wudka j physics 7, special relativity and cosmology (lecture notes, 2002)(214s)
wudka j. physics 7, special relativity and cosmology (lecture notes, 2002)(214s)
... in Athens and there is ample evidence that he was a student of Anaximander and deeply influ- enced by the teachings of the Pythagoreans, whose religious and philosophical brotherhood he joined at ... Then he told us it works better under water, and so you can picture all of us standing in the bathroom with the water turned on and the key under it, and him rubbing the key with his fi...
Ngày tải lên: 24/04/2014, 16:54
General relativity and cosmology for undergraduates j norbury
... AB cos θ (3.24) where A and B are the magnitudes of the vectors A and B and θ is the angle between them. Thus A.B = A i ˆe i .B j ˆe j =(ˆe i .ˆe j )A i B j ≡ g ij A i B j (3.25) 28 CHAPTER 3. ... simply ∂f ∂x i = ∂f ∂x j ∂x j ∂x i . (3.8) 3.1. CONTRAVARIANT AND COVARIANT VECTORS 25 Let’s ’remove’ f and just write ∂ ∂x i = ∂x j ∂x i ∂ ∂x j . (3.9) which we see is s...
Ngày tải lên: 17/03/2014, 13:34
Special Relativity and Flat Spacetime
... in just a slightly different notation, ǫ ijk ∂ j B k − ∂ 0 E i = 4 J i ∂ i E i = 4 J 0 ǫ ijk ∂ j E k + ∂ 0 B i = 0 ∂ i B i = 0 . (1.74) In these expressions, spatial indices have been raised and ... E i F ij = ǫ ijk B k . (1.75) (To check this, note for example that F 01 = η 00 η 11 F 01 and F 12 = ǫ 123 B 3 .) Then the first two equations in (1.74) become ∂ j F ij − ∂ 0 F 0i = 4 J...
Ngày tải lên: 23/10/2013, 20:20
fayngold m. special relativity and motions faster than light
... speed ap- 20 2 Light and Relativity Author: Moses Fayngold Department of Physics, New Jersey Institute of Technology, Newark. e-mail: fayngold@ADM.NJIT.EDU Illustrations: Roland Wengenmayr, Frankfurt, ... felt a divine joy, as though a new glor- ious life was being conceived in her.” 10 1 Introduction Moses Fayngold Special Relativity and Motions Faster than Light But, alas! Beaut...
Ngày tải lên: 24/04/2014, 16:47
norbury. general relativity and cosmology for undergraduates (wisconsin lecture notes, 1997)(116s)
... AB cos θ (3.24) where A and B are the magnitudes of the vectors A and B and θ is the angle between them. Thus A.B = A i ˆe i .B j ˆe j =(ˆe i .ˆe j )A i B j ≡ g ij A i B j (3.25) 28 CHAPTER 3. ... simply ∂f ∂x i = ∂f ∂x j ∂x j ∂x i . (3.8) 3.1. CONTRAVARIANT AND COVARIANT VECTORS 25 Let’s ’remove’ f and just write ∂ ∂x i = ∂x j ∂x i ∂ ∂x j . (3.9) which we see is s...
Ngày tải lên: 24/04/2014, 17:07
Data Mining Association Rules: Advanced Concepts and Algorithms Lecture Notes for Chapter 7 Introduction to Data Mining docx
... all ranges over the partitions P is K-complete w.r.t C if P ⊆ C ,and ∀X ∈ C, ∃ X’ ∈ P such that: 1. X’ is a generalization of X and support (X’) ≤ K × support(X) (K ≥ 1) 2. ∀Y ⊆ X, ∃ Y’ ⊆ X’ ... Tan,Steinbach, Kumar Introduction to Data Mining 19 Min-Apriori New definition of support: ∑ ∈ ∈ = Ti Cj jiDC ),()sup( min Example: Sup(W1,W2,W3) = 0 + 0 + 0 + 0 + 0.17 = 0.17 TID W1 W2 W3 W4 W5...
Ngày tải lên: 15/03/2014, 09:20
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 • Instead of matching each transaction against every candidate, match it against candidates ... increases – Used by DHP and vertical-based mining algorithms Reduce the number of comparisons (NM) – Use efficient data structures to store the candidates or transactions – No need to match ev...
Ngày tải lên: 15/03/2014, 09:20
Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot
... Cluster Analysis? Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups Inter-cluster ... points into clusters and evaluate the `goodness' of each potential set of clusters by using the given objective function. (NP Hard) – Can have global or local objectives. • Hie...
Ngày tải lên: 15/03/2014, 09:20
Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot
... shapes, orientation, and non-uniform sizes • Difference in densities across clusters and variation in density within clusters • Existence of special artifacts (streaks) and noise The clustering ... measure and maximizing “the shared neighbors” objective function Assign the remaining points to the clusters that have been found © Tan,Steinbach, Kumar Introduction to Data Mining 28...
Ngày tải lên: 15/03/2014, 09:20
MBA 604 Introduction Probaility and Statistics Lecture Notes potx
... (A|B)andP (B|A) (iv) Find P (D)andP (D|C) 26 (v) Are A and B independent? Are C and D independent? (vi) Find P (A ∩B)andP (A ∪B). Law of total probability Let the B,B c be complementary events and ... standard deviation. (ix) Find the first and third quartiles, Q 1 and Q 3 . (x) Repeat (i)-(ix) for the data set (21, 24, 15, 16, 24). Answers: x =5.5, med =5, mode =5 range = 7, MAD=2...
Ngày tải lên: 17/03/2014, 03:20