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Locating and tracking assets using RFIDKim, 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.
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Average case analysis of algorithms for the maximum subarray problemBashar, 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
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