海上地震勘探外源干扰快速压制方法

外源信号与地震震源信号没有明显的地球物理特征差异,其频谱与有效信号频谱完全重叠,同时外源信号的反射同相轴符合地震时距曲线规律,因此用滤波等常规噪声压制方法无法压制外源干扰。本文提出一种外源干扰快速压制算法,利用外源干扰的时距曲线和正常时差可以得到外源干扰的信号源位置,再利用时距曲线模拟出任意位置处的干扰模型,以此校正炮集记录,拉平外源干扰。最后,应用LIFT去噪方法分离有效信号与外源干扰。LIFT去噪方法在信号模型建立和数据重构过程中提取估算剩余信号,能够获得更好的信噪比和信号保持。这种海上外源快速压制算法简便、高效,通过对实际三维地震资料进行处理,证实了该方法的有效性。     

形式化方法在CSTA系统测试中的应用研究

系统测试中的形式化方法是将客户需求用数学规约表达出来，推导出各项功能的预期输出结果，以完善客户需求，不仅可以较好地消除需求中可能包含的矛盾、二义性、含糊性、不完整陈述以及抽象层次的混杂等，提高发现问题的工作效率和准确度，提高软件测试质量的保障系数，而且可以将行业知识封装起来，为软件测试业务外包提供一个现实可行的依据。     

利用马尔科夫链的企业信息技术外包服务商模糊动态综合评价研究

在制造业企业发展信息化时,通常会选择外包这个模式,为减少企业外包决策的潜在风险因素,外包服务商的选择与评价问题是首要问题,且需要综合考虑其长期业绩和未来发展前景等因素.根据外包服务商运行过程具有显著的马尔科夫性,以马尔科夫链理论为基础,在对信息技术(IT)外包服务商进行模糊综合评价的过程中,利用马尔科夫链的预测性,提出一种动态评价其潜力的模型,最后以某企业为案例进行分析,论证该模型的可操作性及其应用价值.     

我国电力企业外源融资方式的选择

从我国电力企业外源融资方式历史变迁、重债务融资过渡至重股权融资次序选择可以看出,我国电力企业融资方式在宏观上受国家金融、财政制度等经济环境与融资制度影响,在微观上与电力企业治理结构密切相连.随着我国经济环境与融资制度的不断发展,在不同的金融制度和企业法人治理结构背景下电力融资方式也发生着深刻的变化.     

(r, QI)-Transform:Reversible Data Anonymity Based on Numeric Type of Data in Outsourced Database

An outsource database is a database service provided by cloud computing companies. Using the outsource database can reduce the hardware and software's cost and also get more efficient and reliable data processing capacity. However, the outsource database still has some challenges. If the service provider does not have sufficient confidence, there is the possibility of data leakage. The data may has user's privacy, so data leakage may cause data privacy leak. Based on this factor, to protect the privacy of data in the outsource database becomes very important. In the past, scholars have proposed k-anonymity to protect data privacy in the database. It lets data become anonymous to avoid data privacy leak. But k-anonymity has some problems, it is irreversible, and easier to be attacked by homogeneity attack and background knowledge attack. Later on, scholars have proposed some studies to solve homogeneity attack and background knowledge attack. But their studies still cannot recover back to the original data. In this paper, we propose a data anonymity method. It can be reversible and also prevent those two attacks. Our study is based on the proposed r-transform. It can be used on the numeric type of attributes in the outsource database. In the experiment, we discussed the time required to anonymize and recover data. Furthermore, we investigated the defense against homogeneous attack and background knowledge attack. At the end, we summarized the proposed method and future researches.     

外协队伍施工安全规范化管理实践

随着我国经济的迅猛发展，企业生产经营规模快速扩张，现阶段的设备检修维护和用工模式发生了改变，工程外包成为一种常用方式，但是外协工程队伍人员素质的参差不齐会给施工安全带来很多隐患。本文阐述了根据《安全生产法》对承包单位统一协调、管理的要求，企业对外协队伍规范化管理措施实践。     

Offshoring and Improvisational Learning: Empirical Insights into Developing Global R&D Capabilities

This study examines how global research and development (R&D) capabilities develop through improvisational learning. Using empirical insights from two large Swedish multinational companies and their early learning from establishing a captive R&D offshore unit in Bangalore, India, we use multicase inductive analysis to identify how companies cope with challenge related to coordinating R&D across geographically dispersed units through improvisational learning. Using a cooperative stage model analysis, we explain how improvisational learning occurs during the setup, start-up and ongoing stages of establishing captive R&D offshoring operations. We find that improvisational actions lead to developing routines as a response to solving unexpected coordination challenges and help explain how global R&D capabilities develop.     

对特色培养本科软件外包适用型人才的探索

本文通过分析我国对日软件外包行业的人才现状,指出高校人才培养需要抓住机遇,在专业上大胆改革创新。通过凝练天津科技大学中日合作计算机科学与技术专业的办学特色,探索一条培养对日软件外包行业本科层次适用型人才的道路。     

可验证的安全矩阵行列式计算云外包协议

云计算外包越来越流行的同时也带来了新的安全问题和挑战：输入/输出数据的隐私性和结果的可验证性。本文围绕云计算环境下的安全矩阵行列式计算外包展开研究,构建一个适用于大矩阵行列式计算的可验证的安全云外包协议,在客户端将原始矩阵盲化加密后传送到云服务器端执行计算,云服务器将计算结果和验证值返回给客户端进行解密和验证。理论分析表明,在恶意云的安全模型下协议满足正确性、输入/输出私密性、高效性和结果可验证性。     

多云协同架构下的遥感图像安全外包降噪方案

由于传输介质的干扰,遥感图像会被噪声污染,影响图像的处理和应用。遥感图像包含丰富的信息,致使普通计算机无法独立完成降噪任务,而云平台往往是不可信任甚至是恶意的,因此传统的图像降噪方案无法直接应用到云平台上。为保障遥感图像的可用性与安全性,提出一种基于多云协同的遥感图像安全外包降噪方案,既能实现灾备,又能实现分布式降噪,减少每个云平台的计算负担。利用[(k,n)]门限秘密共享方案将遥感图像共享给多个云服务器,云服务器根据改进的非局部均值降噪算法在密文域中完成图像降噪。