novelty is important for ascertaining the newness of a product, to decide on the patentability of the design, to compare designers' capability of solving problems and to ascertain the potential market of a product. Few attempts at measuring novelty is available in literature [2, 3, 4], but more in-depth research is required for assessing degree of novelty of products. This research aims to determine the novelty of a product by enabling a person to determine the degree of novelty in a product. A measure of novelty has been developed by which the degree of ''novelty'' of products can be ascertained. An empirical study has been conducted to determine the validity of this method for determining the 'novelty' of the products.

Electrooxidation of formic acid at platinum nanoclusters electrodeposited on PEDOT coated carbon paper electrode

Nanoclusters of Pt were electrochemically deposited on a conducting polymer, namely, poly(3,4-ethylenedioxythiophene) (PEDOT), which was also electrochemically deposited on carbon paper current collector. PEDOT facilitated uniform distribution of Pt nanoclusters, when compared with Pt electrodeposition on bare carbon paper substrate. Spectroscopy data indicated absence of any interaction between PEDOT and Pt. The electrochemically active surface area as measured from carbon monoxide adsorption followed by its oxidation was several times greater for Pt-PEDOT/C electrode in comparison with Pt/C electrode. The catalytic activity of Pt-PEDOT/C electrode for electrooxidation of formic acid was significantly greater than that of Pt/C electrode. Amperometry data suggested that the electrodes were stable for continuous oxidation of HCOOH.