In visual indoor positioning systems, the method of constructing a map by point-by-point sampling is widely used due to its characteristics clear static images and simple coordinate calculation. However, too small interval will cause image redundancy, while large lead absence any scene images, which result in worse efficiency inferior accuracy. As result, this paper proposed construction based ...

We show the architecture and design of a numeric function generator that realizes, at high speed, arithmetic functions, like log x, sin x, 1 x , etc.. This approach is general; different circuits are not needed for different functions. Further, composite functions, like log (sin ( 1 x )) can be realized as easily as individual functions. A tutorial description of the method is presented, follow...

in zero acceptance number sampling plans, the sample items of an incoming lot are inspected one by one. the proposed method in this research follows these rules: if the number of nonconforming items in the first sample is equal to zero, the lot is accepted but if the number of nonconforming items is equal to one, then second sample is taken and the policy of zero acceptance number would be appl...

We study two variants of seeded randomness extractors. The first one, as studied by Goldreich et al. [8], is seeded extractors that can be computed by AC circuits. The second one, as introduced by Bogdanov and Guo [3], is (strong) extractor families that consist of sparse transformations, i.e., functions that have a small number of overall input-output dependencies (called sparse extractor fami...

We consider the problem of estimating the average of a huge set of values. That is, given oracle access to an arbitrary function f : {0, 1} → [0, 1], we wish to estimate 2 Px∈{0,1}n f(x) upto an additive error of ǫ. We are allowed to employ a randomized algorithm that may err with probability at most δ. We survey known algorithms for this problem and focus on the ideas underlying their construc...

In discriminative machine learning one is interested in training a system to optimize a certain desired measure of performance, or loss. In binary classification one typically tries to minimizes the error rate. But in structured prediction each task often has its own measure of performance such as the BLEU score in machine translation or the intersection-over-union score in PASCAL segmentation....

Quantum simulation is a prominent application of quantum computers. While there extensive previous work on simulating finite-dimensional systems, less known about algorithms for real-space dynamics. We conduct systematic study such algorithms. In particular, we show that the dynamics $d$-dimensional Schr\"{o}dinger equation with $\eta$ particles can be simulated gate complexity $\tilde{O}\bigl(...