Constrained coding is used widely in digital communication and storage systems. In this paper, we study a generalized sliding window constraint called the skip-sliding window. A skip-sliding window (SSW) code is defined in terms of the length L of a sliding window, skip length J , and cost constraint E in each sliding window. Each valid codeword of length L+kJ is determined by k+1 windows of le...

Traffic-smoothing for delivery of online VBR media is one of the most important problems in designing streaming multimedia applications. Given the available client buffer b and playback delay D, [21] introduces a window-based approach called SLWIN(k) to smooth online generated traffic for the pre-specified window size W (W<D) and sliding distance k (kSW). The required time complexity is O(n*W/k...

Sorted Sliding Window Compression (SSWC) uses a new model (Sorted Sliding Window Model | SSWM) to encode strings e cient, which appear again while encoding a symbol sequence. The SSWM holds statistics of all strings up to certain length k in a sliding window of size n (the sliding window is de ned like in lz77). The compression program can use the SSWM to determine if the string of the next sym...

Traffic smoothing for delivery of online VBR media streams is one of the most important problems in designing multimedia systems. Given an available client buffer, a window size and a window-sliding size, previous window-based online smoothing methods try to reduce peak bandwidth allocated in each window. However, as bandwidths allocated in different windows are minimized independently, these m...

In many online applications, we need to maintain quantile statistics for a sliding window on a data stream. The sliding windows in natural form are defined as the most recent N data items. In this paper, we study the problem of estimating quantiles over other types of sliding windows. We present a uniform framework to process quantile queries for time constrained and filter based sliding window...

Abstract.1 The scheme of the sliding window is known in Information Theory, Computer Science, the problem of predicting and in stastistics. Let a source with unknown statistics generate some word . . . x−1x0x1x2 . . . in some alphabet A. For every moment t, t = . . . −1, 0, 1, . . ., one stores the word (”window”) xt−wxt−w+1 . . . xt−1 where w,w ≥ 1, is called ”window length”. In the theory of ...

background: this work investigated the dosimetry limitations of the random and systematic uncertainties of sliding window (sw) intensity modulated radiation therapy (imrt). materials and methods: a varian 21ex linear accelerator, pinnacle3 treatment planning system and radiographic film dosimetry was used. the limitations of the sw were studied using beam modulation ranging from 2 to 100 mu/bea...

Sliding-window computations are widely used for data analysis in networked systems. Such computations can consume significant computational resources, particularly in live systems, where new data arrives continuously. This is because they typically require a complete re-computation over the full window of data every time the window slides. Therefore, sliding-window computations face important s...

In this paper, we propose a new framework for data stream mining, called the weighted sliding window model. The proposed model allows the user to specify the number of windows for mining, the size of a window, and the weight for each window. Thus, users can specify a higher weight to a more significant data section, which will make the mining result closer to user’s requirements. Based on the w...

We prove the correctness of a sliding window protocol with an arbitrary finite window size n and sequence numbers modulo 2n. The correctness consists of showing that the sliding window protocol is branching bisimilar to a queue of capacity 2n. The proof is given entirely on the basis of an axiomatic theory, and has been checked in the theorem prover PVS. Keywords— μCRL, branching bisimulation, ...