Value management and common accounting performance measures for corporations

Management is aware that the value of firms is the ultimate measure of company performance. However, management has been using common accounting measures as an operating guide because the linkage between operational planning and value is vague and complex and, therefore, difficult to apply. Managers need to have clear targets and performance measures to track progress. This paper examines if a set of common accounting performance measures are linked tightly to the overall value of the firm. An abductive learning network (ALN) approach, an artificial intelligence technique, is used in this research because an ALN approach is non-parametric and can capture a subtle dynamic relationship between input and output variables, which is not obvious in linear statistical analysis. Empirical results show that an ALN model is very effective in synthesizing the value of the firm using six common accounting variables. The results also provide four strategic variables that can be used for devising strategic and operating plans to maximize the value of firms.     

提高网络教学效果的方法浅析

中国的网络远程教育目前也正处于蓬勃发展的阶段,各种远教机构如雨后春笋般涌现。但在远教课程向网络转型的过渡时期,难免会有各种不尽如人意的地方。设计不够贴近学生、缺乏师生互动和技术运用的片面与僵化等是很多网络课程常有的通病。如何在课程设计上进行改进,使网络课程更具人性化,真正实现以学生为中心,是中国网络教育更上一层楼的关键问题之一。     

Virtual teamwork in very large undergraduate classes

Collaborative work is an important part of tertiary education but it is very difficult to arrange and supervise for extremely large classes of students in their first year. The possibility that computer-mediated communication can be used to facilitate this type of learning is appealing from a pragmatic organisational point of view. This paper explains in detail what a ‘virtual team’ is in the educational context. It reports on an interpretive field study where students taking an introductory course were allowed to choose where and when they did the required collaborative work. The paper discusses the factors that should be taken into account when offering students the option of working as a virtual team. These include factors that influence the students’ choice. The project cannot be considered to have been successful but indicates reasons for the lack of success and suggests contexts in which it would be valuable to repeat the project. The importance of extensive preparation in terms of teaching the students necessary social and technological skills cannot be over emphasised.     

Influence of geosynthetic reinforcement on the load-settlement characteristics of two-layer subgrade

The possibility of realistic prediction of two-layer subgrade load-settlement characteristics is discussed. The case of improvement of the soft subgrade properties using the geosynthetic reinforcement placed at the boundary between two different subgrade layers is analysed. In the first part of the paper, a short review of the main conclusions from experimental results dealing with the influence of geosynthetic reinforcement on the load-settlement characteristics of subgrade is presented. Then, the results of using the selected analytical membrane-action model to describe the reinforcement action in soil are discussed. The model is verified on the basis of data obtained from previously published laboratory tests. Particular attention is devoted to influencing some basic initial parameters on the accuracy of obtained results. Important problems which need intensive investigations are identified.     

A hierarchical model for structure learning based on the physiological characteristics of neurons

Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability. The characteristics of typical ANN models are fixed connections, with evolved weights, globalized representations, and globalized optimizations, all based on a mathematical approach. This makes those models to be deficient in robustness, efficiency of learning, capacity, anti-jamming between training sets, and correlativity of samples, etc. In this paper, we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing. A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures. The basic characteristics of this model are localized and random connections, field limitations of neuron fan-in and fan-out, dynamic behavior of neurons, and samples represented through different sub-circuits of neurons specialized into different response patterns. At the end of this paper, some important aspects of error correction, capacity, learning efficiency, and soundness of structural representation are analyzed theoretically. This paper has demonstrated the feasibility and advantages of structure learning and representation. This model can serve as a fundamental element of cognitive systems such as perception and associative memory.     

复杂条件下发挥锚杆支护作用的相关技术

介绍了在特殊地质和开采条件下,发挥锚杆支护作用的几种相关技术。     

Tracing success: graphical methods for analysing successful collaborative problem solving

The aim of this paper is to evaluate the use of trace diagrams for analysing collaborative problem solving. The paper describes a study where trace diagrams were used to analyse joint navigation in a virtual environment. Ten pairs of undergraduates worked together on a distributed virtual task to collect five flowers using two bees with each participant controlling one of the bees. This task is used extensively in research on multi-robot systems. The joint navigation of the pairs was analysed using trace diagrams. They showed that more successful pairs divided the task up, showed very little overlap and very little backtracking. Whereas, the less successful pairs, showed no task division, there was significant overlap and extensive backtracking. From this analysis we developed numerical measures of task division, overlap and backtracking. Task division was significantly and negatively related with task performance. Backtracking and overlap were significantly and positively correlated.     

裂缝性潜山储层地震描述技术

裂缝是潜山油气藏的重要储集层 ,潜山的油气产出与裂缝的发育情况密切相关 ,因此 ,对裂缝发育控制因素和裂缝发育规律进行了分析和探讨。尽管单条裂缝在地震资料上难以识别 ,但是裂缝带在地震资料上有其特征。描述了裂缝储层的地球物理特征 ,并利用测井约束反演技术、吸收系数技术、地震相分类和相干分析技术对潜山储层进行预测。通过在车古 2 0 1潜山的应用实例分析 ,说明以上 4种储层描述技术比较有效