CaO-SiO2-Al2O3-MgO-TiOx-FeOy体系氧化动力学

用电动势和化学分析方法研究了富钛还原熔渣－ＣａＯ－ＳｉＯ_２－Ａｌ_２Ｏ_３－ＭｇＯ－ＴｉＯ_ｘ－ＦｅＯ_ｙ体系的氧化动力学,得出了氧在熔渣中的扩散速率常数分别为 ０． ６６×１０~（－５） ｍ· ｓ~（－１）和 １． ９８×１０~（－５） ｍ·ｓ~（－１）,研究表明：固体电解质构成的氧浓差电池法得出的结果不仅可靠,且方法快速、简便．     

三峡工程移民迁建区灾害地质体改造与利用研究

三峡工程移民迁建区地质环境复杂 ,建设用地严重不足。如何在治理的基础上对滑坡等灾害地质体开发利用是一项风险极大 ,但具非常现实意义的课题。本文论述了预应力锚拉桩在库区大型滑坡防治中的应用成果 ,这种方法不仅能有效地控制滑坡体的稳定性 ,同时 ,也能根据移民工程要求提供适宜的建设用地 ;介绍了注浆方法对库区分布较广的以崩塌、滑坡、岩溶成因为主的崩滑堆积体的改造问题 ,它不仅可以大大降低移民迁建区地基与边坡处理的工程造价 ,也为库区灾害地质体的改造提供了范例 ;弃渣是库区极为突出的环境地质问题 ,不仅危害长江 ,也对移民迁建区构成严重威胁 ,本文介绍了巫山新城等利用加筋土技术处理弃渣 ,并大大增加建设用地的实例 ,由于该挡墙高达 5 6 m,超出了一般意义下的加筋土挡墙范畴 (通常不超过 2 0 m) ,因此出现了前缘筋带断裂和面板脱落问题 ,本文介绍了应用锚管注浆技术进行面板修复的设计 ,为复杂地质条件地区高加筋挡土墙的安全修建提供了经验.     

Discovering interesting statements from a database

Knowledge discovery aims at extracting new knowledge from potentially large databases; this may be in the form of interesting statements about the data. Two interrelated classes of problem arise that are treated here: to put the subjective notion of ‘interesting’ into concrete terms and to deal with large numbers of statements that are related to one another (one rendering the other redundant or at least less interesting). Four increasingly subjective facets of ‘interestingness’ are identified: the subject field under consideration, the conspicuousness of a finding, its novelty, and its deviation from prior knowledge. A procedure is proposed, and tried out on two quite different data sets, that allows for specifying interestingness by various means and that ranks the results in a way that takes interestingness (relevance, evidence) as well as mutual relatedness (similarity, affinity) into account—manifestations of the second and third facets of interestingness in the given data environment.     

In Memoriam

I sketch the rich life and multifaceted work of Philip Morrison (1915–2005), from his early life in Pittsburgh, Pennsylvania, and higher education at the Carnegie Institute of Technology and the University of California at Berkeley, to his contributions to the Manhattan Project, his research at Cornell University and the Massachusetts Institute of Technology after the war, his subsequent political activity on behalf of nuclear disarmament, his role in the search for extraterrestrial intelligence, and his enormous influence as an educator, public speaker, and writer. A.P. French is Professor of Physics, Emeritus, at the Massachusetts Institute of Technology.     

An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances

In this paper, an overview is presented of the existing metaheuristic solution procedures to solve the multi-mode resource-constrained-project scheduling problem, in which multiple execution modes are available for each of the activities of the project. A fair comparison is made between the different metaheuristic algorithms on the existing benchmark datasets and on a newly generated dataset. Computational results are provided and recommendations for future research are formulated.     

Multi-mode resource constrained multi-project scheduling and resource portfolio problem

This paper introduces a multi-project problem environment which involves multiple projects with assigned due dates; activities that have alternative resource usage modes; a resource dedication policy that does not allow sharing of resources among projects throughout the planning horizon; and a total budget. Three issues arise when investigating this multi-project environment. First, the total budget should be distributed among different resource types to determine the general resource capacities, which correspond to the total amount for each renewable resource to be dedicated to the projects. With the general resource capacities at hand, the next issue is to determine the amounts of resources to be dedicated to the individual projects. The dedication of resources reduces the scheduling of the projects’ activities to a multi-mode resource constrained project scheduling problem (MRCPSP) for each individual project. Finally, the last issue is the efficient solution of the resulting MRCPSPs. In this paper, this multi-project environment is modeled in an integrated fashion and designated as the resource portfolio problem. A two-phase and a monolithic genetic algorithm are proposed as two solution approaches, each of which employs a new improvement move designated as the combinatorial auction for resource portfolio and the combinatorial auction for resource dedication. A computational study using test problems demonstrated the effectiveness of the solution approach proposed.