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"This book focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. This book examines applications for solving the traveling salesman problem and its variations, maximum weight independent set problem, different classes of allocation and cluster analysis as well as some classes of scheduling problems. Data correcting algorithms in combinatorial optimization introduces the data correcting approach to algorithms which provide an answer to the following questions, how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.​"

"ABSTRAKDalam analisis multivariate klasik dalam suatu uji hipotesa sering digunakananalisis nilai eigen dalam penetuan statistik ujinya. Dibawah kondisi H0, nilaistatistik uji yang diperoleh akan digunakan untuk bentuk distribusi yang berkaitandengan statistik uji. Daerah kritis penolakan suatu uji uji hipotesa ditentukanberdasarkan bentuk distribusi yang diperoleh. Nilai eigen yang diperoleh untukanalisi multivariat ini untuk pembentukan statistik ujinya bisa menggunakanfungsi yang melibatkan keseluruhan nilai eigen atau dengan menggunakan nilaiyang ekstrem. Untuk nilai eigen yang maksimum statistik uji yang digunakanberdasar Roy test maksimum. Cara lain yang digunakan adalah denganpendekatan distribusi Tracy-Widom. Disamping daerah kritis yang diperoleh jugadibutuhkan p-value berdasar nilai statistik uji yang sebenarnya.

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ABSTRACTClasical multivariate analysis in test hipothesa H0 most used eigen analysis indetermined their test statistics . Under H0 test statistics which founded wiil beused to make distribution concerning with test statistics. Critical area H0determined their distributions. Eigenvalue which founded will be used to buildtest statistics may included entilrely or eigen value maximum. Roy maximum testhad used maximum eigen value for inference by Tracy-Widom distribution.Besides founded critical area, for also wanted p-value for their test statisticswhich had found"

"This update of the 1987 title of the same name is an examination of what is currently known about the probabilistic method, written by one of its principal developers. Based on the notes from Spencer's 1986 series of ten lectures, this new edition contains an additional lecture: The Janson Inequalities. These inequalities allow accurate approximation of extremely small probabilities. A new algorithmic approach to the Lovasz Local Lemma, attributed to Jozsef Beck, has been added to Lecture 8, as well. Throughout the monograph, Spencer retains the informal style of his original lecture notes and emphasizes the methodology, shunning the more technical "best possible" results in favor of clearer exposition. The book is not encyclopedic--it contains only those examples that clearly display the methodology. The probabilistic method is a powerful tool in graph theory, combinatorics, and theoretical computer science. It allows one to prove the existence of objects with certain properties (e.g., colorings) by showing that an appropriately defined random object has positive probability of having those properties."

"A survey of some of the work that has been done since the appearance of the second edition of Combinatorial Algorithms. Topics include progress in: Gray Codes, listing of subsets of given size of a given universe, listing rooted and free trees, selecting free trees and unlabeled graphs uniformly at random, and ranking and unranking problems on unlabeled trees."

"This volume constitutes the refereed proceedings of the 15th International Workshop on Combinatorial Image Analysis, IWCIA 2012, held in Austin, TX, USA in November 2012. The 23 revised full papers presented were carefully reviewed and selected from numerous submissions. The topics covered include digital geometry, combinatorics in digital spaces, digital curves and surfaces; digital topologyl grammars, transformation, applications; grammars and models in image analysis; picture transformations, morphologic operations, image segmentation; and discrete tomography, applications"