基于云计算的营销决策支持系统

设计并实施了一种基于云计算的营销决策支持系统,和其他管理决策子系统发生交互,共同构成了完整的现代企业经营决策支持系统.系统的数据库采用分布式设计,使得系统既有独立处理本地数据库的能力,也可读取异地数据库中的数据.系统模型库包含多种营销因素的决策模型,并采用模型组合的思想,将复杂的决策问题通过模型之间的组合来实现.在流程设计上充分考虑人机交互,将用户的经验判断纳入到决策过程中.完成了系统的开发,并用仿真数据进行了系统测试,结果表明系统基本运行稳定,各子模块衔接良好,与其他子系统实现了数据共享.     

基于模式转换的分布式多媒体系统的结构模型

对于分布式多媒体系统,创建合适的结构模型是其重要的研究课题之一。文章在基于模式转换的思想基础上,提出了一种分布式多媒体系统的结构模型,该模型可有效地支持多媒体对象的表现和通信。     

基于构件的软件工程及其测试、维护和实践

论述了基于构件的软件工程（ＣＢＳＥ）的基本思想。并对其带来的测试和维护上的新问题及解决方案进行了探讨。最后给出所开发的视频编码软件包的例子。     

PC机与多单片机组成串行通信的新尝试

以实际应用的小型集散变频调速系统为例 ,介绍一种PC机与多AT89C2 0 51单片机之间串行通信的接口电路 ,并提出一种新的通信方法 ,即采用QBASIC语言提供通信语句来编写多机通信程序。该方法硬件紧凑 ,软件编程简单可靠。     

智能信息平台Jasmine ii研究及应用

介绍新一代Internet智能信息平台Jasmine ii的结构和特点,包括Jasmine ii的对象模型、访问技术,同时介绍了在该对象平台上开发成功的电子商务套装应用软件E－Mart Suite for Jasmine。最后,比较和分析了该软件的特点和优势。     

Blind Source Extraction for Noisy Mixtures by Combining Gaussian Moments and Generalized Autocorrelations

In the blind source extraction problem, the concept of generalized autocorrelations has been successfully used when the desired signal has special temporal structures. However, their applications are only limited to noise-free mixtures, which is not realistic. Therefore, this paper addresses the extraction of the noisy model based on these temporal characteristics of sources. An objective function, which combines Gaussian moments and generalized autocorrelations, is proposed. Maximizing this objective function, we present a blind source extraction algorithm for noisy mixtures. Simulations on synthesized signals, images, artificial electrocardiogram (ECG) data and the real-world ECG data show the better performance of the proposed algorithm. Moreover, comparisons with the existing algorithms further indicate its validity and also show its robustness to the estimated error of time delay.     

Towards a Mobile Code Management Environment for Complex,Real-Time,Distributed Systems

We present a novel mobile code management environment,currently under design and development. Our design employs anopen architecture, suitable for ``plug-and-play' with COTS andother groups' tools. While we have studied new algorithms, costand objective functions, and other fundamental issues, the maincontribution of this experimental research work is in the environmentitself. It should be noted that networked platforms, such asthe World Wide Web, are inherently not suitable for traditional,predictable real-time applications. Thus, real-time concernsnecessarily need to be blended with others concerns, and thetarget applications, making use of our environment, will toobe a blend of partially hard real-time and partially (or mostly)soft-real- time ones. The prototype environment will thereforesupport performance-based analysis and management focusing notonly on predictability but also on compilation, efficiency, safetyand other tradeoffs. We have selected the Java language and itsbytecode format as a representation for mobile code as well asa language for our implementation.     

Influence-based model decomposition for reasoning about spatially distributed physical systems

Many important science and engineering applications, such as regulating the temperature distribution over a semiconductor wafer and controlling the noise from a photocopy machine, require interpreting distributed data and designing decentralized controllers for spatially distributed systems. Developing effective computational techniques for representing and reasoning about these systems, which are usually modeled with partial differential equations (PDEs), is one of the major challenge problems for qualitative and spatial reasoning research.

This paper introduces a novel approach to decentralized control design, influence-based model decomposition, and applies it in the context of thermal regulation. Influence-based model decomposition uses a decentralized model, called an influence graph, as a key data abstraction representing influences of controls on distributed physical fields. It serves as the basis for novel algorithms for control placement and parameter design for distributed systems with large numbers of coupled variables. These algorithms exploit physical knowledge of locality, linear superposability, and continuity, encapsulated in influence graphs representing dependencies of field nodes on control nodes. The control placement design algorithms utilize influence graphs to decompose a problem domain so as to decouple the resulting regions. The decentralized control parameter optimization algorithms utilize influence graphs to efficiently evaluate thermal fields and to explicitly trade off computation, communication, and control quality. By leveraging the physical knowledge encapsulated in influence graphs, these control design algorithms are more efficient than standard techniques, and produce designs explainable in terms of problem structures.     

Super-Streaming: A New Object Delivery Paradigm for Continuous Media Servers

A number of studies have focused on the design of continuous media, CM, (e.g., video and audio) servers to support the real-time delivery of CM objects. These systems have been deployed in local environments such as hotels, hospitals and cruise ships to support media-on-demand applications. They typically stream CM objects to the clients with the objective of minimizing the buffer space required at the client site. This objective can now be relaxed due to the availability of inexpensive storage devices at the client side. Therefore, we propose a Super-streaming paradigm that can utilize the client side resources in order to improve the utilization of the CM server. To support super-streaming, we propose a technique to enable the CM servers to deliver CM objects at a rate higher than their display bandwidth requirement. We also propose alternative admission control policies to downgrade super-streams in favor of regular streams when the resources are scarce. We demonstrate the superiority of our paradigm over streaming with both analytical and simulation models.Moreover, new distributed applications such as distant-learning, digital libraries, and home entertainment require the delivery of CM objects to geographically disbursed clients. For quality purposes, recently many studies proposed dedicated distributed architectures to support these types of applications. We extend our super-streaming paradigm to be applicable in such distributed architectures. We propose a sophisticated resource management policy to support super-streaming in the presence of multiple servers, network links and clients. Due to the complexity involved in modeling these architectures, we only evaluate the performance of super-streaming by a simulation study.     

BPL: A set-based language for distributed system prototyping

Rapid prototyping of software and hardware is recognized as a very important step in timely, cost-effective system development. The complexity inherent in designing distributed computing systems and distributed problem solutions emphasizes the need for effective rapid prototyping tools. ADL/ADS is a testbed user interface tool for experimentation with critical research and design issues pertaining to distributed data processing (DDP). The experimenter expresses a candidate distributed system in terms of experiment objects, along with attributes and relationships. The experiment objects represent hardware, software, and behavior. This paper provides a brief overview of ADL/ADS, and gives especial emphasis to the Behavior Prototyping Language (BPL) within ADL/ADS. BPL is designed for expressing Behavior Modules (B_MODULEs)—the most versatile of the behavior objects. BPL incorporates set-theoretical approaches, and provides syntax designed for effectively describing manipulations of experiment objects, and their attributes and relationships.