Special Theme: Project Management in E-Science: Challenges and Opportunities

In this introduction to the special theme: Project Management in e-Science: Challenges and Opportunities, we argue that the role of project management and different forms of leadership and facilitation can influence significantly the nature of cooperation and its outcomes and deserves further research attention. The quality of social interactions such as communication, cooperation, and coordination, have emerged as key factors in developing and deploying e-science infrastructures and applications supporting large-scale and distributed collaborative scientific research. If software is seen to embody the relational web within which it evolves, and if the processes of software design, development and deployment are seen as ongoing transformations of this dynamic web of relationships between technology, people and environment, the role of managers becomes crucial: it is their responsibility to balance and facilitate the dynamics of these relationships.     

Project Ernestine: Validating a GOMS Analysis for Predicting and Explaining Real-World Task Performance

Project Ernestine served a pragmatic as well as a scientific goal: to compare the worktimes of telephone company toll and assistance operators on two different workstations and to validate a GOMS analysis for predicting and explaining real-world performance. Contrary to expectations, GOMS predicted and the data confirmed that performance with the proposed workstation was slower than with the current one. Pragmatically, this increase in performance time translates into a cost of almost $2 million a year to NYNEX. Scientifically, the GOMS models predicted performance with exceptional accuracy. The empirical data provided us with three interesting results: proof that the new workstation was slower than the old one, evidence that this difference was not constant but varied with call category, and (in a trial that spanned 4 months and collected data on 72,450 phone calls) proof that performance on the new workstation stabilized after the first month. The GOMS models predicted the first two results and explained all three. In this article, we discuss the process and results of model building as well as the design and outcome of the field trial. We assess the accuracy of GOMS predictions and use the mechanisms of the models to explain the empirical results. Last, we demonstrate how the GOMS models can be used to guide the design of a new workstation and evaluate design decisions before they are implemented.     

MIS Opportunities in Facilities Management

Facilities—an enterprise's physical work environment—represent a major opportunity for MIS today. Facilities management extends a challenge to support a key strategic resource and a chance to build a solid business case for many technology investments.     

小软件开发的项目管理过程

通过分析小软件开发项目的特点及其开发过程中常见的问题,阐述合理的项目管理对成功开发小型软件的重要性,并根据工作实际,针对小软件开发提出项目管理的一般过程和方法。     

Genetic Algorithms for Project Management

The scheduling of tasks and the allocation of resource in medium to large-scale development projects is an extremely hard problem and is one of the principal challenges of project management due to its sheer complexity. As projects evolve any solutions, either optimal or near optimal, must be continuously scrutinized in order to adjust to changing conditions. Brute force exhaustive or branch-and-bound search methods cannot cope with the complexity inherent in finding satisfactory solutions to assist project managers. Most existing project management (PM) techniques, commercial PM tools, and research prototypes fall short in their computational capabilities and only provide passive project tracking and reporting aids. Project managers must make all major decisions based on their individual insights and experience, must build the project database to record such decisions and represent them as project nets, then use the tools to track progress, perform simple consistency checks, analyze the project net for critical paths, etc., and produce reports in various formats such as Gantt or Pert charts.Our research has developed a new technique based on genetic algorithms (GA) that automatically determines, using a programmable goal function, a near-optimal allocation of resources and resulting schedule that satisfies a given task structure and resource pool. We assumed that the estimated effort for each task is known a priori and can be obtained from any known estimation method such as COCOMO. Based on the results of these algorithms, the software manager will be able to assign tasks to staff in an optimal manner and predict the corresponding future status of the project, including an extensive analysis on the time-and-cost variations in the solution space. Our experiments utilized Wall's GALib as the search engine. The algorithms operated on a richer, refined version of project management networks derived from Chao's seminal work on GA-based Software Project Management Net (SPMnet). Generalizing the results of Chao's solution, the new GA algorithms can operate on much more complex scheduling networks involving multiple projects. They also can deal with more realistic programmatic and organizational assumptions. The results of the GA algorithm were evaluated using exhaustive search for five test cases. In these tests our GA showed strong scalability and simplicity. Its orthogonal genetic form and modularized heuristic functions are well suited for complex conditional optimization problems, of which project management is a typical example.     

Project Management for a Change

Along with the proliferation of personal computers in companies comes an increased need for security policies and programs. Recent experiences among MIS managers have shown that no degree of security can be considered too great —and it is the company's responsibility to see that these measures are taken.     

Project Assessment: A Tool for Improving Project Management

Application development projects fail for a myriad of reasons; most, however, stem from poor project management. This article describes a practical guide for analyzing projects from the initiation phase to close-out. Performed correctly, the guide increases the chances of project success as well as gives an organization an opportunity to develop project management skills.     

Project GreenLight: Optimizing Cyber-infrastructure for a Carbon-Constrained World

Even with a variety of aggressive energy efficiency measures, the ICT sector's carbon emissions will nearly triple from 2002 to 2020. We must accelerate ICT energy efficiency so that we can increase the use of ICT in smart infrastructure capable of reducing global greenhouse gas emissions.     

智能工作负载管理之机遇

2009年12月份,Novell宣布了一项重要的公司战略变化,重点针对新兴市场的智能工作负载管理(Intelligent Workload Management,IWM)制定解决方案.     

智能工作负载管理之机遇

2009年12月份,Novell宣布了一项重要的公司战略变化,重点针对新兴市场的智能工作负载管理(Intelligent Workload Management,IWM)制定解决方案。我坚信,我们的智能工作负载管理解决方案具有高度的差异性,并具有极强的竞争力,但我不能就此收受所有的     

软件开发项目中的风险管理和危机管理

风险管理和危机管理是软件开发项目管理中两个重要的方面，风险管理是预测、控制和管理项目风险，而危机管理则是应对项目的突发问题，他们是项目成功的有效保障。本文重点讨论了风险和危机产生的原因，以及风险和危机的管理方法。     

Learning Degradation-Invariant Representation for Robust Real-World Person Re-Identification

Person re-identification (Re-ID) in real-world scenarios suffers from various degradations, e.g., low resolution, weak lighting, and bad weather. These degradations hinders identity feature learning and significantly degrades Re-ID performance. To address these issues, in this paper, we propose a degradation invariance learning framework for robust person Re-ID. Concretely, we first design a content-degradation feature disentanglement strategy to capture and isolate task-irrelevant features contained in the degraded image. Then, to avoid the catastrophic forgetting problem, we introduce a memory replay algorithm to further consolidate invariance knowledge learned from the previous pre-training to improve subsequent identity feature learning. In this way, our framework is able to continuously maintain degradation-invariant priors from one or more datasets to improve the robustness of identity features, achieving state-of-the-art Re-ID performance on several challenging real-world benchmarks with a unified model. Furthermore, the proposed framework can be extended to low-level image processing, e.g., low-light image enhancement, demonstrating the potential of our method as a general framework for the various vision tasks. Code and trained models will be available at: https://github.com/hyk1996/Degradation-Invariant-Re-ID-pytorch.

     

Knowledge Management Today: Challenges and Opportunities

The management of “corporate knowledge,” the lifeblood of the organization, has been recognized as a formal practice over the past decade as advances in technology have made it possible for companies to collect vast amounts of data about their businesses, and to retrieve and disseminate this data throughout the organization.     

数据仓库项目管理的系统动力学方法

数据仓库项目涉及范围广、开发周期长,这会导致实施的效果不理想甚至造成项目的失败。文章采用系统动力学的方法研究数据仓库的项目管理,提出了数据仓库项目管理的系统动力学模型。     

工程项目的动态管理

在实际工作中,我们应当大力推广发展施工项目管理,其指建筑施工企业对某项具体建设项目的施工过程的管理.其中包括:投标承包、签订承包合同、施工准备、施工组织、交工验收.其目的是有效地实现施工项目的承包合同目标.具体推广也要推行行之有效的现代管理技术.重点集中在合同管理、质量管理、进度管理、成本管理、安全管理和信息管理.     

软件项目管理,让合作更有效

在软件开发项目中．许多组织采用合作开发约方式，这种方式的优点在干合作各方可以各取所长．例如业主方可以发挥其对业务过程理解方面的能力．而合作商（一般是专业的软件公司或IT企业）可以发挥其技术方面的优势但另一方面．这种方式也为项目管理带来了许多困难，由于在合作方式下．     

Real-World Robotics: Learning to Plan for Robust Execution

In executing classical plans in the real world, small discrepancies between a planner's internal representations and the real world are unavoidable. These can conspire to cause real-world failures even though the planner is sound and, therefore, proves that a sequence of actions achieves the goal. Permissive planning, a machine learning extension to classical planning, is one response to this difficulty. This paper describes the permissive planning approach and presents GRASPER, a permissive planning robotic system that learns to robustly pick up novel objects.     

浅谈软件项目管理中的需求管理

需求管理是整个软件工程管理的基础,也是决定一个软件项目成败的关键。本文论述了软件项目中需求管理的重要性及存在的问题,并针对这些问题提出相关解决方法。