Type II fuzzy set-based data analytics to explore amino acid associations in protein sequences of Swine Influenza Virus

The veracity present in molecular data available in biological databases possesses new challenges for data analytics. The analysis of molecular data of various diseases can provide vital information for developing better understanding of the molecular mechanism of a disease. In this paper, an attempt has been made to propose a model that addresses the issue of veracity in data analytics for amino acid association patterns in protein sequences of Swine Influenza Virus. The veracity is caused by intra-sequential and inter-sequential biases present in the sequences due to varying degrees of relationships among amino acids. A complete dataset of 63,682 protein sequences is downloaded from NCBI and is refined. The refined dataset consists of 26,594 sequences which are employed in the present study. The type I fuzzy set is employed to explore amino acid association patterns in the dataset. The type I fuzzy support is refined to partially remove the inter-sequential biases causing veracity in data. The remaining inter-sequential biases present in refined fuzzy support are evaluated and eliminated using type II fuzzy set. Hence, it is concluded that a combination of type II fuzzy & refined fuzzy approach is the optimal approach for extracting a better picture of amino acid association patterns in the molecular dataset.     

A Novel Approach to Analyzing the Occupancy of the Geo/Geo/∞ Queueing System

Discrete time queueing systems have been successfully used to model packet queues in computer and digital communications systems. In this article we introduce a novel approach to analyzing the Geo^X/Geo^Y/∞ queueing system, which is suitable for modelling high speed computer and communications systems. The approach is based on characterizing the system by a functional equation which is then solved recursively to give identical results to those obtained using other approaches.     

构建高扩展性的县级广电宽带数据网络

提出在县市级广电宽带数据网络的建设过程中,要着眼业务发展,突出高扩展性,构建基于标准、扩展灵活的主干网,实现网络建设的可持续性发展,并结合实际,从核心设备、端口、中继带宽、网络业务4个方面对扩展能力进行了阐述.     

Using an integrated process of data and modeling in HRA

The paper describes an approach taken to estimate the probabilities of failure associated with various railroad tasks to prevent accidents (principally collisions and derailments). These probabilities were estimated using an expert elicitation process that used partially relevant data available from a variety of databases and that were filtered and scaled to make them more directly relevant to the analyses being performed. Extensive qualitative studies were performed prior to the elicitation process to identify relevant contexts under which the tasks can be performed.     

Acquisition and pattern recognition of spectrum information of welding metal transfer

With the creation of a pattern recognition system for metal transfer mode, this article has collected five kinds of spectrum signals in gas metal arc welding (MIG, MAG and CO₂) and take them as training samples. These samples have been pretreated by computer, several key characteristic parameters of the spectrum signal have been creatively extracted, and a corresponding recognition function and a minimum-distance-classifier have been constructed. The results show that the pattern recognition of several kinds of metal transfer modes for the metal gas arc welding can be done successfully, and relative important parameters in welding process, such as the frequency of droplet transfer and the approximate diameter of each droplet, can also be obtained.     

三维地震勘探低速带静校正系统的研制

本文在研究目前三维地震勘探中常用的低速带静校正算法的基础上，根据几年来低速带静校正处理情况，研制出一种计算三维地震勘探低速带的静校正系统，简述了这种处理系统的原理，并对吉林油田某三维地震工区的低速带资料进行了处理。结果表明，该系统计算速度快、精度高、实用性强，对改善地震剖面质量和提高信噪比是有效的。     

一种非线性Radon变换及非零偏移距VSP波场分离

本文给出了一种非线性Ｒａｄｏｎ变换正反投影公式。这种变换比常规Ｒａｄｏｎ变换具有更广泛的用途。本文探讨了这种变换在地震数据处理中的某些应用，并用这种非线性Ｒａｄｏｎ变换进行了非零偏移距的ＶＳＰ波场分离处理，效果较好。     

用人工神经网络作地质数据分析

本文提出了利用人工神经网络进行地质数据多变量分析的方法，研究表明，此方法具有精度高、运算速度快、算法简单易于编程等显著特点，是地质数据分析中一有效方法。