chapter 2 introduction to data structures and

... Engineering Economics Chapter 2 – Unit 1 Introduction to Financial Statements  and the Accounting Equation Learning Objectives – Chapter 2 Upon completion of this chapter you should understand:  Basic concepts associated with the Income Statement ... Additional Reading  Understanding the Income  Statement: http://www.investopedia.com/articles/04/022504.asp Go to Unit 2 The Balance Sheet 18 Trang 7IET 35000 Engineering Economics Chapter 2 – Unit 2 The Balance Sheet ... as discussed in the previous chapter, dividends  can be paid to owner’s (shareholders). The board of directors  for the corporation determines if dividends are to be paid on  common stock and the amount. Remember that dividends on 

Ngày tải lên: 03/02/2020, 22:35

... When entropy reaches a threshold (b), data evaporation can be invoked to  increase entropy by controlled data distortions When entropy drops to a very low level (c), apoptosis can be triggered to  destroy private data Entropy increases (d) if the set of attributes grows or the disclosed attributes  ... Washington, September 14 ­ 16, 2003” by B. Bhargava, C. Farkas, L. Lilien and F.  Makedon, CERIAS Tech Report 2003­34, CERIAS, Purdue University, November 2003 http://www2.cs.washington.edu/nsf2003 or https://www.cerias.purdue.edu/tools_and_resources/bibtex_archive/archive/2003­34.pdf ... Information Assurance and Security, Purdue Univ., Dec. 2003;  www.cerias.purdue.edu/tools_and_resources/bibtex_archive/archive/2003­34.pdf “Internet Security Glossary,” The Internet Society, Aug. 2004; www.faqs.org/rfcs/rfc2828.html B. Bhargava and L. Lilien “Private and Trusted Collaborations,” to appear in Secure Knowledge 

Ngày tải lên: 30/01/2020, 12:32

... Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining by Tan, Steinbach, Kumar © Tan,Steinbach, Kumar Introduction to Data ... and sometimes they don’t Consider an example of five pairs of clusters © Tan,Steinbach, Kumar Introduction to Data Mining 28 10 Clusters Example Iteration 1 4 3 2 8 6 4 y 2 0 -2 ... Kumar Introduction to Data Mining 7 Partitional Clustering Original Points A Partitional Clustering © Tan,Steinbach, Kumar Introduction to Data Mining 8 Hierarchical Clustering p4 p1 p3 p2 p4

Ngày tải lên: 15/03/2014, 09:20

... AU and PU registers The barrel shifter may be used to perform a data shift in the range of 32 (shift right 32-bit) to 231 (shift left 31-bit) 2.2.2 TMS320C55x Buses As illustrated in Figure 2.1, ... unit (PU), an address-data flow unit (AU), and a data computation unit (DU) These units are connected to 12 different address and data buses as shown in Figure 2.1 2.2.1 TMS320C55x Architecture ... 16-bit data-write data buses (EB and FB) and two 24-bit data-write address buses (EAB and FAB) For a single 16-bit data write, only the EB is used A 32-bit data write will use both the EB and FB

Ngày tải lên: 19/10/2013, 23:15

... relational data marts and OLAP cubes Relational data marts store detailed and summarized data in twodimensional structures, optimized for data retrieval Relational data marts tend to store more ... 1: Introduction to Data Warehousing and OLAP Relational Data Sources Topic Objective To finish the section with a discussion of how the relational data source relates to the OLAP cube ! Star and ... PURPOSES ONLY Module 1: Introduction to Data Warehousing and OLAP Raw Data vs Business Information Topic Objective To describe the differences and relationships between raw data and business information

Ngày tải lên: 21/12/2013, 19:15

... Trang 1Chapter 1:Introduction to Systems Analysis and Design Trang 2• Understand the fundamental systems development life cycle and its four phases. • Understand the evolution of ... Analysis & Design• Attempt to balance emphasis on data and Trang 24THE UNIFIED PROCESSTrang 25The Unified Process• A specific methodology that maps out when and how to use the various UML techniques ... Trang 21Agile DevelopmentExtreme Programming Trang 22Selecting the Right MethodologyUsefulness for Waterfall Parallel Phased Prototyping Throwaway Prototyping Extreme Programming Trang 23Object-Oriented

Ngày tải lên: 16/05/2017, 13:42

... Boom = 122.22% Normal = 13.33% Recession = –100% Expected return = × 122.22 + × 13.33 + × (−100)= 23.33% Variance = 0.3 × (122.22 − 23.33)2 + × (13.33−23.33)2 + × (−100−23.33)2 = 6025.8 Standard ... (−28 – 5.2)2 + × (8 – 5.2)2 + × (48 – 5.2)2 = 700.96 Standard deviation = = 26.5% Portfolio Rate of Return Boom Normal Recession (−28 + 122.22)/2 = 47.11% (8 + 13.33)/2 = 10.665% (48 –100)/2 ... Portfolio Return 22.330 (0.163) 359.36 (0.103) 24.170 (0.309) (0.299) 0.166 26.690 (0.022) 400.52 (0.135) 35.00 4.460 (0.071) 27.290 0.061 463.29 (0.022) 31.140 (0.002) 4.800 (0.002) 25.720 (0.065)

Ngày tải lên: 24/02/2018, 08:34

... Average shares outstanding at year end taken from Annual Report (in millions)­ 2007 = 355.3 and 2006 =340.0 (Note 15) 2 Average Stock Price 2007 =$34.67, 2006 = $23.25. For each year, average  stock price was computed as sum of monthly adjusted closing prices (close  ... savings from refunding: Trang 1211 000,195 $ 20 = $2,264,127 Finally, we calculate the net present value from bond refunding: PV of net savings over 5 years $2,264,127 Since the NPV is positive, ... prices adjusted for dividends and stock splits) divided by 12. Monthly closing  price taken from Yahoo Finance. 2006- Long-term debt (market value) = 7,054.0/(340.0 x $23.25) = 0.89 2007- Long-term debt

Ngày tải lên: 24/02/2018, 08:34

... 1 Chapter 1, Introduction to e­Business  and e­Commerce Outline 1.1 1.2 1.3 1.4 1.5 1.6 Introduction: Transitioning to the Web History of the Internet History of the Web Internet and World Wide Web Development ... Transmission Control Protocol (TCP) – ensures that messages are properly routed from sender to  receiver and that those messages arrived intact  2001 Prentice Hall, Inc.  All rights reserved 1.2 History of the Internet ... Implemented the ARPAnet, the grandparent of today’s  Internet  • Packet switching – Digital data is sent in small packages called packets • Packets – Contain data, address information, error­control information  and sequencing information 

Ngày tải lên: 18/01/2020, 17:40

... Trang 2In this chapter you will learnIn this chapter you will learn The definition and causes of economic growth The nature and cause of the business cycle The nature of unemployment and its ... measurement The definition of inflation and how it is measured The redistribution effects of inflation The output effects of inflation Trang 3Chapter 7 Topics Chapter 7 TopicsEconomic Growth The Business ... changes in productivity – money supply changes – total spending changes Cyclical Impact: Durables & Nondurables Trang 15Chapter 7 Topics Chapter 7 TopicsEconomic Growth The Business Cycle Unemployment

Ngày tải lên: 04/02/2020, 11:10

... Trang 1Chapter 1:Introduction to Systems Analysis and Design Trang 2• Understand the fundamental systems development life cycle and its four phases. • Understand the evolution of ... Throwaway Prototyping Trang 21Agile DevelopmentExtreme Programming Trang 22Selecting the Right Extreme Programmi ng Trang 23Object-Oriented Analysis & Trang 24THE UNIFIED PROCESSTrang 25The Unified ... should the system do for us? Where and when will it be used? Trang 9SDLC: Design1 Develop a design strategy 2 Design architecture and interfaces 3 Develop databases and file specifications 4 Develop

Ngày tải lên: 15/05/2020, 22:24

... the number Trang 22not clickedactive - you have clicked it and you have not yet seen the new page Trang 23Tags and Attributes tags that are pretty much there to serve as handles for styling ... and Clear Trang 391 Float and ClearTrang 402 Inline-block elementsTrang 41n inline-block elements are like inline elements butthey can have a width and height 2 Inline-block elements Trang 422 ... straightforward - and allows nice design within the standards with reasonable effort levels n Site layout and markup is further evolving - mostly to make it increasingly possible to support desktop like

Ngày tải lên: 09/04/2023, 06:48

... k =1 Introduction to Data Mining 49 Euclidean Distance point p1 p2 p3 p4 p1 p3 p4 p2 0 y 1 p1 p1 p2 p3 p4 x 2. 828 3.1 62 5.099 p2 2. 828 1.414 3.1 62 p3 3.1 62 1.414 p4 5.099 3.1 62 Distance Matrix ... 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 ... Kumar Introduction to Data Mining 27 Aggregation Variation of Precipitation in Australia Standard Deviation of Average Monthly Precipitation © Tan,Steinbach, Kumar Introduction to Data Mining Standard...

Ngày tải lên: 15/03/2014, 09:20

... | t ) ]2 j C1 C2 P(C1) = 0/6 = C1 C2 P(C1) = 1/6 C1 C2 P(C1) = 2/ 6 © Tan,Steinbach, Kumar P(C2) = 6/6 = Gini = – P(C1 )2 – P(C2 )2 = – – = P(C2) = 5/6 Gini = – (1/6 )2 – (5/6 )2 = 0 .27 8 P(C2) = 4/6 ... B? C1 Yes No C2 Gini = 0.500 Gini(N1) = – (5/6 )2 – (2/ 6 )2 = 0.194 Gini(N2) = – (1/6 )2 – (4/6 )2 = 0. 528 © Tan,Steinbach, Kumar Node N1 Node N2 C1 C2 N1 N2 Gini=0.333 Introduction to Data Mining ... (3/3 )2 – (0/3 )2 =0 Gini(N2) = – (4/7 )2 – (3/7 )2 = 0.489 © Tan,Steinbach, Kumar Node N2 C1 C2 N1 N2 Gini=0.361 C1 C2 Gini = 0. 42 Gini(Children) = 3/10 * + 7/10 * 0.489 = 0.3 42 Gini improves !! Introduction...

Ngày tải lên: 15/03/2014, 09:20

... 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 ACD BD 345 D BC ... Itemsets Minimum support = 124 123 A 12 124 AB 12 ABC 24 AC ABD ABE AE 345 D BC BD ACD 24 5 C 123 24 123 4 B AD Closed but not maximal null ACE BE ADE BCD E 24 CD BCE Closed and maximal 34 CE BDE 45 ... 357 689 Introduction to Data Mining 367 368 22 Subset Operation Using Hash Tree Hash Function transaction 1+ 23 56 2+ 356 12+ 356 1,4,7 3+ 56 3,6,9 2, 5,8 13+ 56 23 4 567 15+ 145 136 345 124 457...

Ngày tải lên: 15/03/2014, 09:20

... Events 1 ,2, 4 2, 3 1 ,2 2,3,4 1, 2, 3,4 2, 4,5 3, 4, 1, 2, 4, Introduction to Data Mining Minsup = 50% Examples of Frequent Subsequences: < {1 ,2} > < {2, 3} > < {2, 4}> < {3} {5}> < {1} {2} > < {2} {2} > ... B B C Timestamp 10 20 23 11 17 21 28 14 © Tan,Steinbach, Kumar Events 2, 3, 6, 1 4, 5, 7, 8, 1, 1, 1, 8, Introduction to Data Mining 26 Examples of Sequence Data Sequence Database Sequence Element ... Tan,Steinbach, Kumar Introduction to Data Mining 15 Min-Apriori (Han et al) Document-term matrix: TID W1 W2 W3 W4 W5 D1 2 0 D2 0 2 D3 0 D4 0 1 D5 1 Example: W1 and W2 tends to appear together in the...

Ngày tải lên: 15/03/2014, 09:20

... 19 82- 1994) 90 90 24 22 25 60 60 13 26 14 30 30 16 20 17 latitude latitude 21 15 18 0 19 -30 23 -30 -60 -60 11 -90 -180 12 -150 - 120 -90 -60 -30 30 60 90 -90 -180 -150 - 120 -90 10 120 150 180 -60 ... Introduction to Data Mining 22 Experimental Results: CURE (9 clusters) © Tan,Steinbach, Kumar Introduction to Data Mining 23 Experimental Results: CURE (15 clusters) © Tan,Steinbach, Kumar Introduction to ... Kumar Introduction to Data Mining 17 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data Mining 18 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data...

Ngày tải lên: 15/03/2014, 09:20

... 341 26 0 National 27 3 36 Metro 943 746 Sports 738 573 Entertainment © Tan,Steinbach, Kumar Total Articles 555 354 27 8 Introduction to Data Mining 19 Clustering of S&P 500 Stock Data Observe Stock ... day © Tan,Steinbach, Kumar Introduction to Data Mining 28 Challenges of Data Mining Scalability Dimensionality Complex and Heterogeneous Data Data Quality Data Ownership and Distribution Privacy ... 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?...

Ngày tải lên: 15/03/2014, 09:20

... provided on thetonext slide © Tan,Steinbach, Kumar Introduction Data Mining 21 Contour Plot Example: SST Dec, 1998 Celsius © Tan,Steinbach, Kumar Introduction to Data Mining 22 Visualization ... slides © Tan,Steinbach, Kumar Introduction to Data Mining 23 Visualization of the Iris Data Matrix standard deviation © Tan,Steinbach, Kumar Introduction to Data Mining 24 Visualization of the Iris ... Tan,Steinbach, Kumar 28 – Each 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...

Ngày tải lên: 15/03/2014, 09:20

... Repeat Step (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 ... Single 70K No Yes Married 120 K No No Divorced 95K Yes = | 2/ 4 – 1 /2 | + | 2/ 4 – 1 /2 | = No Married No d(Married,Divorced) Yes Divorced 22 0K No = | 0/4 – 1 /2 | + | 4/4 – 1 /2 | = No Single 85K Yes ... according to distance • weight factor, w = 1/d2 © Tan,Steinbach, Kumar Introduction to Data Mining 41 Nearest Neighbor Classification… Choosing the value of k: – If k is too small, sensitive to noise...

Ngày tải lên: 15/03/2014, 09:20