Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.
Below is a small sample set of documents:
FAU - TAX - 4011
Chapter 01 - Types of Taxes and the Jurisdictions That Use ThemChapter 1 Types of Taxes and the Jurisdictions That Use ThemQuestions and Problems for Discussion 1. Tax payments differ from government fines and penalties because they are not intended to
FAU - TAX - 4011
Chapter 02 - Policy Standards for a Good TaxChapter 2 Policy Standards for a Good TaxQuestions and Problems for Discussion 1. 2. This question is designed to lead to a class discussion of the various tax policy issues introduced in Chapter 2. Historical
FAU - TAX - 4011
Chapter 03 - Taxes as Transaction CostsChapter 3 Taxes as Transaction CostsQuestions and Problems for Discussion 1. 2. Net present value (NPV) of a stream of future cash flows decreases as the discount rate increases. A dollar that certainly will be rec
FAU - TAX - 4011
Chapter 04 - Maxims of Income Tax PlanningChapter 4 Maxims of Income Tax PlanningQuestions and Problems for Discussion 1. a. Mr. L is engaging in tax evasion because he is deliberating understating income (and thus his tax liability) for the year. b. Mr
FAU - TAX - 4011
Chapter 05 - Tax ResearchChapter 5 Tax ResearchQuestions and Problems for Discussion 1. The tax law is far too voluminous and complex for even experienced tax professionals to know the answer to all tax questions. In addition, the tax law changes consta
FAU - TAX - 4011
Chapter 06 - Taxable Income from Business OperationsChapter 6 Taxable Income from Business OperationsQuestions and Problems for Discussion 1. a. The annual business cycle for a plant and garden center might end in the late autumn indicating an October 3
FAU - TAX - 4011
Chapter 07 - Property Acquisitions and Cost Recovery DeductionsChapter 7 Property Acquisitions and Cost Recovery DeductionsQuestions and Problems for Discussion 1. The tax law presumes that no expenditure is deductible unless a specific statutory rule a
FAU - TAX - 4011
Chapter 08 - Property DispositionsChapter 8 Property DispositionsQuestions and Problems for Discussion 1. a. Section 1231 asset. b. Capital asset. c. Section 1231 asset.d. Capital asset. e. Noncapital asset. f. Capital asset.g. Capital asset. h. Secti
FAU - TAX - 4011
Chapter 09 - Nontaxable ExchangesChapter 9 Nontaxable ExchangesQuestions and Problems for Discussion 1. Although Company PJ must have expended $700,000 for the 1,000 acres, it did not take a cost basis in the land. Instead, PJ took a substituted basis o
FAU - TAX - 4011
Chapter 10 - Sole Proprietorships, Partnerships, LLCs, and S CorporationsChapter 10 Sole Proprietorships, Partnerships, LLCs, and S CorporationsQuestions and Problems for Discussion 1. A sole proprietorship is not a legal entity but merely a business ac
FAU - TAX - 4011
Chapter 11 - The Corporate TaxpayerChapter 11 The Corporate TaxpayerQuestions and Problems for Discussion 1. Individuals who perform professional services for clients (doctors, attorneys, CPAs, etc.) cannot avoid liability for malpractice by operating a
FAU - TAX - 4011
Chapter 12 - The Choice of Business EntityChapter 12 The Choice of Business EntityQuestions and Problems for Discussion 1. Capital is not a material income-producing factor in Mr. and Mrs. Velottis professional service business. Therefore, they cannot f
FAU - TAX - 4011
Chapter 14 - The Individual Tax FormulaChapter 14 The Individual Tax FormulaQuestions and Problems for Discussion 1. AGI includes net profit from sole proprietorships, net income from rental real estate, and net business income earned by passthrough ent
FAU - TAX - 4011
Chapter 15 - Compensation and Retirement PlanningChapter 15 Compensation and Retirement Planning1. A rank-and-file employee generally must accept the employment terms offered by management without any direct negotiation to tailor the terms to the employ
FAU - TAX - 4011
Chapter 16 - Investment and Personal Financial PlanningChapter 16 Investment and Personal Financial PlanningQuestions and Problems for Discussion 1. a. Interest on U. S. Treasury bonds is taxable income for federal purposes but tax-exempt for state purp
FAU - TAX - 4011
Chapter 17 - Tax Consequences of Personal ActivitiesChapter 17 Tax Consequences of Personal ActivitiesQuestions and Problems for Discussion 1. The basic income recognition rule is that income from whatever source derived is subject to tax. Under this in
Albright College - ACCT - 201
ABE103HansonCompanyisconstructingabuilding.ConstructionbeganonFebruary1andwascompletedonDecember31. Expenditureswere$1,560,000onMarch1,$1,296,000onJune1,and$3,060,000onDecember31. HansonCompanyborrowed$1,057,000onMarch1ona5year,120otetohelpfinanceconstru
University of Florida - CISE - cot5536
Advanced Data Structures Sartaj SahniClip Art Sources www.barrysclipart.com www.livinggraphics.com www.rad.kumc.edu www.livinggraphics.comWhat The Course Is About Study data structures for: External sorting Single and double ended priority queues Dict
Waterloo - MSCI - 311
Midterm 2 Solutions 1. a) Incremental b)C(Q) Q=1.65, Q 3001.65300+(Q300)1.45 = 60 + 1.45, Q Q 2207552 = 688, not realizable 0.21.65300 < QQ(0) =Q(1) = 2(20+60)7552 = 1467, realizable 0.21.45 Q = 1467 c) 75 52 d = = 2.66 Q 1467 d) 6(1467) = 1.457552
University of Florida - CISE - cot5536
Amortized ComplexityAggregate method. Accounting method. Potential function method.Potential Function P(i) = amortizedCost(i) actualCost(i) + P(i 1) (P(i) P(i 1) = (amortizedCost(i) actualCost(i) P(n) P(0) = (amortizedCost(i) actualCost(i) P(n) P(0) >=
University of Florida - CISE - cot5536
External Sorting Sort n records/elements that reside on a disk. Space needed by the n records is very large. n is very large, and each record may be large or small. n is small, but each record is very large. So, not feasible to input the n records, sor
University of Florida - CISE - cot5536
External Sorting Adapt fastest internal-sort methods. Quick sort best average run time. Merge sort best worst-case run time.Internal Merge Sort Review Phase 1 Create initial sorted segments Natural segments Insertion sort Phase 2 Merge pairs of sor
University of Florida - CISE - cot5536
Tournament TreesWinner trees. Loser Trees.Winner Tree DefinitionComplete binary tree with n external nodes and n 1 internal nodes. External nodes represent tournament players. Each internal node represents a match played between its two children; the w
University of Florida - CISE - cot5536
Improve Run Generation Overlap input,output, and internal CPU work. Reduce the number of runs (equivalently, increase average run length).DISK MEMORY DISKInternal Quick Sort6 2 8 5 11 10 4 1 9 7 3 Use 6 as the pivot (median of 3). Input first, middle,
University of Florida - CISE - cot5536
Optimal Merging Of Runs22 22 13 7 4 3 6 15 9 4 7 3 6 9Weighted External Path LengthWEPL(T) = (weight of external node i) * (distance of node i from root of T)227 4 3 615 9WEPL(T) = 4 * 2 + 3*2 + 6*2 + 9*2 = 44Weighted External Path LengthWEPL(T)
University of Florida - CISE - cot5536
Improve Run Merging Reduce number of merge passes. Use higher order merge. Number of passes = ceil(logk(number of initial runs) where k is the merge order. More generally, a higher-order merge reduces the cost of the optimal merge tree.Improve Run Mer
University of Florida - CISE - cot5536
Double-Ended Priority Queues Primary operations Insert Remove Max Remove Min Note that a single-ended priority queue supports just one of the above remove operations.General Methods Dual min and max single-ended priority queues. Correspondence based
University of Florida - CISE - cot5536
Interval Heaps Complete binary tree. Each node (except possibly last one) has 2 elements. Last node has 1 or 2 elements. Let a and b be the elements in a node P, a <= b. [a, b] is the interval represented by P. The interval represented by a node that has
University of Florida - CISE - cot5536
Leftist TreesLinked binary tree. Can do everything a heap can do and in the same asymptotic complexity. insert remove min (or max) initializeCan meld two leftist tree priority queues in O(log n) time.Extended Binary TreesStart with any binary tree an
University of Florida - CISE - cot5536
Binomial HeapsLeftist trees O(log n) O(log n) O(log n) Binomial heaps Actual Amortized O(1) O(1) O(n) O(1) O(log n) O(1)Insert Remove min (or max) MeldMin Binomial Heap Collection of min trees.2 4 9 7 1453676 5588 969Node Structure Degre
University of Florida - CISE - cot5536
Analysis Of Binomial HeapsLeftist trees O(log n) O(log n) O(log n) Binomial heaps Actual Amortized O(1) O(1) O(n) O(1) O(log n) O(1)Insert Remove min (or max) MeldOperations Insert Add a new min tree to top-level circular list. Meld Combine two cir
University of Florida - CISE - cot5536
Fibonacci HeapsInsert Actual O(1) Amortized O(1) O(log n) O(1) O(log n) O(1)Remove min (or max) O(n) Meld Remove Decrease key (or increase) O(1) O(n) O(n)Single Source All Destinations Shortest Paths12 16 78363 4 456210 3175414Greedy Si
University of Florida - CISE - cot5536
Pairing HeapsInsert Fibonacci Pairing O(1) O(1) O(n) O(1) O(n) O(1)Remove min (or max) O(n) Meld Remove Decrease key (or increase) O(1) O(n) O(n)Pairing HeapsInsert Fibonacci Pairing O(1) O(log n) O(log n) O(log n) O(log n) O(log n)Remove min (or max
University of Florida - CISE - cot5536
Dictionaries Collection of items. Each item is a pair. (key, element) Pairs have different keys.Application Collection of student records in this class. (key, element) = (student name, linear list of assignment and exam scores) All keys are distinct.
University of Florida - CISE - cot5536
Static Dictionaries Collection of items. Each item is a pair. (key, element) Pairs have different keys. Operations are: initialize/create get (search) Each item/key/element has an estimated access frequency (or probability). Consider binary search tr
University of Florida - CISE - cot5536
Dynamic Dictionaries Primary Operations: get(key) => search put(key, element) => insert remove(key) => delete Additional operations: ascend() get(index) remove(index)Complexity Of Dictionary Operations get(), put() and remove()Data Structure Worst C
University of Florida - CISE - cot5536
AVL Trees binary tree for every node x, define its balance factor balance factor of x = height of left subtree of x height of right subtree of x balance factor of every node x is 1, 0, or 1 log2 (n+1) <= height <= 1.44 log2 (n+2)Example AVL Tree-1 10 1
University of Florida - CISE - cot5536
Red Black TreesColored Nodes Definition Binary search tree. Each node is colored red or black. Root and all external nodes are black. No root-to-external-node path has two consecutive red nodes. All root-to-external-node paths have the same number of bla
University of Florida - CISE - cot5536
Red-Black TreesAgain rank(x) = # black pointers on path from x to an external node. Same as #black nodes (excluding x) from x to an external node. rank(external node) = 0.An Example103 22 1 11 37401 1582 30 1201 135451 60 00 00 0 0125
University of Florida - CISE - cot5536
B-Trees Large degree B-trees used to represent very large dictionaries that reside on disk. Smaller degree B-trees used for internal-memory dictionaries to overcome cache-miss penalties.AVL TreesRed-Black Treesm-way Search Trees Each node has up to m
University of Florida - CISE - cot5536
B-Trees (continued) Analysis of worst-case and average number of disk accesses for an insert. Delete and analysis. Structure for B-tree nodeWorst-Case Disk Accesses7 12 4 9 15 20 10 13 16 17 30 4013568Insert 14. Insert 2. Insert 18.Worst-Case Disk
University of Florida - CISE - cot5536
B+-Trees Same structure as B-trees. Dictionary pairs are in leaves only. Leaves form a doubly-linked list. Remaining nodes have following structure: j = number of keys in node.Example B+-tree9 516 30 56 9 16 17 30 4013 index node leaf/data nodeB+-
University of Florida - CISE - cot5536
Splay Trees Binary search trees. Search, insert, delete, and split have amortized complexity O(log n) & actual complexity O(n). Actual and amortized complexity of join is O(1). Priority queue and double-ended priority queue versions outperform heaps, dea
University of Florida - CISE - cot5536
Bottom-Up Splay TreesAnalysis Actual and amortized complexity of join is O(1). Amortized complexity of search, insert, delete, and split is O(log n). Actual complexity of each splay tree operation is the same as that of the associated splay. Sufficient t
University of Florida - CISE - cot5536
Digital Search Trees & Binary Tries Analog of radix sort to searching. Keys are binary bit strings. Fixed length 0110, 0010, 1010, 1011. Variable length 01, 00, 101, 1011. Application IP routing, packet classification, firewalls. IPv4 32 bit IP addres
University of Florida - CISE - cot5536
Binary Tries (continued) split(k). Similar to split algorithm for unbalanced binary search trees. Construct S and B on way down the trie. Follow with a backward cleanup pass over the constructed S and B.Forward Pass Suppose you are at node x, which is
University of Florida - CISE - cot5536
Higher Order Tries Key = Social Security Number. 441-12-1135 9 decimal digits. 10-way trie (order 10 trie).0123456789Height <= 10.Social Security Trie 10-way trie Height <= 10. Search => <= 9 branches on digits plus 1 compare. 100-way trie 441-1
University of Florida - CISE - cot5536
Router/Classifier/Firewall Tables Set of rules(F,A) F is a filter Source and destination addresses. Port number and protocol. Time of day. A is an action Drop packet Forward to machine x (next hop). Reserve 10GB/sec bandwidth.Example Filters QoS-ro
University of Florida - CISE - cot5536
Suffix Trees String any sequence of characters. Substring of string S string composed of characters i through j, i <= j of S. S = cater => ate is a substring. car is not a substring. Empty string is a substring of S.Subsequence Subsequence of string S
University of Florida - CISE - cot5536
Bloom Filters Differential Files Simple large database. Collection/file of records residing on disk. Single key. Index to records. Operations. Retrieve. Update. Insert a new record. Make changes to an existing record. Delete a record.Nave Mode Of Op
University of Florida - CISE - cot5536
Interval Treesi i i i Store intervals of the form [l ,r ], l <= r . Insert and delete intervals. Version 1 Answer queries of the form: which intervals intersect/overlap a given interval [l,r]. Version 2Variant Report just 1 overlapping interval.Defi
University of Florida - CISE - cot5536
Priority Search Trees Keys are distinct ordered pairs (xi, yi). Basic operations. get(x,y) return element whose key is (x,y). delete(x,y) delete and return element whose key is (x,y). insert(x,y,e) insert element e, whose key is (x,y). Rectangle operat
University of Florida - CISE - cot5536
Priority Search Trees Keys are distinct ordered pairs (xi, yi). Min tree on y. Search tree (almost) on x. Two varieties. Search tree is a balanced binary search tree such as a red-black tree. Red-black Priority Search Tree (RBPST) Search tree is a rad
University of Florida - CISE - cot5536
Multidimensional Range Search Static collection of records. No inserts, deletes, changes. Only queries. Each record has k key fields. Multidimensional query. Given k ranges [li, ui], 1 <= i <= k. Report all records in collection such thatli <= ki <=
University of Florida - CISE - cot5536
Quad Trees Region data vs. point data. Roads and rivers in a country/state. Which rivers flow through Florida? Which roads cross a river? Network firewalls. (source prefix, destination prefix, action) (01*, 110*, drop packet)27 dest 24 8 15sourceQu
University of Florida - CISE - cot5536
BSP Trees Binary space partitioning trees. Used to store a collection of objects in ndimensional space. Tree recursively divides n-dimensional space using (n-1)-dimensional hyperplanes.Space Partitioningn-dimensional spacesplitting hyperplane (n-1)-di
University of Florida - CISE - cot5536
R-Trees Extension of B+-trees. Collection of d-dimensional rectangles. A point in d-dimensions is a trivial rectangle.Non-rectangular Data Non-rectangular data may be represented by minimum bounding rectangles (MBRs).Operations Insert Delete Find al
Irvine Valley College - MATH - 3B
1-0=.5(",')iso, ~'),-",1\<."=~ ~_~ha",\-0-=_0 ~_.':)~.f ()(2 o-bb_I-.-+~(\0~c,O-.Q ---6) .i '(~):I-+-<-~)(2+b)(!"~t - ~ : _tio.~~ _~~'"_;~-= 4-(34:.)_ ~0~0 _ -:a)_ \'\.~VL\-c.\';~\-~ _-:")_ t S~l. 9 _'?:"l~. '>~CJ.-~ ~~ (!.
Irvine Valley College - MATH - 3B
Qu\f.IB-1 l~\_\-\(t<) +-=)_\A.o~\<5.O~I-\~o_~ \-a-<.O~=7_ Q(~')~\"iQ._~O~\C._ _-I-Cl)I-H~ \.~).: - S<:. 0=:'1 ~-"M.o'lo.O ~v-.A.S_'=f.')O~.\.a_- _o_~_~ __'_~_-_\ _vt-~IS ~'S1-1+)\ ~ -5"~~J =-2~)<+"oev-I (,c:) . _ -A -
Irvine Valley College - MATH - 3B
Math 3B - Castro conde Quiz 2A (7.4*, 7.5) Start your work after the last question. paper, if needed. I. 2. 3. Evaluate the expressionName: 1.0.#:~ (Use the back and attach more sheet(s) oflog, 6 -log2 15 + log, 20Graph the function g(x) =urLabel i
Irvine Valley College - MATH - 3B
Math 3B - Castroconde Quiz 2B (7.4*, 7.5) Start your work after the last question. paper, if needed. 1. 2. 3. Evaluate the expression Graph the function g(x)Name: 1.0.#:t~<JUse the back and attach more sheens) oflog.I 00 -log3 18 -log3 50= SX.Label