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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Showing 1 to 2 of 2 (0.058 seconds)

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1

Locating and tracking assets using RFID

Kim, Gak Gyu 15 May 2009 (has links)
Being able to quickly locate equipment is critical inside buildings, including hospitals, manufacturing floors and warehouses. In order to utilize limited budget and resources efficiently, accurate locating or tracking is required in many fields. In this research, we will focus on how to find the location of an item by using RFID in real time indoors to track equipment. When an item needs to be located, the purpose of using RFID is to minimize the searching time, effort, and investment cost. Thus, this research presents a math¬ematical model of using RFID (both handheld readers and stationary readers) for efficient asset location. We derive the expected cost of locating RFID¬tagged objects in a multi¬area environment where hand¬held RF readers are used. We then discuss where to deploy stationary RF readers in order to maximize the efficiency of the search process.
RFID
Hand-held reader
Stationary reader
Heuristic policy
Traveling route
Install location
Expected time
2

Average case analysis of algorithms for the maximum subarray problem

Bashar, Mohammad Ehsanul January 2007 (has links)
Maximum Subarray Problem (MSP) is to find the consecutive array portion that maximizes the sum of array elements in it. The goal is to locate the most useful and informative array segment that associates two parameters involved in data in a 2D array. It's an efficient data mining method which gives us an accurate pattern or trend of data with respect to some associated parameters. Distance Matrix Multiplication (DMM) is at the core of MSP. Also DMM and MSP have the worst-case complexity of the same order. So if we improve the algorithm for DMM that would also trigger the improvement of MSP. The complexity of Conventional DMM is O(n³). In the average case, All Pairs Shortest Path (APSP) Problem can be modified as a fast engine for DMM and can be solved in O(n² log n) expected time. Using this result, MSP can be solved in O(n² log² n) expected time. MSP can be extended to K-MSP. To incorporate DMM into K-MSP, DMM needs to be extended to K-DMM as well. In this research we show how DMM can be extended to K-DMM using K-Tuple Approach to solve K-MSP in O(Kn² log² n log K) time complexity when K ≤ n/log n. We also present Tournament Approach which solves K-MSP in O(n² log² n + Kn²) time complexity and outperforms the K-Tuple
Maximum Subarray Problem
Distance Matrix Multiplication
All Pairs Shortest Path Problem
Shortest Path
Expected Time
Average Time
Average Case Analysis
Binary Heap
Prefix Sum
Directed Acyclic Graph
X + Y Problem
Binary Tournament Tree
Solution Set
MSP
K-MSP
DMM
K-DMM
APSP
K-Tuple

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