7297586
Diversifying and improving business process management systems by service cooperation middleware
Emerging service oriented business process management (BPM) systems require efficient middleware infrastructure. However, current techniques for middleware are not optimal for that because they all do not have service-oriented natures themselves. This paper introduces a novel service cooperation middleware (SCM), which is designed to meet such requirements. It improves the development and integration of loosely coupled service oriented BPM system by applying several concepts such as control flow semantic and projection operation, etc. Furthermore, based on the SCM architecture, the related process integration suit viz. ISProcessIntegration (PI) can be widely applied into all kinds of scenes, for example EAI, B2B, B2C, P2P, cluster, with different topologies.
23372402
Information Concept Lattice and Its Reductions
In this paper, the combination of formal concept analysis and rough set theory is considered. The notion of information concept lattice is presented and some properties are given. We present the reduction theory of information concept lattice and obtain the reduction method. Information concept lattice is compared with rough set theory and concept lattice.
2247575
Towards dynamic process with variable structure by reflection
Advancing information technologies are increasing the evolution and variation of software resources. Applications that cannot adapt to dynamic environments will decrease their usefulness, particularly to business process systems that face requirements changed frequently. After surveying related work, we propose a new formalism for modeling dynamic process in which the state space and transition function are enriched so that one model can transit to another model at runtime by the computational reflection that aims to represent and modify its own design. Such goal necessitates an appropriate runtime environment. We introduce the service cooperation middleware (SCM) because it is service-oriented, into which the reflection mechanism is easily attached to support structural and behavioural changes on processes at runtime.
46077798
A Component-Based Analytical Performance Model of IP-Based SAN
In this paper we propose a component-based analytical performance model for IP-based SAN. This model evaluates and analyzes the behavior of IP network, cache, RAID and disks under multiple synchronous I/O workloads by using closed queueing networks. The theoretical results are compared with the results from a real IP-based SAN using a variety of synthetic workloads. These experiments prove that the component-based method is an appropriate way to build performance model for a complex storage system. Using the model, we can find out that the bottleneck of SAN performance is network or storage node under different workloads or applications. We also identify areas for future research in the performance analysis of real IP-based SAN.
15326279
GCS-MA: A group communication system for mobile agents
Reliable messaging is a key component necessary for mobile agent systems. Current researches focus on reliable one-to-one message delivery to mobile agents. But how to implement a group communication system for mobile agents remains an open issue, which is a powerful block that facilitates the development of fault-tolerant mobile agent systems. In this paper, we propose a group communication system for mobile agents (GCS-MA), which includes totally ordered multicast and membership management functions. We divide a group of mobile agents into several agent clusters, and each agent cluster consists of all mobile agents residing in the same sub-network and is managed by a special module, named coordinator. Then, all coordinators form a ring-based overlay for interchanging messages between clusters. We present a token-based algorithm, an intra-cluster messaging algorithm and an inter-cluster migration algorithm to achieve atomicity and total ordering properties of multicast messages, by building a membership protocol on top of the clustering and failure detection mechanisms. Performance issues of the proposed system have been analysed through simulations. We also describe the application of the proposed system in the context of the service cooperation middleware (SCM) project.
38303932
Fuzzy inference based on fuzzy concept lattice
In this paper, a fuzzy inference method based on the notion of fuzzy concept lattice is studied. We first propose a new form of fuzzy concept lattice, and then based on three kinds of known fuzzy concept lattices and our new fuzzy concept lattice, two coherent fuzzy inference methods, the lower approximate fuzzy inference and the upper approximate fuzzy inference, are proposed, and the combined use of the two methods will make the fuzzy inference more precise.
38900432
Fast (Structured) Newton Computations
Many vector-valued functions, representing expensive computations, are also structured computations. In this case the calculation of the Newton step can be greatly accelerated by exploiting this structure. It is often not necessary, nor economic, to form the true Jacobian in the process of computing the Newton step; instead, a more cost-effective auxiliary Jacobian matrix is used. This auxiliary matrix can be sparse even when the true Jacobian matrix is dense; consequently, sparse matrix technology can be used, to great speed advantage, both in forming the auxiliary matrix and in solving the auxiliary linear system.
15069022
An integrated baseball digest system using maximum entropy method
In this paper, we propose a novel system that is able to automatically detect and classify highlights from baseball game videos in TV broadcast. The digest system gives complete indexes of a baseball game which cover all of the status changes in a game. We achieve this by seamlessly integrating image, audio and speech clues using a maximum entropy based method. What distinguishes our system from previous ones is that we emphasize on the integration of multimedia features and the acquisition of domain knowledge through machine learning process. Integration of multimedia features is important because with the current state-of-the-art image and audio analysis techniques, most image and audio features we can extract from videos are very low level, and detecting/classifying sports game highlights based on features from single medium are doomed to yield poor performances. Acquiring domain knowledge through learning process is preferred over heuristic rules because machine learning process is more powerful for discovering and expressing domain knowledge. We perform extensive experiments on game videos including various stadiums, teams and broadcasted by different TV stations.
29445330
Bifurcations of travelling wave solutions in a model of the hydrogen-bonded systems
By using the theory of bifucations of dynamical systems to a model of the Hydrogen-bonded systems, the existence of solitary wave, kink and anti-kink wave solutions and uncountably infinite many smooth and non-smooth periodic wave solutions is obtained. Under different parametric conditions, various sufficient conditions to guarantee the existence of the above solutions are given. In some simple parametric conditions, exact explicit and implicit solution formulas are listed.
30599384
Category-based Web personalization system
There has been a massive growth in systems on the Internet that can personalize the content delivered to individual users. This paper develops a category-based Web personalization system in which an unconventional system logger, along with a category generator and a customizer, was designed. This system obtains and records more precise information directly from the users' activity and the objects they access. In addition, the system is designed with its own method to match and deliver individual information in which each user might be interested. Analysis and comparisons with related work are addressed in this research.
156293
An efficient and backwards-compatible transformation to ensure memory safety of C programs
Memory-related errors, such as buffer overflows and dangling pointers, remain one of the principal reasons for failures of C programs. As a result, a number of recent research efforts have focused on the problem of dynamic detection of memory errors in C programs. However, existing approaches suffer from one or more of the following problems: inability to detect all memory errors (e.g., Purify), requiring non-trivial modifications to existing C programs (e.g., Cyclone), changing the memory management model of C to use garbage collection (e.g., CCured), and excessive performance overheads. In this paper, we present a new approach that addresses these problems. Our approach operates via source code transformation and combines efficient data-structures with simple, localized optimizations to obtain good performance.