A Software Design Model Based on Big Data

2014 ◽  
Vol 644-650 ◽  
pp. 2821-2825
Author(s):  
Zhong Lin He ◽  
Xiao Hong Xiao ◽  
Yu Hua He
Keyword(s):  
Big Data ◽  
Software Engineering ◽  
Data Processing ◽  
Programming Language ◽  
Software Design ◽  
Design Model ◽  
Computational Accuracy ◽  
Model Based ◽  
Processing Ability

Big data is mainly for analytic applications, which puts high requirements on data processing ability instead of computational accuracy. In this environment, software engineering-based methods should be carried out with the goal of data processing and computation. To adapt to the development of various analytic applications in big data era, this paper provides a software design model based on big data, and at the same time, analyzes compiler mechanism of big data programming language.

A New Approach of Expanding Data Processing Ability for Configuration Monitoring Software MCGS Based on OLE

2011 ◽  
Vol 65 ◽  
pp. 295-298 ◽  
Author(s):  
Fan Yang ◽  
Cai Li Zhang
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Monitoring System ◽  
Programming Language ◽  
Configuration Software ◽  
Time Data ◽  
Software Configuration ◽  
Processing Ability ◽  
Significant Performance ◽  
Monitoring Software

Considering the insufficient ability of data processing existed in configuration software, a scheme integrated both advantages of advanced programming language and configuration software is provided. In this scheme real-time data acquisition and complex processing are achieved by advanced programming language, the human-computer interface and other functions of the monitoring system are achieved by configuration software. Configuration software achieves the purpose of expanding data processing ability by data communications between advanced programming language and configuration software based on OLE technology. The practical application result indicates that the data processing ability of configuration software can be effectively expanded based on OLE technology, which has well stability and real-time, and can play significant performance in complex parameters and data processing related monitoring system.

Computer Control Software Design Model Based on Improved PID Algorithm

2014 ◽  
Vol 716-717 ◽  
pp. 1671-1674
Author(s):  
Xin Jie Qian ◽  
Gui Xiang Hu ◽  
Qiu Lin Fu ◽  
Bo Yang
Keyword(s):  
Software Design ◽  
Computer Control ◽  
Control Process ◽  
Search Space ◽  
Design Model ◽  
Particle Swarm Algorithm ◽  
Control Software ◽  
Pid Algorithm ◽  
Model Based ◽  
Control Precision

The optimal design for computer control software is studied. Since computer control software is susceptible to interference during the control process, a computer control software design model based on improved PID algorithm is proposed. The PID algorithm is combined with particle swarm algorithm to calculate PID control parameters, which is viewed as evolutionary particles of the particle population, and given a certain flight speed in the search space, the speed of the particles will be adjusted iteratively and dynamically in accordance with the experience of population’s evolution calculation, in order to achieve computer control software design. The simulation results show that the proposed algorithm applied for computer control software design, can improve the control precision and meet the actual needs of computer control.

Transforming an HCI Model to a Software Design Model

1997 ◽  
Vol 07 (01) ◽  
pp. 145-167
Author(s):  
Andrew M. Olson
Keyword(s):  
Software Engineering ◽  
Human Factors ◽  
Software Design ◽  
Design Model ◽  
Software Project ◽  
Software Engineering Process ◽  
Final Code ◽  
Action Grammar ◽  
Project Life

The software engineering and human factors communities are seeking ways to integrate their methodologies. This paper outlines an amplified, software engineering methodology that extends beyond requirements gathering to encompass human factors analyses. The methodology employs an object model that is uniform throughout the software project. It involves a procedure that seamlessly transforms a task action grammar model, from HCI theory, directly into a specification model based on user/machine dialog and, thence, into a software design model. The model's object-oriented structure makes it feasible to trace the effects of the user's needs throughout the amplified project life cycle to the final code. A case study documents evidence concerning how effectively the procedure supports the software engineering process. An examination of the extent of metamorphosis the model undergoes in the case study indicates that the transition through the amplified life history is well controlled; in particular, the transition from the software specification to the design model is more controlled than that under traditional methodologies.

scholarly journals Gene Sequences Parallel Alignment Model Based on Multiple Inputs and Outputs

2019 ◽  
Vol 14 (2) ◽  
pp. 141-153
Author(s):  
Xiaolong Feng ◽  
Jing Gao
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Sequence Alignment ◽  
Gene Sequence ◽  
Computational Time ◽  
Gene Sequences ◽  
Model Based ◽  
Hadoop Platform ◽  
Alignment Model ◽  
Inputs And Outputs

Bioinformatics computing is a kind of big data processing problem, which usually has the characteristics of large data scale, large computational load and long computational time. Therefore, the use of big data technology in bioinformatics computing has gradually become a research hotspot, and using Hadoop for gene sequence alignment is one of it. It is a common way to use various tools to complete a job in the field of Biocomputing. In most studies of parallel alignment of gene sequences using Hadoop, third-party tools are also needed. However, there are few methods using Hadoop independently to complete gene sequences alignment. Adding data processing with other tools to Hadoop workflow not only affects the improvement of computing performance, but also complicates the application. In this paper, a parallel alignment model of gene sequences based on multiple inputs and outputs is proposed, which can independently complete parallel alignment of gene sequences in Hadoop platform without using other tools. This model not only simplifies the process flow of gene sequence alignment, but also improves the performance compared with other methods. This paper describes in detail the method of manipulating gene sequences with multiple inputs and outputs modes on Hadoop platform and the design of a computing model based on this method, and proves the superiority of this model through experiments.

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