Heat transfer in partially ionized Erying-Powell liquid containing four types of nano-particles is discussed in this manuscript. Mathematical models for the mixture Erying-Powell plasma and nano-particles are developed and are solved by using finite element method (FEM). Numerical computations are carried out under tolerance 10-5. Physical parameters have significant effects on both thermal boundary layer thicknesses and momentum boundary layer thicknesses. Shear stresses at the surface can be minimized by the Hall and ion slip currents whereas the shear stresses at the sheet for Erying-Powell fluid are high as comparing to the Newtonian fluid. The rate of transfer of heat is significantly influenced by Hall and ion slip parameters. Highest rate of transfer of heat is observed for the case of TiO2 nano-particles. Therefore, it is recommended to disperse TiO2 nano-particles in Erying-Powell fluid for enhancement of heat transfer in Erying-Powell plasma.
Abstract-The initial criteria for evaluating a researcher's output is the number of papers published. Furthermore, for the measurement of author's research quality, the number of citations is significant. Typically, citations are directly linked with the visibility of a research paper. Many researches had shown that the visibility of a research paper can be improved further by using the search engine optimization techniques. In addition, some research already proved that the visibility of an article could improve the citation results. In this article, we analysed the impact of search engine optimization techniques that can improve the visibility of a research paper. Furthermore, this paper also proposing some strategies that can help and making the research publication visible to a large number of users.
<span>Search Engines are used to search any information on the internet. <br /> The primary objective of any website owner is to list their website at the top of all the results in Search Engine Results Pages (SERPs). Search Engine Optimization is the art of increasing visibility of a website in Search Engine Result Pages. This art of improving the visibility of website requires the tools and techniques; This paper is a comprehensive survey of how a Search Engine (SE) works, types and parts of Search Engine and different techniques and tools used for Search Engine Optimization (SEO.) In this paper, we will discuss the current tools and techniques in practice for Search Engine Optimization.</span>
Abstract-The increasing of energy cost and also environmental concern on green computing gaining more and more attention. Power and energy are a primary concern in the design and implementing green computing. Green is of the main step to make the computing world friendly with the environment. In this paper, an analysis on the comparison of green computer with other computing in E-learning environment had been done. The results show that green computing is friendly and less energy consuming. Therefore, this paper provides some suggestions in overcoming one of main challenging problems in environment problems which need to convert normally computing into green computing. In this paper also, we try to find out some specific area which consumes energy as compared to green computing in E -learning centre in Malaysia. The simulation results show that more than 30% of energy reduction by using green computing.
Search Engine Optimization (SEO) plays a very vital role in the development of professional websites. There are some search engines available on the internet such as Yahoo, Ask.com, AOL.com, Baidu, and Bing. Among which Google is the most widely used search engine. Each search engine uses different SEO technique and algorithm, which not only forms the foundation of SEO but affects the position of a website in organic search results as well. As Google modify its algorithm about 500 or more times per year, the web design and internet also evolves dynamically because of changes in SEO techniques and algorithms. However, how well Malaysian universities websites are optimized for other search engines is questionable particularly the critical differences between search engine ranking techniques and algorithms. This research paper tends to answer these vital questions by proposing a comparative analysis of Bing and Google on some Malaysian universities website, analyzing their search engine optimization parameters and outcomes of using Microsoft Bing as compared to its primary competitor, Google.
Today, heart diseases have become one of the leading causes of deaths in nationwide. The best prevention for this disease is to have an early system that can predict the early symptoms which can save more life. Recently research in data mining had gained a lot of attention and had been used in different kind of applications including in medical. The use of data mining techniques can help researchers in predicting the probability of getting heart diseases among susceptible patients. Among prior studies, several researchers articulated their efforts for finding a best possible technique for heart disease prediction model. This study aims to draw a comparison among different algorithms used to predict heart diseases. The results of this paper will helps towards developing an understanding of the recent methodologies used for heart disease prediction models. This paper presents analysis results of significant data mining techniques that can be used in developing highly accurate and efficient prediction model which will help doctors in reducing the number of deaths cause by heart disease.
To the modern Search Engines (SEs), one of the biggest threats to be considered is spamdexing. Nowadays spammers are using a wide range of techniques for content generation, they are using content spam to fill the Search Engine Result Pages (SERPs) with low-quality web pages. Generally, spam web pages are insufficient, irrelevant and improper results for users. Many researchers from academia and industry are working on spamdexing to identify the spam web pages. However, so far not even a single universally efficient method is developed for identification of all spam web pages. We believe that for tackling the content spam there must be improved methods. This article is an attempt in that direction, where a framework has been proposed for spam web pages identification. The framework uses Stop words, Keywords Density, Spam Keywords Database, Part of Speech (POS) ratio, and Copied Content algorithms. For conducting the experiments and obtaining threshold values WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets have been used. An excellent and promising F-measure of 77.38% illustrates the effectiveness and applicability of proposed method.
In this modern age, the internet is a powerful source of information. Roughly, one-third of the world population spends a significant amount of their time and money on surfing the internet. In every field of life, people are gaining vast information from it such as learning, amusement, communication, shopping, etc. For this purpose, users tend to exploit websites and provide their remarks or views on any product, service, event, etc. based on their experience that might be useful for other users. In this manner, a huge amount of feedback in the form of textual data is composed of those webs, and this data can be explored, evaluated and controlled for the decision-making process. Opinion Mining (OM) is a type of Natural Language Processing (NLP) and extraction of the theme or idea from the user's opinions in the form of positive, negative and neutral comments. Therefore, researchers try to present information in the form of a summary that would be useful for different users. Hence, the research community has generated automatic summaries from the 1950s until now, and these automation processes are divided into two categories, which is abstractive and extractive methods. This paper presents an overview of the useful methods in OM and explains the idea about OM regarding summarization and its automation process.
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