11130686
An Aspect-Oriented Approach to Security Requirements Analysis
This paper presents an aspect-oriented approach to integrated elicitation of functional and security requirements based on use case-driven development. We identify security threats with respect to use cases and adopt threat mitigations for preventing or reducing security threats. To capture crosscutting nature of threats and mitigations, we specify them as aspects that encapsulate pointcuts and advice. A threat (mitigation) pointcut is a collection of join points in use cases at which the use cases are threatened (secured); whereas threat/mitigation advice describes how a threat can become an attack (can be mitigated). Eliciting threats and mitigations as aspects provides a structured way for separating functional and security concerns
8230807
A Petri Net Based Software Architecture for UAV Simulation
This paper presents a Petri net-based hierarchical architecture for multiple Unmanned Aerial Vehicle (UAV) simulations in order to facilitate rapid prototyping via visual modeling and analysis. Using high-level Colored Petri nets, we specify UAV control structure by a hierarchy of mission control net and task nets: the mission control net, built upon task nets, models the decision making process of the UAV simulation; tasks nets are built from primitive UAV behaviors and environmental behaviors. To realize effects of UAV behaviors on the simulation environment, procedures may be associated with transitions in Petri nets. To demonstrate the approach, we describe two experimental UAV mission scenarios: sweeping search and multi-point attack.
8292696
Human-agent teamwork for distributed team training
This paper presents an approach to human-agent mixed teams for distributed team training, demonstrated through the integration of the domain independent multiagent architecture CAST with the military command-and-control simulation software DDD (distributed dynamic decision-making). We extend the CAST architecture in a way such that agents can replace any number of teammates on a DDD team. To capture the overall picture of teamwork, we explore the MALLET language in CAST for the specification of team structures and processes that involve both humans and agents.
18622586
State-based incremental testing of aspect-oriented programs
Taking aspects as incremental modifications to their base classes, this paper presents an incremental approach to testing whether or not aspect-oriented programs and their base classes conform to their respective behavior models. We exploit a rigorous aspect-oriented extension to state models for capturing the impact of aspects on the state transitions of base class objects as well as an explicit weaving mechanism for composing aspects into their base models. We generate abstract tests for base classes and aspect-oriented programs from their state models. As base class tests are not necessarily valid for aspect-oriented programs, we identify several rules for maximizing reuse of concrete base class tests for aspects according to the state-based impact of aspects on their base classes. To illustrate our approach, we use two examples that indicate distinctive types of aspect-oriented applications and exhibit fundamental features in complex applications: aspects removing state transitions from base classes and aspects adding and modifying state transitions in base classes. Our results show that majority of base class tests can be reused for aspects, but subtle modifications to some of them are necessary. In particular, positive (or negative) base class tests can become negative (or positive) aspect tests. We also discuss how several types of aspect-specific faults can be revealed by the state-based testing.
205336
A strategy for persistent object service under CORBA and Web environment
With the rapid development of the Internet, the integrated applications of Web, database, CORBA and Java have offered the three-tiered client/server application models a good computing environment and implementation strategy. This paper briefly introduces this kind of client/server application model based on CORBA and Web, and discusses a persistent object service for it. The paper describes in detail the persistent object service's architecture model, interactive process of components, main interface descriptions and some considerations when implementing this strategy. Finally, a summary is supplied for the persistent object service.
342298
Nonlinear information aggregation via evidential reasoning in multiattribute decision analysis under uncertainty
In many decision situations, it is inevitable to deal with both quantitative and qualitative information under uncertainty. Evidence-based reasoning within a multiple criteria decision analysis framework provides an alternative way of handling such information systematically and consistently. In this paper, the evidential reasoning (ER) approach is introduced, which is based on a recursive ER algorithm that, in essence, constitutes a nonlinear information aggregation process. To facilitate the application of the ER approach and as an indispensable part of its development, the nonlinear features of the ER information aggregation process need to be thoroughly investigated and properly understood. This forms the theme of this paper where the nonlinear features are explored by examining typical reasoning patterns in aggregating harmonic, quasi-harmonic, and contradictory decision information. This analytical investigation provides insights into the recursive nature of the ER approach as well as valuable experience that could be useful to other researchers and practitioners interested in developing and applying operation research/artificial intelligence (OR/AI)-based approaches for decision analysis under uncertainty. The analytical study is complemented by the numerical studies of two application examples. The analysis of a quality assessment problem for motor engines is aimed to show the step-by-step process of implementing the ER approach and to illustrate its nonlinear features in a real-life decision situation. The study of a more complex assessment problem in ship design is intended to demonstrate the potential of the ER approach and its supporting software for dealing with general decision problems.
1250480
Understanding protein dispensability through machine-learning analysis of high-throughput data
MOTIVATION
Protein dispensability is fundamental to the understanding of gene function and evolution. Recent advances in generating high-throughput data such as genomic sequence data, protein-protein interaction data, gene-expression data and growth-rate data of mutants allow us to investigate protein dispensability systematically at the genome scale.


RESULTS
In our studies, protein dispensability is represented as a fitness score that is measured by the growth rate of gene-deletion mutants. By the analyses of high-throughput data in yeast Saccharomyces cerevisiae, we found that a protein's dispensability had significant correlations with its evolutionary rate and duplication rate, as well as its connectivity in protein-protein interaction network and gene-expression correlation network. Neural network and support vector machine were applied to predict protein dispensability through high-throughput data. Our studies shed some lights on global characteristics of protein dispensability and evolution.


AVAILABILITY
The original datasets for protein dispensability analysis and prediction, together with related scripts, are available at http://digbio.missouri.edu/~ychen/ProDispen/


CONTACT
xudong@missouri.edu.
2839172
A framework of fuzzy diagnosis
Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent elearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e.g., the fault diagnosis of student behaviors in the elearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, fuzzy diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world elearning case is described to demonstrate the application of our diagnostic framework.
40999406
Multi-agent collaboration for B2B workflow monitoring
Business-to-business (B2B) applications environments are exceedingly dynamic and competitive. This dynamism is manifested in the form of changing process requirements and time constraints. However, current workflow management technologies have difficulties to solve the challenges problems, such as: how to deal with the dynamic nature of B2B commerce processes, how to manage the distributed knowledge and recourses, and how to reduce the transaction risk. In this paper, a collaborative multi-agent system has been proposed. Multiple intelligent agents in our system can work together not only to identify the workflow problems, but also to solve such problems, by applying business rules, such as re-organizing the procurement and the transaction processes, and making necessary workflow process changes.