Categorical data

Segmentation has a great importance in digital image analysis. It is also one of the most difficult low-level image analysis tasks. Many image processing application apply segmentation as primary step. Image segmentation serve a variety of applications, such as handwritten character identification, medical image analysis as breast cancer detection, in infrared image, automatic target recognition, radar image application, and in pattern recognition application...etc. The quality of the…

Big Data Analytics Introduction In this report, the term Big Data Analytics will be explained and studied, it has been broken down into sub-headings of which Big Data Analytics consists of. The following examines what Big Data is, how it benefits businesses and companies, it determines who is using Big Data and the three V’s of Big Data Analytics. This report examines what Big Data offers and the many opportunities for businesses and companies who wish to collect a lot of information from either…

BLOOD VESSEL SEGMENTATION IN RETINAL FUNDUS IMAGES USING PRE-PROCESSING AND ITERATIVE REFINEMENT Ms.A.Rajapackiam PG Scholar, Department of Computer Science and Engineering, Chandy college of Engineering, Mullakadu,Thoothukudi(T.N)India. rajiamrose91@gmail.com Mr.L.Arokia Jesu Prabhu AP/CSE , Department of Computer Science and Engineering, Chandy college of Engineering, Mullakadu,Thoothukudi(T.N)India. jlplazer@gmail.com ABSTRACT Automatic diagnosis of several diseases such as Diabetic…

Kayla Steinmetz Dr. Lalita Hogan English 112 25 September 2017 Focusing on Distractions Everyday our brains are constantly processing a massive amount of information that is constantly being attained through various technological platforms. With this abundant flow of information, the question of just how productive and how much of this information is actually being processed beneficially is posed. While more ways to obtain information may mean the attainment of more knowledge, it also poses the…

Question 4 a. Big data analyzes millions of pieces of data to produce materials that appropriately fit consumers. There is a plethora amount of information about consumer habits and trends, especially about what, when, how and why consumers buy. It is vital for organizations to put that data to use. b. Disney collects big data from their newest, 'Magic band.' The Magic band allows attendees to enter the parks, unlock hotel rooms, and buy food and merchandise. Also, the band unlocks special…

demographic data parsed through their predictive models, moreover they could presume the gender of the child and the progress of the pregnancy. The recent use of big data and data mining for business, personal and security related advantages have had questionable ethics between consumers and enterprises alike. However, the definitive benefits produced by big data undoubtedly exceed the potential risks that may present themselves over time. The collection and processing of substantial volumes of…

This is because many previous studies showed that networks of human travel patterns have a big impact on the spread of different arboviral diseases. Hence, by employing the United States air travel passenger information data, through an open-source software Gephi, network parameters of human travel patterns like degree centrality, betweenness centrality, closeness centrality and hubs were…

arrange the large amount of data in to clusters.MapReduce came in to picture as it is effective in handling and processing the large amount of data.The main aim of the MapReduce is to read the data and filter the data according to the business logic.we are going to discuss more about the MapReduce in the following business problem. Business Problem: The main problem in todays industries are facing the excess amount of data in there data storage to retrieve or place the data in an order .The…

Enterprise Systems are large scale, integrated application software packages that use the computational, data storage, and data transmission power of modern information technology to support business processes, information flows, reporting, and data analytics within and between complex organizations (Williams and Duff, 2002). Operational excellence is the quest to reliably meet and exceed customer expectations with cost effective and efficient operations. It is the pursuit of conducting…

Six Sigma asserts these activities have to be investigated as they could represent issues in a business process. Based on these assumptions, a high Z-score in the data would be an indicator of unexpected abnormalities. Thus, this research can assess the effectiveness of data-driven IC by creating a volatility function to quantify the fluctuation of IC activities. The usage of the volatility feature is prevalent in the area of finance and economics. The most famous is…