粘土作为高放废物处置回填材料的可行性研究

本文以西北粘土为对象,对其压实行为、热传导、膨胀特性,以及吸附和渗透性能进行了初步研究,借以探讨西北粘土在高放废物处置中用作回填材料的可行性。试验表明,以西北粘土为基材,经过适当的热改性和吸附改性,在初始含水量约为9%,于70MPa 下成型,用作高放废物处置中的回填材料是可行的。     

Treatment of Humic Waters By Ozone

Two different generators for ozone were tested, a traditional electrical discharge generator and a generator based upon UV–irradiation of air at 150–180 nm. It was demonstrated that the traditional generator gave slightly higher reductions in levels of color for equivalent ozone dosages. Both gases affected the molecular weight distribution in the way that the bigger molecules were broken down to smaller ones. No significant difference between the molecular weight reduction efficiency of the gases was found.     

冶钢小方坯连铸机结晶器液面控制系统故障分析及对策

本文针对某一钢铁厂的一套小方坯连铸机结晶器液面自动控制系统，对其故障原因进行了深入分析，指出导致系统控制性能达不到设计要求长期无法投入运行的主要原因，并提出了相应的解决方法。     

等压灌注中液位控制影响因素及对策

通过分析等压灌注中影响液位的波动因素，找出关键控制点，并采取措施，以减少产品的液位波动。     

砷化镓材料中EPR“As_(Ga)”的退火行为

本文比较了中子辐照。压缩变形和原生LEC砷化镓等三种不同来源样品的EPR“As_(Ga)”的Hamiltonian参数。并系统地研究了EPR“As_(Ga)”的浓度和低温光猝灭行为随退火温度的变化,从而进一步验证了EPR“As_(Ga)”的本性,即除孤立As_(Ga)反位原子外,还可能包括As_(Ga)的一些空位络合物。这些不同本性的EPR“As_(Ga)”缺陷及其它有关的缺陷在样品热处理过程中可能相互转化。按照物理化学中Le Chatlier原理,缺陷的原始浓度和晶体内部应变能似应是引起这些转化反应的重要因素。     

基于等级保护的网络改造方法及异常情况分析与处理

本文介绍了在电力企业信息网中基于等级保护的网络安全防护改造方法。在具体案例中,针对网络改造过程中遇到的网络异常情况,技术人员通过逐一分析、排查,最终恢复正常网络,达到企业信息网络二级域改造的目的。网络安全防护改造方法以及异常情况分析排查案例对同类型企业在网络改造及异常排查工作中具有一定借鉴和指导意义。     

A self-adjusting algorithm for byzantine agreement

Summary Byzantine Agreement is important both in the theory and practice of distributed computing. However, protocols to reach Byzantine Agreement are usually expensive both in the time required as well as in the number of messages exchanged. In this paper, we present a self-adjusting approach to the problem. The Mostly Byzantine Agreement is proposed as a more restrictive agreement problem that requires that in the consecutive attempts to reach agreement, the number of disagreements (i.e., failures to reach Byzantine Agreement) is finite. Fort faulty processes, we give an algorithm that has at mostt disagreements for 4t or more processes. Another algorithm is given forn3t+1 processes with the number of disagreements belowt ²/2. Both algorithms useO(n ³) message bits for binary value agreement. Yi Zhao is currently working on his Ph.D. degree in Computer Science at University of Houston. His research interests include fault tolerance, distributed computing, parallel computation and neural networks. He obtained his M.S. from University of Houston in 1988 and B.S. from Beijing University of Aeronautics and Astronautics in 1984, both in computer science. Farokh B. Bastani received the B. Tech. degree in electrical engineering from the Indian Institute of Technology, Bombay, India, and the M.S. and Ph.D. degrees in electrical engineering and computer science from the University of California, Berkeley. He joined the University of Houston in 1980, where he is currently an Associate Professor of Computer Science. His research interests include software design and validation techniques, distributed systems, and fault-tolerant systems. He is a member of the ACM and the IEEE and is on the editorial board of theIEEE Transactions on Software Engineering.     

SERT结晶器液位控制系统

介绍一种梅山冶金公司板坯连同上应用的新型的结晶器液位控制系统，它由浮式式液位检测装置，ＲＳＥ１０００控制器和电动塞棒执行机构所组成，由法国ＳＥＲＴ公司成套制造。     

Level of interest sensing in spoken dialog using decision-level fusion of acoustic and lexical evidence

Automatic detection of a user's interest in spoken dialog plays an important role in many applications, such as tutoring systems and customer service systems. In this study, we propose a decision-level fusion approach using acoustic and lexical information to accurately sense a user's interest at the utterance level. Our system consists of three parts: acoustic/prosodic model, lexical model, and a model that combines their decisions for the final output. We use two different regression algorithms to complement each other for the acoustic model. For lexical information, in addition to the bag-of-words model, we propose new features including a level-of-interest value for each word, length information using the number of words, estimated speaking rate, silence in the utterance, and similarity with other utterances. We also investigate the effectiveness of using more automatic speech recognition (ASR) hypotheses (n-best lists) to extract lexical features. The outputs from the acoustic and lexical models are combined at the decision level. Our experiments show that combining acoustic evidence with lexical information improves level-of-interest detection performance, even when lexical features are extracted from ASR output with high word error rate.