electronics devices and circuits lecture notes pdf

Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf

Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf

... each candidate itemset – To reduce the number of comparisons, store the candidates in a hash structure ã Instead of matching each transaction against every candidate, match it against candidates ... Lattice – General-to-specific vs Specific-to-general Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining by Tan, Steinbach, Kumar â Tan,Steinbach, ... confidence ã Thus, we may decouple the support and confidence requirements © Tan,Steinbach, Kumar Introduction to Data Mining 16 Reducing Number of Comparisons Candidate counting: – Scan the database...

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Always On, Always Connected Finding Growth Opportunities in an Era of Hypermobile Consumers The 2012 Accenture Consumer Electronics Products and Services Usage Report pdf

Always On, Always Connected Finding Growth Opportunities in an Era of Hypermobile Consumers The 2012 Accenture Consumer Electronics Products and Services Usage Report pdf

... 160% 18 133% 19 500% TV Viewing and Purchase Intent Declining As consumers can consume entertainment via more devices, apps and cloud services, their television use and purchase intent are declining. ... most-used devices Total ownership Figure A: Consumer Electronics Used Most Often Figure B: Country-Specific Purchase Plans for Selected Devices Next Previous Table of Contents 2012 Consumer Electronics ... manufacturer's branded store (e.g., Apple store, Sony store, Nokia store) Physical store – consumer electronics retailer (i.e., specialized electronics store that carries many brands) Purchase...

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Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx

Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx

... are found Candidate Generation: ã Merge pairs of frequent subsequences found in the (k-1)th pass to generate candidate sequences that contain k items Candidate Pruning: ã Prune candidate k-sequences ... Rules How do support and confidence vary as we traverse the concept hierarchy? – If X is the parent item for both X1 and X2, then σ(X) ≤ σ(X1) + σ(X2) – If σ(X1 ∪ Y1) ≥ minsup, and X is parent ... new pass over the sequence database D to find the support for these candidate sequences Candidate Elimination: ã Eliminate candidate k-sequences whose actual support is less than minsup © Tan,Steinbach,...

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Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot

Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot

... clusters are irregular or intertwined, and when noise and outliers are present. 6 density-based clusters © Tan,Steinbach, Kumar Introduction to Data Mining 34 Handling Empty Clusters Basic K-means ... the distance to the nearest cluster – To get SSE, we square these errors and sum them. – x is a data point in cluster C i and m i is the representative point for cluster C i ã can show that ... problem to a different domain and solve a related problem in that domain – Proximity matrix defines a weighted graph, where the nodes are the points being clustered, and the weighted edges represent...

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Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot

Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot

... points share more than T neighbors and – the two points are in each others k nearest neighbor list For instance, we might choose a nearest neighbor list of size 20 and put points in the same cluster ... Can Handle Differing Densities Original Points SNN Clustering © Tan,Steinbach, Kumar Introduction to Data Mining 13 Limitations of Current Merging Schemes Closeness schemes will merge (a) and ... reduced – The size of the problems that can be handled is increased © Tan,Steinbach, Kumar Introduction to Data Mining 35 SNN Clustering Can Handle Other Difficult Situations © Tan,Steinbach,...

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Electronic Devices and Circuits doc

Electronic Devices and Circuits doc

... Compensation 281 5.13 Biasing Circuits For Linear Integrated Circuits 284 "This page is Intentionally Left Blank" 26 Electronic Devices and Circuits 1.4 PRINCIPLES OF CRT ... Technology ASICS (Application Specific Integrated Circuits) HYBRIDICs BICMOS MCMs (Multi Chip Modules) 3-D packages 10 Electronic Devices and Circuits Problem 1.3 An electron starts at ... oscilloscope. eRO is an extremely useful and versatile laboratory instrument used for the measurement and analysis of waveforms and other phenomena in electronic circuits. These are basically very...

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MBA 604 Introduction Probaility and Statistics Lecture Notes potx

MBA 604 Introduction Probaility and Statistics Lecture Notes potx

... 89 1 Introduction 89 2 OneWayANOVA:CompletelyRandomizedExperimentalDesign 90 3 TheRandomizedBlockDesign 93 3 Brand 1 Brand 2 Brand 1 90/100 10/100 Brand 2 40/200 160/200 So P =  0.90.1 0.20.8  Question ... 2 (ii) x-2146 p(x).2.2.2.1 43 Chapter 3 Random Variables and Discrete Distributions Contents. Random Variables Expected Values and Variance Binomial Poisson Hypergeometric 1 Random Variables The discrete ... (A)=.2, and P (B)=.4, are A and B mutually exclusive? independent? (ii) If P (A ∪B)=.65, P (A)=.3, and P (B)=.5, are A and B mutually exclusive? independent? (iii) If P (A ∪ B)=.7, P (A)=.4, and...

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wudka j. physics 7, special relativity and cosmology (lecture notes, 2002)(214s)

wudka j. physics 7, special relativity and cosmology (lecture notes, 2002)(214s)

... Greeks and is known only because of a summary statement in Archimedes’ The Sand-Reckoner and a reference by Plutarch. The only surviving work of Aristarchus, On the Sizes and Distances of the Sun and Moon, ... universe and for his pioneering attempt to determine the sizes and distances of the Sun and Moon. Aristarchus was a student of Strato of Lampsacus, head of Aristotle’s Lyceum, coming between Euclid and Archimedes. ... produced the three Cyclops, the three Hecatoncheires, and twelve Titans. However, Uranus was a bad father and husband. He hated the Heca- toncheires and imprisoned them by pushing them into the hidden...

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Tài liệu Lecture Notes in Control and Information SciencesEditors: M. Thoma pdf

Tài liệu Lecture Notes in Control and Information SciencesEditors: M. Thoma pdf

... in du stri es, and expect simultaneously that the researchplanted the root in this kind of ground will be expanded at the researchinstitute etc. of an enterpriseand, expecially and university. At ... (2.40) is called ajointlinearized model. Here, u 1 ( t )and u 2 ( t )denotes the angle input of axis 1and axis2,respec- tively. K p denotes K p 1 of equation (2.23) in thel ow sp eed 1st order mo del of 2.2.3. Fig. 2.12i llustrates the blo ck diagram of the1 st order system. In this section, ... commandto servosystem is aproblem. Thisproblemisabout the form of time functionof command.The problemofcommandcontaining the way of data given must be discussed. In the discussion of this commandsystem,...

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Tài liệu Lecture Notes in Geoinformation and Cartography pdf

Tài liệu Lecture Notes in Geoinformation and Cartography pdf

... National Science Foundation under Grants #40471111 and #70571076, and by the 973 Project under Grant #2001CB5103. Lecture Notes in Geoinformation and Cartography Series Editors: William Cartwright, ... ArcGIS Server and ArcGIS Engine; x Server Side: ESRI ArcGIS Server and ArcIMS; x Application Platforms x Client Side: ArcGIS Desktop and IE Viewer as well as Ar- cObjects, MapObjects and ArcGIS ... Decision Support Platform Spatial and Temporal Modeling Spatial Modeling and Decision Support  Spatial Spread and Temporal Epidemic Trends  Spatial and Temporal Epidemic Forecast- ing...

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Tài liệu Lecture Notes in Economics and Mathematical Systems pdf

Tài liệu Lecture Notes in Economics and Mathematical Systems pdf

... tragic fate and the mathematical legacy of W. Dăoblin see Bru and Yor (2002). Introduction The lecture notes are organized as follows: Chapter 1 gives a concise overview of the theory of Lebesgue and ... differentiation and integration can be stated as X t = X 0 + t  0 ˙ X s ds 2.6 Stopping Times and Local Martingales 41 Proof. From Lemma 2.6.6 take T n ↓ T and d ∈ D n . 1) For X T n ∈F T n and B ∈B d , ... X T (ω):=X T (ω) (ω) is F T -measurable. Lecture Notes in Economics and Mathematical Systems 579 Founding Editors: M. Beckmann H.P. Künzi Managing Editors: Prof. Dr. G. Fandel Fachbereich Wirtschaftswissenschaften Fernuniversität...

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