Computational complexity theory

move ahead in the future, I strongly desire for a program that would help me build a comprehensive foundation in the field of Computer Science. Within this field, I have developed a deep interest in the area of Theory and Computational Science. More specifically I find algorithms and theory of computation the most appealing areas due to their application in solving many real world problems. My undergraduate course in the field of Electronics Engineering has given me a comprehensive exposure to all

Company Complexity According to Ge and McVay research study findings, business complexity is positively correlated with firm disclosure of material weaknesses. They hypothesized that the “firms with more complicated transactions likely to have greater chance for a disconnect in the financial reporting process, and thus a material weakness (Ge et al., 148).” To measure business complexity, Ge and McVay used the number of operating segments reported in the annual 10-K and the existence of foreign currency

CHAPTER 1 INTRODUCTION 1.1 0-1 Knapsack problem The 0-1 Knapsack Problem is an example of a combinatorial optimization problem, which seeks for a best solution from among many other solutions. It is concerned with a knapsack that has positive integer volume (or capacity) V. There are n distinct items that may potentially be placed in the knapsack. An item i have a positive integer, volume Vi and positive integer benefit Bi. In addition, there are Qi copies of the item i available, where quantity

Homework #7 Problem 1. (a). Here we have k number of routes from one source to one destination, which is a graph with the source and shrink. Suppose we have n files to transfer from k routes by minimizing the total time. We can apply simple greedy routing algorithm. This algorithm assigns the file to the route which has low load compared to other. Select route from graph which has capacity still greater or equal to the li. (b). The problem belongs to P Class (Polynomial Time). (c). Let number

amount of cities impractical.  The Dynamic Programming Method The dynamic programming method improves on the brute force method by storing the minimum cost of sub paths to avoid computing those values again and again significantly improving the time complexity. When solving a problem with dynamic programming, we define the solution with the help of a recursive relation with explains how the problem is solved step by step. For travelling salesperson problem the recursive relation to find the shortest path

broadcast monitoring and forensic applications. Various requirements of a digital watermarking system include Imperceptibility, Robustness, Security, Payload and Computational complexity. The main requirement of real time DRM systems is lesser computational complexity and high robustness. This chapter proposes and analyses a robust and computational efficient Image watermarking technique in spatial domain based on Inter Block Pixel Difference (IBPD). The cover image is divided into 8×8 non overlapping blocks

A Novel Study of Bee Colony Optimization Algorithms for their Applications into Various Domains INTRODUCTION The Bee Colony Optimization (BCO) is a technique based on the mutual understanding of the natural bees in food foraging process. It is a population based search algorithm for optimizing numerical problems. Bees are classic example of teamwork experience, coordination and synchronization. The way they work is remarkable. They carry out a kind of neighborhood search combined with global search

being refined today to provide new functionality for dealing with the newer code-development related issues we might encounter (de Ville & Neville, 2013). Since decisions trees are essentially binary trees, they also operate in O(log(n)) time complexities for best and worst case scenarios, and O(n) for space. Decision trees are generated by algorithms which determine possible ways to branch-off data depending on the end result of a set question. From this, the aim of the tree would be to predict

A framework for evaluation of operational complexity cost: A case of make-to-stock supply chain Dheeraj Chandraa , Dharmendra Singh Chauhanb a Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India b Department of Management Studies, Indian Institute of Technology Roorkee, Roorkee 247667, India Abstract Today’s supply chains are more complex than ever due to globalization and its effects, especially on manufacturing activities. Therefore

Project Proposal (option 3) Name: Yao Yang UNI: yy2641 The common theme my project will be focuses on is K-means clustering. The k-means clustering problem can be described as following: Given a set of n data points in d-dimensional space R^d and an integer k. Find a set of k points/centers in R^d, such that the mean squared distance from each data point to its nearest centre (one of the k centers) is minimized. Paper Summaries: A local search approximation algorithm for k-means clustering