基于小角度高位技术的钻孔初采期瓦斯治理

回采工作面初采期瓦斯涌出不均衡,易出现瓦斯超限现象。针对新源煤矿近距离煤层群开采、瓦斯涌出量大等特点,提出了小角度高位钻孔抽采治理初采期瓦斯的方法;2219工作面应用实践表明,初采期内,小角度高位钻孔抽采瓦斯纯量最高5.25m3/min,瓦斯抽采率64.02%,回风流瓦斯浓度最高为0.32%,上隅角最高瓦斯浓度0.96%,未出现瓦斯超限现象,取得了很好的初采期瓦斯治理效果。     

基于MSTP以太网专线远程视音频传输的分析和实现

基于MSTP以太网专线进行远程视音频传输,是一种结构简单、线路便宜、容易搭建的传输系统.由于MSTP以太网专线的独特设计,点到点的透传方式,容易实现对用户MAC帧点到点的透传,在线路上能独享带宽,业务延迟小,且和其它业务完全隔离,安全性高,这种业务适合广播级视音频信号远程传输的应用.     

结合公钥加密和关键字可搜索加密的加密方案

带关键字搜索的公钥加密(PEKS)是一种有用的加密原语，它允许用户将在加密数据上搜索的功能委托给不可信的第三方服务器，而不影响原始数据的安全性和隐私性。但是，由于缺乏对于数据的加密以及解密能力，PEKS方案不能单独进行使用，必须与标准的公钥加密方案(PKE)相结合。因此，Baek等人在2006年引入了一种新的加密原语，称为结合PKE和PEKS的加密方案(PKE+PEKS)，它同时提供了PKE和PEKS的功能。目前，已有文献提出了几种PKE+PEKS方案。然而，他们都没有考虑关键字猜测攻击的问题。本文提出一个新的高效且能够抵抗关键字猜测攻击的PKE+PEKS方案，与已有方案相比，该方案在性能上有很大的提升，并且在生成关键字和数据密文时，不需要使用双线性对，极大地降低了计算和存储成本。安全性分析表明，本文中所提出的方案能够满足密文隐私安全性、陷门不可区分性和抗关键字猜测攻击的安全性。效率分析表明，本分提出的方案更加高效。     

关于加强员工考勤管理工作的几点思考

本文介绍了江汉油田员工考勤管理工作的基本情况,梳理和分析了当前员工考勤管理中存在的问题及原因,提出了要进一步细化和完善管理制度,强化过程监督和责任落实,逐步推进考勤公示制度化等措施。     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。     

0Cr20Mn21Ni2N奥氏体不锈钢锻件组织性能研究

研究了无磁钻铤用0Cr20Mn21Ni2N奥氏体不锈钢圆棒锻件横截面的室温强度、硬度和韧性等力学性能,并从微观角度进行了分析。在圆棒表层区域观察到了锻造变形态晶粒组织,而直径四分之一区域为再结晶组织,平均晶粒尺寸为80μm,芯部再结晶晶粒尺寸粗化为150μm,这些差异是由不同的变形温度和降温速度造成的。这种组织差异导致的室温拉伸性能和冲击韧性也有相应的变化趋势。研究结果表明,在900、1000℃以0.5 s-1的应变速率压缩的0Cr20Mn21Ni2N试验钢样品,其应力应变曲线具有一定的加工硬化特征,其芯部硬度比应变速率为0.1 s-1的样品分别提升了28、15 HB。在700、800℃以20%以上的变形量进行压缩时,峰值抗力显著提高,而在900、1000℃以10%~50%的变形量进行压缩时,峰值抗力均无明显提高,可保证顺利的变形过程。     

构皮滩水电站泄洪洞优化设计

构皮滩水电站为满足2008年12月工程提前发电的需要,结合现有泄洪洞地质情况和施工情况对泄洪洞布置进行了专题研究,结果表明利用降低进口高程为550 m的泄洪洞和坝身放空底孔联合参与后期导流,可缓解2007年导流隧洞下闸封堵后大坝在2008年汛期施工的压力,为大坝施工增加了2个月左右的工期。     

乌江索风营水电站地下厂房岩锚梁镜面混凝土施工技术

镜面混凝土是水电工程建设中新兴的一门施工技术,在乌江索风营水电站地下厂房岩锚梁混凝土施工中采用了镜面混凝土,这在技术上是一次大胆的尝试和创新,既满足了功能上的要求,同时也达到了美观和装饰地下厂房的效果,为今后水电工程施工中广泛采用镜面混凝土技术提供了样本和宝贵经验。     

Uplink Scheduling in CDMA Packet-Data Systems

Uplink scheduling in wireless systems is gaining importance due to arising uplink intensive data services (ftp, image uploads etc.), which could be hampered by the currently in-built asymmetry in favor of the downlink. In this work, we propose and study algorithms for efficient uplink packet-data scheduling in a CDMA cell. The algorithms attempt to maximize system throughput under transmit power limitations on the mobiles assuming instantaneous knowledge of user queues and channels. However no channel statistics or traffic characterization is necessary. Apart from increasing throughput, the algorithms also improve fairness of service among users, hence reducing chances of buffer overflows for poorly located users. The major observation arising from our analysis is that it is advantageous on the uplink to schedule “strong” users one-at-a-time, and “weak” users in larger groups. This contrasts with the downlink where one-at-a-time transmission for all users has shown to be the preferred mode in much previous work. Based on the optimal schedules, we propose less complex and more practical approximate methods, both of which offer significant performance improvement compared to one-at-a-time transmission, and the widely acclaimed Proportional Fair (PF) algorithm, in simulations. When queue content cannot be fed back, we propose a simple modification of PF, Uplink PF (UPF), that offers similar improvement. Hereafter, we refer to users with low recieved power at the base even when transmitting at peak transmit power as “weak” users, and the strongly recieved users at the base as “strong” users. Krishnan Kumaran is currently a member of the Complex Systems Modeling section in the Corporate Strategic Research of ExxonMobil Corp., Clinton, NJ. Formerly, he was a Member of Technical Staff in the Mathematics of Networks and Systems Research Department at Bell Labs in Murray Hill, NJ, where his research interests were in modeling, analysis and simulation of design, resource management and scheduling issues in telecommunication networks. Lijun Qian is an assistant professor in the Department of Electrical Engineering at Prairie View A&M University. He received his B.S. from Tsinghua University in Beijing, M.S. from Technion-Israel Institute of Technology, and Ph.D. from WINLAB, Rutgers University, all in electrical engineering. Before joining PVAMU, he was a researcher at Networks and Systems Research Department of Bell Labs in Murray Hill, NJ. His major research interests are in wireless communications and networking technologies, especially in radio resource management, protocol design, TCP/RLP optimization and MPLS traffic engineering.