introduction to data conversion chapter 12

... 1Contemporary Concepts and Cases Chapter TwelveCapacity Planning  Trang 3Hierarchy of Capacity Decisions(Fig 12.1) Facilities decisions Aggregate planning Trang 8Factors Affecting Facilities Strategy ... Continue (go to 5) until you meet all constraints. Trang 19Options for Influencing Trang 21Level Load StrategyProduce products and services at a  constant rate   Avoid making changes to  operations ... constant rate   Avoid making changes to  operations Trang 23Table 12.1: Comparison of Chase versus Level Strategy Chas e  Trang 26End of Chapter Twelve

Ngày tải lên: 25/05/2021, 21:40

... Trang 1Introduction to Data AccessWelcome to Chapter 5, where we will lay out the cornerstones of working with databases This chapter is an introduction to the integration with popular Java data-access ... expect It’s up to you, as a developer, to decide howyou expect them to occur and to use transactions to meet your goals Trang 3• Network connections to database systems are typically hard to control ... Class public class NewsletterSubscriptionDataAccess { private DataSource dataSource; public void setDataSource(DataSource dataSource) {this.dataSource = dataSource; }public void addNewsletterSubscription(int

Ngày tải lên: 05/10/2013, 04:20

... three chapters They discuss the basic approaches to datacompression and describe a few popular techniques and methods that are commonlyused to compress data Chapter 1 introduces the reader to the ... specific type of data The goal of the book is to introduce the reader to the chief approaches, methods,and techniques that are currently employed to compress data The main aim is to startwith a ... channel.The third factor that affects the storage and transmission of data is security Gener-ally, we do not want our data transmissions to be intercepted, copied, and read on theirway Even data saved on

Ngày tải lên: 14/12/2013, 15:15

... sequence of CLs are compressed to 17, 112, and 12 consecutive zeros in an SQare compressed to 18, 012.The sequence of CLs is compressed in this way to a shorter sequence (to be termed SSQ) of integers ... 2order to remove ambiguity, the term “edoc” is used here to refer to them Each edoc isconverted to a prefix code that’s output The first table allocates edocs 0 through 255to the literals, edoc 256 to ... interval [0.1, 0.512] can be specified by the longer numbers 0.1 and 0.512 The very narrow interval [0.12575, 0.1257586] is specified by the long numbers 0.12575 and 0.0000086 Trang 12The output of

Ngày tải lên: 14/12/2013, 15:15

... ten-sile side prior to bending Equation 12.5.1 shows that an ideal elastic response, with a constant value of T o, gives σI proportional to P−1/3 This relationship ap-plies to well-developed cone ... sides of the impression Various experimental factors affect the value of VDH as calculated using Eq 12.6.1a Vickers hardness data are usually quoted together with the load used and the loading time ... approaches that corresponding approximately to the hardness value H Figure 12.3.2 shows the results for a coarse-grained micaceous glass-ceramic (see also Fig 12.2.2) The solid line shows the Hertzian

Ngày tải lên: 11/08/2014, 09:20

... were unsatisfactory. Proposed saltwater values of 0.025 µ g/L (24-h average), not to exceed 3.7 µ g/L at any time (Table 12.1), provided safety factors of 4 to 8O against acute toxicity (based ... values were 53 to 175 based on the 24-h mean, and 18 to 59 based on the maximum permissible concentration (Table 12.1). However, more recent freshwater criteria of 0.012 µg/L, not to exceed 2.4 ... (Table 12.1; USEPA, 1985), dramatically reduce the level of protection afforded aquatic biota: safety factors for acute toxicities are now 8 to 167 based on the 96-h average, and only 0.04 to 0.8

Ngày tải lên: 11/08/2014, 20:21

... 7.6.1 The Protocol 118 7.6.2 Simulations 118 7.7 Discussion 122 8 Space–Time Processing .125 8.1 Introduction 125 8.2 Discrete Space–Time Channel and Signal Models 129 8.3 Space–Time ... mountains) and users traveling on vehicles To aggravate further the capacity prob-lem, in 1990s the Internet gave the people the tool to get data on-demand (e.g., stock quotes, news, weather reports, ... referred to as Mobile Ad hoc NETwork (MANET), and it is beginning to emerge using BluetoothTM technology BluetoothTM is a short-range, low-power radio link (10–100 m) that allows two or more BluetoothTMdevices

Ngày tải lên: 13/08/2014, 02:20

... immediate solution to this Trang 812 INTRODUCTION TO SMART ANTENNAScell microcell FIGURE 2.6: Cell-splitting. problem was to subdivide a cell into smaller cells; this technique is referred to as cell ... Transmit Data Receive Process Wireless Channel Receive Data Transmit Data Receive Data FIGURE 2.3: A general antenna system for broadband wireless communications [ 1 ]. Trang 610 INTRODUCTION TO SMART ... (MS) The data communication from the BS to the MS is usually referred to as the downlink or forward channel Similarly, the data communication from the MS to the BS is usually referred to as the

Ngày tải lên: 13/08/2014, 02:21

... is fixed to the optimum direction (toward which the signal-to-noise ratio is maximized). In this direction the maximum of the pattern is ideally toward the desired signal. 26 INTRODUCTION TO SMART ... antenna branches are demodulated to baseband with quadrature demodulator and processed with correlator or matched filter detector. The output is then applied to a diversity combiner. This procedure ... does not match the originally transmitted data bit. The bit error rate (BER) is the ratio of the number of bit errors to the total number of transmitted data bits [69]. From Fig. 3.4, we observe

Ngày tải lên: 13/08/2014, 02:21

... adjacent elements The vector of relative phases is referred to as the steering vector (SV), also mentioned in the previous chapter A more general concept is the array response vector (ARV) which is ... [125] Even though the sampling structure leads to a convenient method of computing a beamformed output by exploiting a structure amenable to FFT processing, it does not need to be uniform [125] ... the mode vector a(θ i) is tantamount to knowing the angleθ i [126] Furthermore, for a set of data observations L > K, we can form the matrices X = [x(1), x(2), , x(L)] , (5.12a) S = [s(1),

Ngày tải lên: 13/08/2014, 02:21

... necessary electronics to downconvert the received signal to baseband and for analog-to-digital (AD) conversion for digital beamforming. To simplify the analysis of this chapter, only baseband ... continually update the weight vector to meet the new requirements imposed by the varying conditions [98] This need to update the weight vector, without a priori information, leads to estimating the covariance ... estimate of the weight vector is [22] wopt= R−1xx CHR−1xxC −1 Trang 1096 INTRODUCTION TO SMART ANTENNASAs a special case, a requirement would be to force the beam pattern to be constant in the

Ngày tải lên: 13/08/2014, 02:21

... algorithm supplies this information to the beamformer to orient the maximum of the radiation pattern toward the SOI and to reject the interferers by placing nulls toward their directions The most ... algorithm in [124] and the two-dimensional (2D) unitary ESPRIT algorithm focus on computing the azimuth and elevation angles while neglecting to provide a Trang 6112 INTRODUCTION TO SMART ANTENNASTABLE ... iterative Newton method The MI-ESPRIT method was extended from the one-dimensional (1D) DOA case to computation of both azimuth and elevation directions in [124] where approximations were used to get

Ngày tải lên: 13/08/2014, 02:21

... better, customized services for an edge (e.g in Customer Relationship Management) © Tan,Steinbach, Kumar Introduction to Data Mining Why Mine Data? Scientific Viewpoint Data collected and stored at ... analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns © Tan,Steinbach, Kumar Introduction to Data Mining What is (not) Data Mining? ... © Tan,Steinbach, Kumar Total Articles 555 354 278 Introduction to Data Mining 19 Clustering of S&P 500 Stock Data Observe Stock Movements every day Clustering points: Stock-{UP/DOWN} Similarity...

Ngày tải lên: 15/03/2014, 09:20

... Kumar Introduction to Data Mining Types of data sets Record – Data Matrix – Document Data – Transaction Data Graph – World Wide Web – Molecular Structures Ordered – Spatial Data – Temporal Data ... Tan,Steinbach, Kumar Introduction to Data Mining 19 Ordered Data Spatio-Temporal Data Average Monthly Temperature of land and ocean © Tan,Steinbach, Kumar Introduction to Data Mining 20 Data Quality ... and Dense Linear System Solvers Introduction to Data Mining 16 Chemical Data Benzene Molecule: C6H6 © Tan,Steinbach, Kumar Introduction to Data Mining 17 Ordered Data Sequences of transactions...

Ngày tải lên: 15/03/2014, 09:20

... object Introduction to Data Mining separate face becomes a Star Plots for Iris Data Setosa Versicolour Virginica © Tan,Steinbach, Kumar Introduction to Data Mining 29 Chernoff Faces for Iris Data ... Tan,Steinbach, Kumar Introduction to Data Mining 35 OLAP Operations: Data Cube The key operation of a OLAP is the formation of a data cube A data cube is a multidimensional representation of data, together ... percentile © Tan,Steinbach, Kumar Introduction to Data Mining 17 Example of Box Plots Box plots can be used to compare attributes © Tan,Steinbach, Kumar Introduction to Data Mining 18 Visualization...

Ngày tải lên: 15/03/2014, 09:20

... same data! 10 © Tan,Steinbach, Kumar Introduction to Data Mining Decision Tree Classification Task Decision Tree © Tan,Steinbach, Kumar Introduction to Data Mining Apply Model to Test Data Test Data ... that belong to more than one class, use an attribute test to split the data into smaller subsets Recursively apply the procedure to each subset © Tan,Steinbach, Kumar Introduction to Data Mining ... Determine how to split the records • How to specify the attribute test condition? • How to determine the best split? – Determine when to stop splitting © Tan,Steinbach, Kumar Introduction to Data Mining...

Ngày tải lên: 15/03/2014, 09:20

... (2) and (3) until stopping criterion is met © Tan,Steinbach, Kumar Introduction to Data Mining 14 Example of Sequential Covering (ii) Step © Tan,Steinbach, Kumar Introduction to Data Mining 15 Example ... Step Introduction to Data Mining 16 Aspects of Sequential Covering Rule Growing Instance Elimination Rule Evaluation Stopping Criterion Rule Pruning © Tan,Steinbach, Kumar Introduction to Data ... that have the k smallest distance to x © Tan,Steinbach, Kumar Introduction to Data Mining 39 nearest-neighbor Voronoi Diagram © Tan,Steinbach, Kumar Introduction to Data Mining 40 Nearest Neighbor...

Ngày tải lên: 15/03/2014, 09:20

... 245 C 123 AD 123 4 ABDE ACDE BCDE ABCDE Introduction to Data Mining 29 Maximal vs Closed Frequent Itemsets Minimum support = 124 123 A 12 124 AB 12 ABC 24 AC ABD ABE AE 345 D BC BD ACD 245 C 123 ... {A,B,C,D} © Tan,Steinbach, Kumar Introduction to Data Mining 28 Maximal vs Closed Itemsets TID Items ABC ABCD BCE ACDE DE Transaction Ids null 124 123 A 12 124 AB 12 24 AC ABC B AE 24 ABD ABE 2 ... support © Tan,Steinbach, Kumar Introduction to Data Mining 12 Illustrating Apriori Principle Found to be Infrequent Pruned supersets © Tan,Steinbach, Kumar Introduction to Data Mining 13 Illustrating...

Ngày tải lên: 15/03/2014, 09:20

... 7, 8, 1, 1, 1, 8, Introduction to Data Mining 26 Examples of Sequence Data Sequence Database Sequence Element (Transaction) Event (Item) Customer Purchase history of a given customer A set of items ... need to perform more passes over the data – May miss some potentially interesting cross© Tan,Steinbach, Kumar Introduction to Data Mining 25 level association patterns Sequence Data Sequence Database: ... Kumar Introduction to Data Mining 20 Multi-level Association Rules Food Electronics Bread Computers Milk Wheat Skim White Foremost © Tan,Steinbach, Kumar 2% Desktop Kemps Introduction to Data...

Ngày tải lên: 15/03/2014, 09:20

... Tan,Steinbach, Kumar Introduction to Data Mining Notion of a Cluster can be Ambiguous How many clusters? Six Clusters Two Clusters Four Clusters © Tan,Steinbach, Kumar Introduction to Data Mining Types ... hierarchical tree © Tan,Steinbach, Kumar Introduction to Data Mining Partitional Clustering Original Points © Tan,Steinbach, Kumar A Partitional Clustering Introduction to Data Mining Hierarchical Clustering ... Tan,Steinbach, Kumar Introduction to Data Mining 18 Clustering Algorithms K-means and its variants Hierarchical clustering Density-based clustering © Tan,Steinbach, Kumar Introduction to Data Mining 19...

Ngày tải lên: 15/03/2014, 09:20