基于TMN的电信管理网研究与实现

为解决由于电信事业的发展对电信管理网所提出的更高要求,即兼容性、可持续性、综合技术应用性等方面的要求,提供了一种基于TMN架构的电信管理网的设计实现架构,对整个系统的架构进行了概括性的分析。该系统是一个成功应用的商用系统,采用了J2EE架构,对J2EE架构的应用具有一定的启示作用。依照该架构实现的电信管理网系统,无论从软件的复用性,可扩展性及产品的功能特点等指标,均满足了当前电信事业发展的要求。     

基于B/S模式矿山管理信息系统构建技术研究

在全面分析以往矿山管理信息特点的基础上，提出了基于B／S模式开发矿山信息系统的思路。对基于B／S模式开发矿山信息系统的关键技术及开发步骤进行了详细的介绍。     

The Impact of eBusiness and the Information Society on ‘STRATEGY’ and ‘STRATEGIC PLANNING’: An Assessment of New Concepts and Challenges

The current era of Information, Communication and Media Technologies (ICMT) has ushered in the era of eBusiness and the Information Society where traditional managerial paradigms are challenged and new business models are sought. One central area of managerial discourse is STRATEGY. Based upon a pilot study with leading European managers, consultants and academics, we offer a structured perspective on what may be the shape of things to come for STRATEGIC PLANNING in the context of eBusiness and the Information Society. Normative implications are explored.     

一种基于知识地图集的知识管理系统模型框架

在分析知识管理、知识管理系统(KMS)的含义和知识地图集技术的特点的基础上，提出了一种基于知识地图集的KMS模型框架，并且分析了该模型框架中知识地图集的组成及功能，讨论了KMS中知识地图集和知识存储之间的关系。依据该模型框架，组织易于构建知识管理系统，实现知识资源的共享与充分运用。最后，通过一个实例分析进一步说明了该模型框架的应用。     

过程链管理--用于制定和管理转型组织的工具

在当今企业环境日益复杂而活跃的背景条件下，企业需要不断进行重组和迅速转型。这要求企业要具备更强的适应性和更高的灵活性。为了确保实现这些动态的要求，企业必须制定和实施新型的组织形式。本文介绍过程链管理——一种面向过程进行转型的工具。本文首先简要说明了过程链管理应用的工具、过程链管理的任务和构造。它的出发点是由行动、结构、资源、和指挥所组成的过程链管理。在第二步骤中，重点阐述了客户取向这个过程链管理中最重要的取向量。总体来说，整个价值创造链及与此相关的内部交换关系都具有重要意义。在对过程链管理的方法进行了说明以后，提出了一个应用实例，该实例不仅描述了垂直重构，也对水平重构进行了描述。     

传感技术与RFID在血液管理分析中的运用

由于血液管理对于环境条件的特殊要求，针对血液管理分析提出了将传感技术与RFID技术结合后应用于其中的想法。简要介绍了RFID传感器标签的设计，分析了将其运用于血液管理分析后对加强流程监控、提高工作效率的好处，并主要从血液的出入库管理、跟踪管理、质控管理三个方面详细描述，阐明了方法的可行性。     

Improving Cost Estimates of Construction Projects Using Phased Cost Factors

Central to cost-based competition is the capability to accurately predict the cost of delivering a project. Most literature on cost estimation focuses on specific estimation methods as generic techniques and little attention has been paid to the unique requirements at each project stage. This note attempts to identify the critical factors for effective estimation at various stages of typical construction projects. Drawing from organization control theory and cost estimating literature, this note develops a theoretical framework that identifies the critical factors for effective cost estimation during each project phase of a conventional construction project. The underlying logic is that as a cost estimating effort progresses, both task programmability and output measurability improve. As a result, control effort will shift from input-oriented control to a combination of output and behavior control.     

Developing Cost Response Models for Company-Level Cost Flow Forecasting of Project-Based Corporations

The difficulty in applying the standard curve (S-curve) and cost-schedule integration (CSI) techniques for company-level cost flow forecasting in a project-based industry is the prerequisite of forecasting future unknown individual projects and contract classifications. By analyzing cost flows at the company level through a pool of macroeconomic and internal financial data, this paper proposes an innovative approach to firm-specific model estimation. First, a series of data transformations introduce linear relationships between cost, macroeconomic, and internal financial variables. Second, multivariate regression analysis is employed for initial model building. Third, for the purposes of model restructuring, a subsequent application of Yule–Walker estimates and incomplete principal component analysis is used. This paper uses a sample of four project-based construction firms to demonstrate model performance. Using this methodology, mean absolute percentage error (MAPE) values of the forecasting models range from 0.27 to 0.60%. As such, the transformed cost, macroeconomic, internal financial data could strongly predict company-level cost flow forecasting. While converting the predicted cumulative cost data to periodic cost flows, the MAPE values were augmented, ranging from 7.04 to 17.55%, thus, requiring future research.     

Production Equations for Unsteady-State Construction Processes

The production equation called Little’s law has been applied to construction data recently. However, Little’s law was derived for steady-state conditions assuming constant input and output rates and long production runs. Production in construction is inherently temporary, and learning curves and environmental influences often render input and output rates unequal and nonlinear. Starting with a conservation of mass formulation, general equations for work-in-process and cycle time for unsteady-state conditions and limited run production are developed. The motivation behind these equations is to explain common trends in production variables seen on construction projects. Previous studies have shown that when output from a construction production system is drastically increased, a significant upward impact is also seen on cycle time and work-in-process, and this work provides underlying theory and equations to explain these trends. Cycle time and work-in-process equations are presented as functions of time and on average. Data from construction activities are used to show that unsteady-state conditions commonly occur. Reasonable simplifications of the general equations provide guidelines for buffer sizing and resource allocation decisions.     

History of Construction, Engineering, and Management in the Department of Civil and Environmental Engineering at Penn State

At Penn State, the credit for broadening the Civil Engineering Department’s longstanding academic focus on analysis and design to include the construction phase must go to Dr. Harmer A. Weeden and his longtime associate Dr. Thomas D. Larson. Jack H. Willenbrock joined the Department as an Instructor in June 1968 and grew the construction program so that today about a fourth to a third of the civil undergraduates obtain employment in the construction industry. The program has awarded about 250 postbaccalaureate degrees.