scholarly journals Design and Implementation of VLSI for Finite State Entropy Encoding

2021 ◽  
Vol 33 (4) ◽  
pp. 640-648
Author(s):  
Hai Huang ◽  
Lin Xing ◽  
Ning Na ◽  
Guoliang Zhang ◽  
Shilei Zhao ◽  
...  
Author(s):  
Winfield Chen ◽  
Lloyd T. Elliott

We improve the efficiency of population genetic file formats and GWAS computation by leveraging the distribution of samples in population-level genetic data. We identify conditional exchangeability of these data, recommending finite state entropy algorithms as an arithmetic code naturally suited for compression of population genetic data. We show between [Formula: see text] and [Formula: see text] speed and size improvements over modern dictionary compression methods that are often used for population genetic data such as Zstd and Zlib in computation and decompression tasks. We provide open source prototype software for multi-phenotype GWAS with finite state entropy compression demonstrating significant space saving and speed comparable to the state-of-the-art.


Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 325
Author(s):  
Andrea Vaclavova ◽  
Peter Strelec ◽  
Tibor Horak ◽  
Michal Kebisek ◽  
Pavol Tanuska ◽  
...  

Today, Industrial Internet of Things (IIoT) devices are very often used to collect manufacturing process data. The integration of industrial data is increasingly being promoted by the Open Platform Communications United Architecture (OPC UA). However, available IIoT devices are limited by the features they provide; therefore, we decided to design an IIoT device taking advantage of the benefits arising from OPC UA. The design procedure was based on the creation of sequences of steps resulting in a workflow that was transformed into a finite state machine (FSM) model. The FSM model was transformed into an OPC UA object, which was implemented in the proposed IIoT. The OPC UA object makes it possible to monitor events and provide important information based on a client’s criteria. The result was the design and implementation of an IIoT device that provides improved monitoring and data acquisition, enabling improved control of the manufacturing process.


2012 ◽  
Vol 2012 ◽  
pp. 1-8
Author(s):  
Ping-Heng Kuo ◽  
Pang-An Ting

Geometric mean decomposition (GMD) has been proposed as a method to realize multiple spatial links with identical gains that are intrinsic to a MIMO channel. In order to simplify system design and implementation based on knowledge regarding probability behavior of MIMO-GMD schemes, the main objective of this paper is to statistically characterize the link gains and channel capacities that can be provided via GMD. In particular, closed-form univariate and bivariate probability density functions (PDFs) for these metrics under Rayleigh fading are derived using Gamma approximations. By applying these analytical results, the fluctuations of MIMO-GMD schemes are examined by modeling both link gains and capacities using finite-state Markov chains (FSMCs).


2021 ◽  
Author(s):  
Winfield Chen ◽  
Lloyd T. Elliott

AbstractWe improve the efficiency of population genetic file formats and GWAS computation by leveraging the distribution of sample ordering in population-level genetic data. We identify conditional exchangeability of these data, recommending finite state entropy algorithms as an arithmetic code naturally suited to population genetic data. We show between 10% and 40% speed and size improvements over dictionary compression methods for population genetic data such as Zstd and Zlib in computation and and decompression tasks. We provide a prototype for genome-wide association study with finite state entropy compression demonstrating significant space saving and speed comparable to the state-of-the-art.


2002 ◽  
Vol 2 (1) ◽  
pp. 96-113 ◽  
Author(s):  
Alan R. Flora-Holmquist ◽  
Edward Morton ◽  
James D. O'Grady ◽  
Mark G. Staskauskas

Sign in / Sign up

Export Citation Format

Share Document