08-02-10 Static Analysis Considerations for Stack Usage Static Analysis Considerations for Stack Usage ESC-423 Gerald T. Rigdon Fellow‚ Software Engineering Boston Scientific‚ Inc. gerald.rigdon@bsci.com Hiten Doshi Fellow‚ Software Engineering Boston Scientific‚ Inc. hiten.doshi@bsci.com Xin Zheng Software Engineer Boston Scientific‚ Inc. xin.zheng@bsci.com In [3]‚ David N. Kleidermacher‚ chief technology officer at Green Hills Software‚ discussed future directions for
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GLOBAL CODE ALGORITHM Get the data point from the STL file. These points are saved in form of Matrices. For Example‚ the Vertex matrix is saved a 3-dimensional matrix‚ having 3 vertices for each face‚ and each vertex have three coordinates. So the size of the matrix V will be D1x3x3‚ where D1 is the number of faces. In order to simplify mesh‚ we have used the method where we combine the two vertices of the face if they are less than a threshold value‚ say t= 1.1 units. For a particular face Fn
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A problem-solving search can either forward or backward. What factors determine the choice of direction for a particular problem? Farword Versus Backword Reasoning. FORWARD VERSUS BACKWARD REASONING (Search Direction) A search procedure must find a path between initial and goal states. There are two directions in which a search process could proceed. (1) Reason forward from the initial states: Being form the root of the search tree. General the next level of the tree by finding all the rules whose
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N: maximum number of keys per node. D : node from which key is to be deleted. L : left sibling of D R: right sibling of D After deleting key from leaf node D‚ if D contains less than ceil(N/2) keys ( i.e. underflow in D)‚ then check the following cases. Redistribution or Merging 1) Redistribution for Leaf node i) If L or R node contains ceil(N/2) + 1 or more keys then a) Move the rightmost key from L to D in case of left sibling. b) Move
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Pradeep reddy Pinninti - 85025 1- Depth-first search always expands at least as many nodes as A* search with an admissible heuristic FALSE. Depth-first search may possibly‚ sometimes‚ expand fewer nodes than A* search with an admissible heuristic. E.g.‚ it is logically possible that sometimes‚ by good luck‚ depth-first search may march directly to the goal with no back-tracking. 2- h(n) = 0 is an admissible heuristic for the 8-puzzle TRUE. h(n)=0 NEVER over-estimates the remaining optimal distance
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Bicycle Stopping Distance Design Experiment Introduction Training wheels are additional wheels that are mounted parallel to the rear wheel of a bicycle that have been use to assist children to balance their bicycle until they have developed a usable sense of balance on the bicycle. In this experiment we aim to discover how does the size‚ or diameter‚ of the training wheel affect the stopping distance of the bike thus finding out which size training wheel is the most effective in reducing
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PLANAR DRAWINGS OF BIPARTITE GRAPHS BY ELIMINATING MINIMUM NUMBER OF EDGES MUHAMMAD OARISUL HASAN RIFAT Department of Computer Science and Engineering Chittagong University of Engineering & Technology (CUET)‚ Chittagong-4349‚ Bangladesh. PLANAR DRAWINGS OF BIPARTITE GRAPHS BY ELIMINATING MINIMUM NUMBER OF EDGES A thesis is submitted in partial fulfillment of the requirements for the degree of Science in Computer Science and Engineering. By Muhammad Oarisul Hasan Rifat (0404054) Supervised
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OPERATIONS MANAGEMENT ASSIGNMENT Topic: COMPUTERIZED LAYOUT ANALYSIS TECHNIQUES Submitted By: SAMYADIP CHAKRABORTY MOHD. ABDUL NAYEEM PhD Batch -2010 COMPUTERIZED LAYOUT ANALYSIS TECHNIQUES In the field of computerized layout analysis‚ a number of computerized layout programs have been developed since the 1960s and 70s. But the most time tested computerized layout techniques and software program packages that are frequently used are- CRAFT‚ CORELAP‚ ALDEP‚ etc. Originally developed
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Backtracking General method • Useful technique for optimizing search under some constraints • Express the desired solution as an n-tuple (x1 ‚ . . . ‚ xn ) where each xi ∈ Si ‚ Si being a finite set • The solution is based on finding one or more vectors that maximize‚ minimize‚ or satisfy a criterion function P (x1 ‚ . . . ‚ xn ) • Sorting an array a[n] – Find an n-tuple where the element xi is the index of ith smallest element in a – Criterion function is given by a[xi ] ≤ a[xi+1 ] for 1 ≤ i < n
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| Leonhard Euler | A short biography | | Jessica Fleming | 3/4/2013 | | Leonhard Euler (15 April‚ 1707- 18 September‚ 1783) was a Swiss mathematician and physicist. Born in Basel Switzerland‚ later moved to neighboring town‚ Riehen‚ Euler attended a rather poor school that taught no mathematics. His father having studied theology at the University of Basil managed to teach him some‚ which ignited an interest in Euler for the subject and at just 14‚ he began attending the University
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