Parallel Dictionary Research Articles

Variable partition based parallel dictionary learning for linearity and nonlinearity coexisting dynamic process monitoring

In practical industrial processes with complex mechanisms, there are both linear and nonlinear relationships between process variables. However, focusing solely on one of these relationships can lead to the neglect of important information related to faults. This neglect can degrade the monitoring performance and increase the potential risk of catastrophic accidents caused by unreliable fault alarms. In order to solve this puzzle, this paper proposes a variable partition based parallel dictionary learning (PDL) method. Firstly, a linearity maximization analysis (LMA) method is presented to recognize linear variable subsets efficiently. The collinearity of variables is evaluated using the variance inflation factor, then linear and nonlinear variable subsets can be divided by maximizing the linear correlation between one variable and the rest. After that, a PDL based monitoring model can be constructed in all subsets to extract linear and nonlinear features concurrently. Finally, based on Bayesian inference, the monitoring results of all subsets are fused to construct a global monitoring statistic. The effectiveness of the proposed approach is illustrated by a numerical simulation case, the continuous stirred tank heater, the Tennessee Eastman process, and a real industrial roasting process. Experiment results show that linear and nonlinear variable subsets can be divided reasonably according to the proposed LMA method. Meanwhile, compared with several state-of-the-art methods, the proposed method can achieve better monitoring results by modeling linear and nonlinear data parts separately, which further demonstrates the feasibility of the proposed method.

FEATURES OF THE ORTHOEPIC DICTIONARY IN THE KAZAKH LANGUAGE BASED ON THE LATIN ALPHABET

The problem of transition of the Kazakh writing system to the Latin script is very important in modern linguistics. In this regard, there is a need to issue dictionaries in Latin script. Currently, the work “Development of a parallel orthoepic dictionary in Cyrillic and Latin graphics» is being carried out. The article deals with the features of the orthoepic dictionary in the Kazakh language based on the Latin alphabet

Efficient VLSI architecture for the parallel dictionary LZW data compression algorithm

The Lempel–Ziv–Welch (LZW) algorithm is an important dictionary-based data compression approach that is used in many communication and storage systems. The parallel dictionary LZW (PDLZW) algorithm speeds up the LZW encoding by using multiple dictionaries. This simplifies the parallel search in the dictionaries. However, the compression gain of the PDLZW depends on the partitioning of the address space, i.e. on the sizes of the parallel dictionaries. This work proposes an address space partitioning technique that optimises the compression rate of the PDLZW. Numerical results for address spaces with 512, 1024, and 2048 entries demonstrate that the proposed address partitioning improves the performance of the PDLZW compared with the original proposal. These address space sizes are suitable for flash storage systems. Moreover, the PDLZW has relative high memory requirements which dominate the costs of a hardware implementation. This work proposes a recursive dictionary structure and a word partitioning technique that significantly reduce the memory size of the parallel dictionaries.

On the Conditions and Means of Knowledge Transfer in Interdisciplinary Research

The first part of this article discusses the methodology for studying the conditions and means of knowledge transfer in interdisciplinary research. It is based on a combination of methodology from historical, socio-cultural and scientific research applied to the study of the conditions of interdisciplinary communication, with a methodological approach characteristic of the philosophy and epistemology of science, focusing on studying means of transfer. It is suggested that conceptual metaphors, or semantic transfers between conceptual domains, which are studied in cognitive linguistics, be considered as such tools. The article analyzes their role in interdisciplinary transfer using the author’s parallel dictionary methodology. The second part of the article shows the application of this approach to studying specific interdisciplinary knowledge transfer based on the examples of a number of relevant and developing interdisciplinary areas. Three examples were specifically examined: the transfer of knowledge between evolutionary biology and evolutionary computation; between evolutionary biology and evolutionary political science and biological science and semiotics.

Real-time dynamic MRI using parallel dictionary learning and dynamic total variation

One of the technical challenges in dynamic magnetic resonance imaging (dMRI) is to obtain MR images with high spatiotemporal resolution in a short scan time. Current state-of-the-art recovery algorithms exploit both spatial and temporal sparsity in dMRI to improve the reconstruction quality. In this paper, we proposed a novel algorithm based on 4-frame parallel dictionary learning and dynamic total variation (PDLDTV) for real-time dMRI reconstruction. The dMRI sequence was decomposed into 4-frame subsets and each subset included the first frame (obtained with more k-space sampling for reference to later frames) and any adjacent three frames. A 3D patch-based dictionary learning algorithm and a dynamic total variation algorithm were used to exploit the spatiotemporal sparsity in each subset. High algorithm speed was required for our real-time reconstruction, and a primal-dual algorithm was used to solve the challenging problem. Experiments over two cardiac dMRI sequences indicated that the proposed 4-frame PDLDTV showed better reconstruction performance than the state-of-the-art online and offline methods such as DTV, k-t SLR, and DLTG.

A Novel Compression Technique for Compound Images Using Parallel Lempel-Ziv-Welch Algorithm

Compound image is a combination of natural images, text, and graphics.This paper presents a compression technique for improving coding efficiency. The algorithm first decomposes the compound images by using 3 level biorthogonal wavelet transform and then the transformed image was further compressed by Parallel dictionary based LZW algorithm called PDLZW.In PDLZW algorithm instead of using a unique fixed word width dictionary a hierarchical variable word width dictionary set containing several dictionaries of small address space and increases the word widths used for compression and decompression algorithms. The experimental results show that the PSNR value is increased and the Mean Square error value was improved.

A Lossless Data Compression and Decompression Algorithm and Its Hardware Architecture

In this paper, we propose a new two-stage hardware architecture that combines the features of both parallel dictionary LZW (PDLZW) and an approximated adaptive Huffman (AH) algorithms. In this architecture, an ordered list instead of the tree-based structure is used in the AH algorithm for speeding up the compression data rate. The resulting architecture shows that it not only outperforms the AH algorithm at the cost of only one-fourth the hardware resource but it is also competitive to the performance of LZW algorithm (compress). In addition, both compression and decompression rates of the proposed architecture are greater than those of the AH algorithm even in the case realized by software

A Hardware Architecture for the LZW Compression and Decompression Algorithms Based on Parallel Dictionaries

In this paper, a parallel dictionary based LZW algorithm called PDLZW algorithm and its hardware architecture for compression and decompression processors are proposed. In this architecture, instead of using a unique fixed-word-width dictionary a hierarchical variable-word-width dictionary set containing several dictionaries of small address space and increasing word widths is used for both compression and decompression algorithms. The results show that the new architecture not only can be easily implemented in VLSI technology because of its high regularity but also has faster compression and decompression rate since it no longer needs to search the dictionary recursively as the conventional implementations do.

Parallel Dictionaries Using AVL Trees

AVL (Adel'son-Vel'skii and Landis) trees are efficient data structures for implementing dictionaries. We present a parallel dictionary, using AVL trees, on the EREW PRAM by proposing optimal algorithms to performkoperations withp(1 ≤p≤k) processors. An explicit processor scheduling is devised to avoid simultaneous reads in our parallel algorithm to performksearches, which avoids the need for any additional memory in the parallelization. To perform multiple insertions and deletions, we identify rotations (in addition to AVL tree rotations) required to restore balance and present parallel algorithms to performpinsertions/deletions inO(logn+ logp) time withpprocessors.

AN OPTIMAL SYSTOLIC DICTIONARY

We present a simple systolic algorithm for implementing dictionary machine based on the VLSI technology. Our design makes use of a dynamic. global tree rebalancing scheme to attain high system throughput. Our scheme is simple to implement and requires low sophistication in the design of processing nodes. Results from analysis and simulation show that our algorithm has optimal response time and achieves an average latency close to 1. This represents a significant improvement over many of the previous designs. Unlike most parallel dictionary machines reported in the literature, our approach requires no compression operations.

An Optimal Parallel Dictionary

A parallel dictionary is implemented on a randomized CRCW PRAM with p processors in such a way that n instructions (Insert, Delete, Lookup), n / p read in by each processor, can be executed in optimal expected time O ( n / p ). Further, the response time of each lookup is worst case constant. The construction is inspired by the sequential dynamic hashing strategy due to Dietzfelbinger et al. (in "Proceedings, 29th IEEE Symposium on Foundations of Computer Science," pp. 524-531), which in turn is based on the perfect hashing scheme due to Fredman et al. (1984, J. Assoc. Comput. Mach. 31, 538-544).