40757344
A Pi-calculus-Based Business Process Formal Design Method
The pi-calculus is a model of concurrent computation, which can express communication between correlation processes. It provides a way of constructing systems in a bottom-up manner by composing subsystems, and it also has strict formal semantics. Therefore, pi-calculus is very suitable for designing business processes which are presently becoming more and more complicated. The paper proposes a composition-oriented approach to business process design based on pi-calculus theory and gives the formal definition of business process. It also illustrates the design method by simulating an example of order processing. By this method, a complicated business process can be divided into several independent simple sub-modules, which can greatly reduce the complexity of business process design.
14510404
Model replication: transformations to address model scalability
2 SUMMARY In Model-Driven Engineering, it is often desirable to evaluate different design alternatives as they relate to scalability issues of the modeled system. A typical approach to address scalability is model replication, which starts by creating base models that capture the key entities as model elements and their relationships as model connections. A collection of base models can be adorned with necessary information to characterize a specific scalability concern as it relates to how the base modeling elements are replicated and connected together. In current modeling practice, such model replication is usually accomplished by scaling the base model manually. This is a time-consuming process that represents a source of error, especially when there are deep interactions between model components. As an alternative to the manual process, this paper presents the idea of automated model replication through a model transformation process that expands the number of elements from the base model and makes the correct connections among the generated modeling elements. The paper motivates the need for model replication through case studies taken from models supporting different domains.
16418111
Levels of Independence in Aspect-Oriented Modeling
We are investigating the application of aspect-oriented principles as an aid toward improving the capabilities of domain-specific modeling. The approach, in general, provides transformations by weaving modeling aspects into a base model. The modeling aspects provide variation points within the model and can be used to drive the synthesis of the model into different artifacts. In this brief position paper, we describe how our current and future work improves the capabilities offered in a model-based tool. We highlight several levels of independence that make the approach applicable to numerous modeling situations.
3219801
Aspect mining from a modelling perspective
Aspect mining aims at identifying, analysing, and refactoring crosscutting concerns throughout a legacy system for the purpose of improving software modularisation. This paper presents our investigation into raising the benefits of aspect mining to high level domain-specific models. A key contribution is the capability to identify crosscutting concerns early in development, which will assist in the modularisation of a design through aspects, before proceeding to the implementation level. Furthermore, our experience has led us to believe that aspects are easier to identify at the modelling level, because much of the accidental complexities of implementation concerns are not present in the corresponding modelling abstractions.
14774281
A Composition-Oriented Approach for Business Process Formal Design
Traditional approaches to designing business processes are often inadequate for complicated, distributed, and collaborated settings. However since network technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore a new approach is needed. To this end, we describe the motivation, conceptualization, and analysis of a composition-oriented business process design method. The key advance of our method is that it uses process algebra pi-calculus as its formal basis and builds a complex process by composing simple structured process control modules to reduce the complexity of business process design as well as let several designers collaborate the design of a complex process. To make business process more clear, we also provide way of separating exception processing logic from normal process control logic and provide scooping mechanisms to minimize the detrimental effects of unplanned contingencies by ways of composition
7333588
Automating change evolution in model-driven engineering
The escalating complexity of software and system models is making it difficult to rapidly explore the effects of a design decision. Automating such exploration with model transformation and aspect-oriented techniques can improve both productivity and model quality. The combination of model transformation and aspect weaving provides a powerful technology for rapidly transforming legacy systems from the high-level properties that models describe. Further, by applying aspect-oriented techniques and program transformation, small changes at the modeling level can trigger very large transformations at the source code level. Thus, model engineers can explore alternative configurations using an aspect weaver targeted for modeling tools and then use the models to generate program transformation rules for adapting legacy source code on a wide scale.
20173388
Spectral Decomposition Approach for Transient Analysis of Multi-Server Discrete-Time Queues
Abstract Discrete time queueing systems are extensively used in modeling the ATM environment at the cell level. This paper examines the transient behavior of a discrete time FCFS multiple server queue. For the arrival process we assume a general discrete time Markovian batch arrival process, where the batch size distribution of the arrivals in successive slots is governed by a finite state discrete time Markov chain. We show that once the spectral decomposition of the “probability generating matrix” of the arrival process is obtained, the complete solution in the transform domain may be given. Using the complex analysis technique and Cauchy's integral formula, we present an efficient numerical method for the numerical calculation of a few performance measures of interest, namely transient probability of queue being empty, and the mean of the queue length distribution. We also generalize our numerical method in the situations where the superposition of a number of independent arrival sources are fed to the queue. It is shown that the numerical complexity of obtaining the transient solution in this case can be substantially reduced by using the approach based on the Kronecker product. The finite buffer case is also analyzed.
13486467
Computing Exact p-Value for Structured Motif
Extracting motifs from a set of DNA sequences is important in computational biology. Occurrence probability is a common used statistics to evaluate the statistical significance of a motif. A main problem is how to calculate the occurrence probability of the motif on the random model of DNA sequence efficiently and accurately. In this paper, we are interested in a particular motif model which is useful in transcription process. This motif, which is called structured motif, is composed two motif words on single nucleotide alphabet and with fixed spacers between them. We present an efficient algorithm to calculate the exact occurrence probability of a structured motif on a given sequence. It is the first nontrivial algorithm to calculate the exact p-value for such kind of motifs.
8627694
Interweave Neural Networks with Evolutionary Algorithms, Cellular Computing, Bayesian Learning and Ensemble Learning
A neural networks are able to give solutions to complex problems in business intelligence and financial engineering due to their nonlinear processing. This paper consists of a survey of various business intelligence and financial engineering and so on applications based on the neural networks, and also a summary of the recent techniques such as still evolutionary algorithms, cellular computing, Bayesian learning and ensemble learning. The neural networks can be powerful tools in several fields of business intelligence and financial engineering. It can be concluded that, the future of neural networks lies in their use in conjunction with other advanced technologies.
2367333
Building Accountability Middleware to Support Dependable SOA
The Intelligent Accountability Middleware Architecture (Llama) project supports dependable service-oriented architecture (SOA) monitoring, runtime diagnosis, and reconfiguration. At its core, Llama implements an accountability service bus that users can install on existing service-deployment infrastructures. It collects and monitors service execution data from a key subset of services; enables Llama users to incorporate others' advanced diagnosis models and algorithms into the framework; and provides enterprise service bus extensions for collecting service profiling data, thus making process problems transparent to diagnose. Finally, experimental results indicate that using Llama contributes a modest amount of system overhead.
18945895
Advances in Fuzzy Method for Natural Computing
Both natural computing and fuzzy method exhibit human-like mental processing. Natural computing is the field of research that works with computational techniques inspired in part by natural systems. Fuzzy method is an alternative to traditional notions of set membership and logic, and it occurs in many applications of engineering, science and medicine. This paper presents a survey of recent advances in fuzzy method for natural computing, such as fuzzy artificial neural networks, fuzzy genetic algorithms, fuzzy ant colony optimization, fuzzy artificial immune systems, etc. We utilize uncertainty handling capacity of fuzzy method for modeling ambiguity, and the learning ability of natural computing for efficiently traversing large search spaces.