...ASSIGNMENT Cluster Analysis of Godrej India Limited Case Submitted to: Prof. Sreedhara Raman Submitted by: Step 1: Agglomeration Schedule: The first step in Cluster Analysis is to find out the number of clusters that should be made. From the below table we observe that the difference between 16th and 15th value is the highest =4.5. Thus, the number of cluster taken is 4. Agglomeration Schedule | Stage | Cluster Combined | Coefficients | Stage Cluster First Appears | Next Stage | | Cluster 1 | Cluster 2 | | Cluster 1 | Cluster 2 | | 1 | 1 | 19 | 11.000 | 0 | 0 | 12 | 2 | 11 | 20 | 15.000 | 0 | 0 | 11 | 3 | 8 | 9 | 15.000 | 0 | 0 | 8 | 4 | 6 | 10 | 17.000 | 0 | 0 | 11 | 5 | 5 | 13 | 18.000 | 0 | 0 | 12 | 6 | 14 | 18 | 19.000 | 0 | 0 | 15 | 7 | 7 | 15 | 20.000 | 0 | 0 | 15 | 8 | 2 | 8 | 20.500 | 0 | 3 | 14 | 9 | 16 | 17 | 22.000 | 0 | 0 | 14 | 10 | 4 | 12 | 23.000 | 0 | 0 | 16 | 11 | 6 | 11 | 24.000 | 4 | 2 | 13 | 12 | 1 | 5 | 24.000 | 1 | 5 | 13 | 13 | 1 | 6 | 26.750 | 12 | 11 | 16 | 14 | 2 | 16 | 28.000 | 8 | 9 | 17 | 15 | 7 | 14 | 28.000 | 7 | 6 | 18 | 16 | 1 | 4 | 32.500 | 13 | 10 | 19 | 17 | 2 | 3 | 32.800 | 14 | 0 | 18 | 18 | 2 | 7 | 36.250 | 17 | 15 | 19 | 19 | 1 | 2 | 44.300 | 16 | 18 | 0 | Step 2: Final Cluster Centers: From this table we identify the major characteristics of the respondents belonging to different clusters, which will help us to create a Cluster Profile. Final Cluster Centers | ...
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...actively seize the opportunities arising from this trend. Based on the article, cluster is a group of firms and institutions of one industrial sector that are complementing each other along a value chain and also overlapping in a limited geographical area. Clusters are considered to increase the productivity with which companies can compete, nationally and globally. Clusters are also very important aspects of strategic management. Business cluster gives many benefits such as productivity benefits, innovation and higher profitability compared to their isolated competitors. The producers that located within clusters can more easily concentrate on their core competencies and increase productivity. In clusters, it is easier for companies to recruit suitable employees and for employees to specialize in terms of their education. However, a wage-spiral may arise in a very dynamic cluster if employees frequently switch from one firm to another. The significance of employees moving from company to company becomes clearer still when viewed as a mechanism for knowledge exchange. People take their knowledge with them to their new jobs, combining it with the knowledge acquired at their new firms and thus developing the common knowledge base further. This provides an explanation for research findings showing that a few selected centers are host to most of the innovations in an industry. Companies anchored in such clusters can yield, on average, higher productivity than isolated companies and also...
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...Cluster Computing Name Course name Instructor’s name Date of submission Cluster Computing Cluster computing was first heard in the year 1960 from the IBM, the IBM used cluster computing as the second option for connecting their large mainframe in the servers. These cluster computing was used to provide cheap ways or alternative that was considered cost effective in the commercial parallelism. Cluster is the process where computers are tightly or loosely connected and are working together thus seen as one system. The component that are in the cluster are normally interconnected using a fast or local network that is of high speed. The nodes in the network mostly computer that is used as the server normally run their own instance of the operating system. The whole idea of computer cluster started from coming together of computing development that entailed the presence of cheap microprocessor, network that had high speed and the software’s that was considered having a high performance in the distributed mode of computing. The main use of cluster is to boost the performance and the availability compared to using a single computer. The process is cheap and faster if compared to using a single computer. Computer cluster can be used in many ways to start with small corporate clusters with a minority of nodes to roughly faster mainframes example the IBM. Cluster computing has some outstanding importance...
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...and configuring licensing on a cluster-enabled server. These steps assume you configured the clustering on the hardware on which you intend to install the license server. A detailed procedure follows. 1. Ensure that the first node has control of the cluster resources. 2. On the first node of the cluster, start the Citrix Licensing installation from the command-line and install it on the first node to the shared cluster drive (not the quorum drive). 3. Move the resources from the active node in the cluster to the second node. 4. Install the license server on the second node to the same shared location as the first node. 5. Obtain license files that specify the cluster name of the license server as the host name. After obtaining license files, you must add them to the license server and then reread them. 6. Configure your Citrix product to use the cluster name—not the node name—of the license server cluster. Note: When a clustered license server fails over, the cluster service renames the lmgrd_debug.log to the name of the node that previously hosted the services. Then it starts the services on the new active node and creates a new lmgrd_debug.log. To install licensing on a cluster-enabled server 1. Install Java on both cluster nodes. You can find a supported version on the Citrix product CD in the Support folder. 2. Ensure that the cluster IP address, cluster name, and a shared disk are configured as cluster resources and that all the cluster resources are owned by the first...
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...involving cluster analysis are, the different types of clusterings and clusters, the basic algorithms etc. That leads us to the second paper, titled: "Cluster analysis in marketing research: review and suggestions for application". Where the book chapter mainly explains the theory underlying cluster analysis, this paper actually focuses on the practical issues regarding the use and validation of cluster analytic methods. This part of the presentation is built up as follows: first, we provide you guys with a short introduction on the paper. Of course, there is quite some overlap with the book chapter and the first part of the paper so we will keep it short. Second, a major contribution of this paper is its empirical comparison of clustering methods to evaluate their performance. Therefore I will discuss the findings of this comparison with you. In the final part, my team member will guide you through the recommendations for using cluster analysis, as proposed by the authors. This part contains the major issues regarding the use of clustering methods. 2. Problems The main problem is the large number of different clustering methods that makes it hard for a potential user to choose the right method(s) that suits his or her purpose best. As also stated in the book chapter, cluster analysis has independently developed in a multitude of different disciplines. This is the main reason for the fact that (at least at the time, the paper is from 1983) almost a jungle of different cluster analytic...
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...MySQL Cluster Quick Start Guide – LINUX This guide is intended to help the reader get a simple MySQL Cluster database up and running on a single LINUX server. Note that for a live deployment multiple hosts should be used to provide redundancy but a single host can be used to gain familiarity with MySQL Cluster; please refer to the final section for links to material that will help turn this into a production system. 1 Get the software For Generally Available (GA), supported versions of the software, download from http://www.mysql.com/downloads/cluster/ Make sure that you select the correct platform – in this case, “Linux – Generic” and then the correct architecture (for LINUX this means x86 32 or 64 bit). If you want to try out a pre-GA version then check http://dev.mysql.com/downloads/cluster/ Note: Only use MySQL Server executables (mysqlds) that come with the MySQL Cluster installation. 2 Install Locate the tar ball that you’ve downloaded, extract it and then create a link to it: [user1@ws2 ~]$ tar xvf Downloads/mysql-cluster-gpl-7.1.3-linux-x86_64-glibc23.tar.gz [user1@ws2 ~]$ ln -s mysql-cluster-gpl-7.1.3-linux-x86_64-glibc23 mysqlc Optionally, you could add ~/mysqlc/bin to your path to avoid needing the full path when running the processes. 3 Configure For a first Cluster, start with a single MySQL Server (mysqld), a pair of Data Nodes (ndbd) and a single management node (ndb_mgmd) – all running on the same server. Create folders to store the configuration...
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...Nine (Lab): Cluster Analysis MART 307 Assignment Four: Cluster Analysis 1. T When looking at the Agglomeration Schedule for Wards linkage for the last 10 clusters, the difference between coefficients of stage 162 and 16(Cluster #2) is 352.72. The difference between the coefficients of stage 161 and 160(Cluster#3) is 304.538. The difference between the coefficients of stage 160 and 159(Cluster#4) is 177.043. When looking at the chart, there is a biggest jump between clusters 3 and 4, indicating that there is a biggest difference between those two clusters. This is backed up by the Dendrogram as shown to the left, when putting a straight line through the longest horizontal lines; the line is cut by three clusters. Also, when looking at the Ward Scree Plot, the biggest kink is at 3 as shown by the arrow above which shows an abrupt change in angle (elbow.) Which indicates the 3rd cluster being more unique than the forth. The single linkage message also shows we should use 3 clusters, because looking at the Dendrogram, if we put a line through the longest horizontal distances it would be cut at 3 points. I would choose Wards method over Single Linkage because it is much clearer, the dendogram has much clearer clusters and there are fewer clusters. The agglomeration schedule is easier to figure out 2) 1 means not at all considered 2 unlikely to consider 3 would possibly consider 4 would actively consider 5 already do As shown in the Initial Cluster Centers to...
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...A COMPARITIVE STUDY OF CLUSTER ANALYSIS WITH NATURE INSPIRED ALGORITHMS A PROJECT REPORT Submitted by K.Vinodini 310126510043 I.Harshavardhan 310126510039 B.Prasanth kumar 310126510013 K.Sai Sivani 310126510042 in Partial Fulfillment of the requirements for the Award of the Degree of BACHELOR OF TECHNOLOGY in COMPUTER SCIENCE AND ENGINEERING DEPARTMENT OF COMPUTER SCIENCE AND SYSTEMS ENGINEERING Anil Neerukonda Institute of Technology and Science (ANITS) ANDHRA UNIVERSITY : VISAKHAPATNAM – 530003 APRIL 2014 ANIL NEERUKONDA INSTITUTE OF TECHNOLOGY AND SCIENCES ANDHRA UNIVERSITY : VISAKHAPATNAM-530 003 BONAFIDE CERTIFICATE Certified that this project report “A Comparative study of cluster analaysis with Nature Inspired Algorithms”is the bonafide work of “K.Vinodini, I.Harsha, B.V.PrasanthKumar, K.SaiSivani”who carried out the project work under my supervision. Signature Signature Dr S C Satapathy Dr S C Satapathy HEAD OF THE DEPARTMENT ...
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...A COMPUTER IMPLEMENTATION OF ESTIMATED VARIANCES IN MULTI-STAGE CLUSTER SAMPLING SCHEMES L. A. Nafiu, L. Idris, A. F. Busari and A. B. Olaniyan Department of Mathematics and Statistics, Federal University of Technology, Minna, Niger State (lanconserv@yahoo.com) ABSTRACT The computation of sample variances arising from multi-stage cluster sampling schemes or designs are complex and time-consuming. This paper presents a computer software written with Java programing language for implementing some of the available formulars for estimated variances in multi-stage techniques. The software has the advantages of accessibility, cheapness, and ease of use in computing estimated variances in both one-stage, two-stage and three-stage sampling schemes. A data set for estimating number of diabetic patients in Niger state for 2005 was used for illustration. We recommend that computation involving these estimated variances be done with the aid of this software. Keywords: Software, Computation, Multi-stage, Estimated Variances, Time, Data and Diabetic Patients. Introduction Multistage sampling is where the researcher divides the population into clusters, samples the clusters, and then resample, repeating the process until the ultimate sampling units are selected at the last of the hierarchical levels (Okafor, 2002). For instance, at the top level, states may be sampled (with sampling proportionate to state population size); then cities may be sampled; then schools; then classes; and...
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...off-the-shelf PCs by running a Linux clustering system called Beowulf. New developments add the ability to run Beowulf clusters on 64-bit AMD Opteron processors, dramatically improving the performance of clustered computers. Beowulf provides one way to group a set of computers to work on a single task. One PC acts as the master of the cluster, controlling the other computers. The other computers each act as stripped-down computation devices, performing operations in parallel. Each computer in the cluster gets one small piece of an overall task. All the computers in the cluster communicate over a high-speed internal network. The power of Beowulf clustering lies in the usage of off-the-shelf hardware, dramatically reducing the cost for creating what can be supercomputer performance, at least for tasks that work well with clusters. Beowulf clusters work best for computational tasks that can be divided into relatively independent pieces. For example, a lot of weather prediction and graphics ray-tracing for movie special effects fit well into Beowulf-style clusters. One of the neat things about the clusters is that the software can work on older PCs, turning boxes relegated to boat anchors and door stops into computation engines. Beowulf, though, isn't just one software package. There are several packages you can install to make up parts of a Beowulf cluster such as Parallel Virtual Machine (PVM), Message Passing Interface (MPI), or, Local Area Multicomputer MPI (LAM/MPI). Different...
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...hardware and software environment. Installation and maintenance costs were high, and compiling data for all centers was time consuming and difficult. Each night the thousands of centers would upload their data to the main server for consolidation. With the growing number of centers, there wasn’t enough time in the night to process all of the incoming data. Advance America’s system had run up against a wall. It was time for a change. Advance America decided to invest in a new system based on a grid computing architecture. They installed thin client machines to run in each center, connecting via the Web to a fault-tolerant server cluster running Oracle database software. The server cluster consists of a four-node cluster ofIBM P5 series servers, which include four processors per node for a total of 16 processors. The servers in the cluster work as a grid by sharing the work load of the entire organization equally among them. A pair of Cisco load balancers make sure that processing is distributed evenly among the servers for maximum performance. The new system includes a 2 TB storage area network (SAN) that uses an IBM disk...
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... 10. Summary of project References Abstract The purpose of this project is to identify the impact of power and politics in Dan Mart Inc management decision in choosing information technology architecture that can provide a high availability and clustering in a business environment like Dan Mart Inc, this project will also identify the limitation power and politics, advantages and cost of implementing each one so as to have a choice of choosing from them all. But for the sake of this project the use of Oracle cooperation high availability and clustering technologies will be the target. We would be discussing different types of technologies by Oracle such as real application cluster(RAC), automatic storage management (ASM), data guard, grid infrastructure, grid control, cloud control, Flash back technology, database e-memory that will be suitable for Dan Mart Inc business environment. Brief Company Background DanMart is a high volume customer oriented business organization that require 24/7 availability of their services, they handle online sales...
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...Customer Clusters as Sources of Innovation-Based Competitive Advantage Vishal Bindroo, Babu John Mariadoss, and Rajani Ganesh Pillai ABSTRACT The authors examine the effect of customer clusters on a firm’s innovation. They argue that knowledge leveraged from customer clusters can help the firm develop innovations. The authors specifically concentrate on the effect of a firm’s geographical proximity and diversity of customer clusters on innovation outcomes. In addition to showing the importance of customer cluster proximity on firm innovation, they explore the effect of customer cluster heterogeneity on innovation in an international marketing environment. They test the theoretical model using multicountry data (N = 288) drawn from the U.K. innovation survey implemented by the Economic and Social Research Council, which collected the data across five European countries. Theoretical constructs operate largely as hypothesized and explain a substantial proportion of the variation in the different innovation outcomes tested. Keywords: radical innovation, customer cluster, cluster heterogeneity, proximity, innovation speed I nnovation is frequently acknowledged as the source of organizational renewal and growth, the primary source of competitive advantage (Porter 1990), and central to marketing strategy (Varadarajan and Jayachandran 1999). Because innovation is linked to superior financial performance and survival ability of firms (Agarwal, Cockburn, and McHale 2006), creating...
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...Beowulf Clusters Beowulf clusters were created in the early 1990s by two NASA employee’s, Donald Becker, and Thomas Sterling, to serve their computational needs. They did this by connecting multiple personal computers on a local network that ran on free open source software. This cluster of interconnected computers allowed them to solve task that normally only a supercomputer could perform. Beowulf clusters yield supercomputer performance at a fraction of the cost. They are relatively inexpensive to create since they use commodity hardware, such as personal computers. They also use free open source software such as Linux, to serve as their operating system. Clusters achieve multi-instruction-multi-data multiprocessing by using multiple systems, known as nodes, which are joined together. These nodes are connected via a local area network, which allows them to communicate with one another. These systems are capable of running an application simultaneously on all nodes of the cluster, which in turn, significantly increases performance of the system. However, applications have to be specifically written to utilize all of the computers of the cluster. This is done through parallelization, which is a program that is divided into separate components that run in parallel on individual node of the cluster. Beowulf clusters also yield high availability since each node of the cluster can monitor another over LAN. If one computer fails, another can take over whatever task that...
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...21 IDENTIFIED POTENTIAL CLUSTERS INCLUDING ORGANIC PRODUCTS FOR DEVELOPMENT FOR EXPORTS S. No. Products 1 Basmati Rice States Uttar Pradesh Production Clusters Shahajahanpur, Pilibhit, Rampur, Badaun, Bijnor, Moradabad, Phulenagar, Saharanpur, Mujjafarnagar, Meerut, Bulandshahar, Ghaziabad Udham Singh Nagar, Nainital, Dehradun and Haridwar Gurdaspur, Amritsar, Kapur-thala, Hoshiarpur and Nawanshahar Jalandhar, Uttrakhand Punjab 2. Gherkins Andhra Pradesh Karnataka Mahboobnagar, Rangareddy, Karimnagar, Warangal, Medak Ananthapur and Nalgonda Tumkur, Bangalore Urban, Bangalore Rural, Hassan, Kolar, Chitradurga, Dharwad and Bagalkot Ranga Reddy, Medak & parts Mahabob nagar Nasik, Sanghli, Pune, Satara, Ahmednagar and Sholapur Chittoor Krishnagiri Muzaffar-pur, Samastipur, Hajipur, Vaishali, East and West Champaran, Bhagalpur, Begulsarai, Khagaria, Sitamarhi, Saran and Gopalganj Ahmedabad, Khadia, Anand, Vadodra, Surat, Navsari, Valsad, Bharuch and Narmada 3. Grape and Grape Wine Andhra Pradesh Maharashtra 4. Mango pulp Andhra Pradesh, Tamil Nadu Bihar 5. Fresh Vegetables Gujarat Uttar Pradesh Jharkhand Punjab Andhra Pradesh Lucknow, Unnao, Hardoi, Sitapur and Barabanki Ranchi, Hazaribagh and Lohardaga Fatehgarh Sahib, Patiala, Sangrur, Ropar and Ludhiana Chittoor, Rangareddy, Medak, Guntur 6. Fresh Mango Gujarat Ahmedabad, Khadia, Anand, Vadodra, Surat, Navsari, Valsad, Bharuch and Narmada Lucknow, Unnao, Hardo...
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