Star Map Stitching Algorithm Based on Visual Principle

2018 ◽  
Vol 32 (08) ◽  
pp. 1850028 ◽  
Author(s):  
Shi Qiu ◽  
Dongmei Zhou ◽  
Qiang Guo ◽  
Hanlin Qin ◽  
Xiang Yan ◽  
...  
Keyword(s):  
Visual Perception ◽  
Data Compression ◽  
Compression Ratio ◽  
Experimental Results ◽  
Imaging Features ◽  
Paper Study ◽  
Storage Model ◽  
Star Group ◽  
Manual Processing ◽  
Matching Models

For the problem that the limited star map field angle cannot obtain the complete star map accurately, the paper study astral intrinsic and imaging features, a star map stitching algorithm based on the principle of visual perception is proposed firstly. The matching models of time and space dimensions is constructed by simulating the visual perception, then the stars and the planets points are saved by searching the matching star group dynamically, the star map is stitched and reconstructed efficiently by creating the computer sparse storage model. The experimental results show that the algorithm can achieve data compression quickly, compression ratio is 99.54%, which can reduce complexity of manual processing and can achieve star map stitching accurately.

scholarly journals A modified approach to the new lossless data Compression method

2013 ◽  
pp. 129-133
Author(s):  
Bitla Srinivas ◽  
V.K. Govindan
Keyword(s):  
Data Compression ◽  
Compression Ratio ◽  
Experimental Results ◽  
Compression Method ◽  
Lossless Data Compression ◽  
Location Map ◽  
Mathematical Operations ◽  
Good Compression

This paper proposed the modified approach to the new lossless data compression method. It is developed based on hiding data reversibly with a location map. It performs same as the earlier algorithm but it stands on lossless strategy where as the former approach could not do it. It can compress any kind of symbols as it operates on binary symbols. It is faster than many algorithms as it does not have any complex mathematical operations. Experimental results proved that when the symbol probability increases the algorithm shows good compression ratio.

Principle and structure of a multi-chamber piezoelectric pump with large flow rate integrated into printed circuit board

2022 ◽  
pp. 1045389X2110721
Author(s):  
Yun-Hao Peng ◽  
Dai-Hua Wang ◽  
Lian-Kai Tang
Keyword(s):  
Flow Rate ◽  
Compression Ratio ◽  
Layer Structure ◽  
Experimental Results ◽  
Processing Technology ◽  
Rate Model ◽  
Piezoelectric Pump ◽  
Central Deflection ◽  
Maximum Value ◽  
Large Flow

Parametric simulation of multi-chamber piezoelectric pump proposed by authors shows that its flow rate is positively correlated with chamber compression ratio when height of chamber wall is not less than central deflection of circular piezoelectric unimorph actuator (CPUA). Therefore, in this paper, principle and structure of multi-chamber piezoelectric pump with novel CPUAs with three-layer structure are proposed and realized, so as to improve its chamber compression ratio, and then improve its flow rate. Its processing technology compatible with PCB processing technology is studied and its flow rate model is established. Central deflection of CPUA with three-layer structure and the flow rate characteristics are tested. Experimental results show that when the central deflection of CPUA with three-layer structure reaches the maximum value of 106.8 μm, the chamber compression ratio and flow rate of multi-chamber piezoelectric pump reach the maximum value of 50% and 3.11 mL/min, respectively. The maximum flow rate is increased by 622% compared to unimproved pump. By comparing experimental results with numerical and finite element simulation results, the realized multi-chamber piezoelectric pump has large flow rate and the established flow rate model can predict its flow rate.

scholarly journals Parallel Algorithm for Wireless Data Compression and Encryption

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Jiancheng ◽  
Lu Yiqin ◽  
Zhong Yu
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Compression ◽  
Parallel Algorithm ◽  
Wireless Network ◽  
Compression Ratio ◽  
Wireless Data ◽  
Limited Bandwidth ◽  
Compression Speed ◽  
Parallel Pipeline

As the wireless network has limited bandwidth and insecure shared media, the data compression and encryption are very useful for the broadcasting transportation of big data in IoT (Internet of Things). However, the traditional techniques of compression and encryption are neither competent nor efficient. In order to solve this problem, this paper presents a combined parallel algorithm named “CZ algorithm” which can compress and encrypt the big data efficiently. CZ algorithm uses a parallel pipeline, mixes the coding of compression and encryption, and supports the data window up to 1 TB (or larger). Moreover, CZ algorithm can encrypt the big data as a chaotic cryptosystem which will not decrease the compression speed. Meanwhile, a shareware named “ComZip” is developed based on CZ algorithm. The experiment results show that ComZip in 64 b system can get better compression ratio than WinRAR and 7-zip, and it can be faster than 7-zip in the big data compression. In addition, ComZip encrypts the big data without extra consumption of computing resources.

Threshold Effect in Visual Perception of Geometrical Figures

1998 ◽  
Vol 87 (1) ◽  
pp. 340-342 ◽  
Author(s):  
Vito Di Maio
Keyword(s):  
Visual Perception ◽  
Threshold Effect ◽  
Input Image ◽  
Visual Illusions ◽  
Experimental Results ◽  
Perceptual Error ◽  
Image Function ◽  
Random Dot Patterns

Filtering of the input image has been shown to play a central role in several aspects of visual perception. In our experiments in visual perception of the area of geometrical figures the orientation in random dot patterns, and some visual illusions, we have shown that a threshold effect inferred from the filtering of the input image produces a perceptual error. This error has been explained by using the concept of Image Function. The present paper is a brief review of our experimental results and of the models we have proposed.

scholarly journals Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search

2020 ◽  
Vol 34 (01) ◽  
pp. 51-58 ◽  
Author(s):  
Xinyan Dai ◽  
Xiao Yan ◽  
Kelvin K. W. Ng ◽  
Jiu Liu ◽  
James Cheng
Keyword(s):  
Data Compression ◽  
Vector Quantization ◽  
Similarity Search ◽  
Euclidean Distance ◽  
Quantization Error ◽  
Experimental Results ◽  
Inner Product ◽  
Direction Error ◽  
Product Search ◽  
Norm Error

Vector quantization (VQ) techniques are widely used in similarity search for data compression, computation acceleration and etc. Originally designed for Euclidean distance, existing VQ techniques (e.g., PQ, AQ) explicitly or implicitly minimize the quantization error. In this paper, we present a new angle to analyze the quantization error, which decomposes the quantization error into norm error and direction error. We show that quantization errors in norm have much higher influence on inner products than quantization errors in direction, and small quantization error does not necessarily lead to good performance in maximum inner product search (MIPS). Based on this observation, we propose norm-explicit quantization (NEQ) — a general paradigm that improves existing VQ techniques for MIPS. NEQ quantizes the norms of items in a dataset explicitly to reduce errors in norm, which is crucial for MIPS. For the direction vectors, NEQ can simply reuse an existing VQ technique to quantize them without modification. We conducted extensive experiments on a variety of datasets and parameter configurations. The experimental results show that NEQ improves the performance of various VQ techniques for MIPS, including PQ, OPQ, RQ and AQ.

scholarly journals FPGA implementation of Lempel-Ziv data compression

2021 ◽  
Vol 10 (2) ◽  
pp. 99
Author(s):  
Gody Mostafa ◽  
Abdelhalim Zekry ◽  
Hatem Zakaria
Keyword(s):  
Data Compression ◽  
Compression Ratio ◽  
Digital Communication ◽  
Compression Rate ◽  
High Compression Ratio ◽  
Compression Algorithms ◽  
High Compression ◽  
Space Saving ◽  
Fpga Chip ◽  
Lossless Data Compression

When transmitting the data in digital communication, it is well desired that the transmitting data bits should be as minimal as possible, so many techniques are used to compress the data. In this paper, a Lempel-Ziv algorithm for data compression was implemented through VHDL coding. One of the most lossless data compression algorithms commonly used is Lempel-Ziv. The work in this paper is devoted to improve the compression rate, space-saving, and utilization of the Lempel-Ziv algorithm using a systolic array approach. The developed design is validated with VHDL simulations using Xilinx ISE 14.5 and synthesized on Virtex-6 FPGA chip. The results show that our design is efficient in providing high compression rates and space-saving percentage as well as improved utilization. The Throughput is increased by 50% and the design area is decreased by more than 23% with a high compression ratio compared to comparable previous designs.

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