从"电化教育"到"教育技术"--实践的发展与理论的升华

通过分析AECT’94定义的演变和电化教育的发展历程，本着历史的、现实的态度，对教育技术的定义给出了合理的建议，并分析了电化教育与教育技术的关系，以统一人们在思想上和理论上的认识。     

我国石油企业跨国经营战略的探讨

石油企业走出国门，实施跨国经营，是解决我国国内油气资源供求矛盾加剧的必然选择，也是维护和保障我国石油安全乃至国家经济安全的必由之路。文章探讨了我国石油企业国际化经营的必然性及其动因，进一步分析了目前我国石油企业国际化经营的发展现状，在此基础上提出了我国三大石油集团实施“走出去”战略的八项对策。     

磁防垢除垢技术研究与应用新进展

回顾了磁防垢除垢技术的发展历程，介绍了磁防垢除垢技术的作用效果和应用情况，分析了磁防垢除垢技术研究现状和存在的问题，跟踪报道了磁防垢除垢技术研究的新进展。     

慎重看待大用户直供电问题

论述了在电力市场初期我国缺少实施大用户直供电所必须具备的若干条件,分析了当前开展大用户直供电存在的问题及可能造成的影响,指出开展直供是改革的趋势但不可急于求成.     

基于神经网络系统的项目投资风险评价探讨

与传统的评价方法不同，神经网络模型具有自学习、自组织、自适应能力等的特点，它较好的克服了传统项目评价局限性以及依赖专家经验的弊端，为项目投资风险评价开辟了新途径。论文阐述了神经网络结构与原理，分析了项目投资风险评价的神经网络模型，通过应用评价，进一步探讨其应用价值及其意义。     

探析高校在注册会计师行业人才培养中的定位和职责

20多年来,中国注册会计师行业在服务于改革开放和市场经济体制建设的过程中,自身也得到了长足的发展,行业建设进入了一个新的阶段。随着市场经济体制建设的深化和经济全球化程度的不断提高,注册会计师行业也必须直面提升执业队伍的专业素质、执业能力和职业道德水平的客观要求,以便适应国际化发展对专业人才的需求。为此,中国注册会计师协会发布了《关于加强行业人才培养工作的指导意见》(以下简称“三十条”),明确提出了加强行业人才培养的指导思想和总体思路以及人才培养的宏伟目标,力争在不太长的时间内,打造出一支在质量和数量上能够满…     

Optimizing the credit term decisions in supply chain finance

We study a credit term determination problem in the context of a supplier-buyer supply chain. The supplier's credit term decision is simultaneously made with its production and inventory decisions, and most importantly, it is impacted by the buyer's order quantity. We present a new game-theoretic framework to model this problem, which captures the interaction between the supplier's credit term decision and the buyer's order decision in a multi-period setting. An exact method based on nonlinear programming is implemented to obtain the optimal solutions. We apply our methodologies on a real world case. The computational results show that our approach significantly outperforms the heuristics with fixed credit terms, and either a short or a long credit term can be sub-optimal for the supplier in profitability. Our work offers the first data-driven model and solution approach that assists purchasing and supply managers to make optimal dynamic credit term decision in conjunction with production, ordering and inventory decisions in a game-theoretic setting.     

Intelligent agents for adaptive security market surveillance

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

浅谈选煤厂建设投资估算影响因素及改进措施

本文对选煤厂建设工程投资估算中影响准确性的因素进行了分析,并结合BP神经网络理论基于Matlab软件对选煤厂带式输送机及栈桥单位工程进行了数值模拟,通过对比数值模拟结果与概算指标估算结果,详细阐述了可以提高选煤厂建设工程投资估算准确性的几点建议。