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.
14135016
A Study on Illumination Invariant Face Recognition Methods Based on Multiple Eigenspaces
This paper presents two multiple illumination eigenspaces-based methods, RDEB and BPNNB, for solving the variable illumination problem of face recognition. The experiment shows that the methods have a high recognition ratio. In particular, BPNNB has outperformed the assumptive method which knows the illumination directions of faces and completes recognition in the specific eigenspace using eigenface method[2] for each face subset with a specific illumination direction.
9746543
Design an Interoperable Mobile Agent System Based on Predicate Transition Net Models
Mobile agents provide an effective and flexible style to develop advanced distributed systems. In order to promote interoperability and ensure the quality of mobile agent systems, it is necessary to formalize software architecture of mobile agent systems. In this paper, we not only define the software architecture of interoperable mobile agent systems using predicate transition nets, but also analyze the interoperability between agents. In addition, a formal model-driven design method to develop mobile agent systems is described with examples. Our method naturally integrates formal methods and practical approaches in the agent system design phase. The method can be used to develop other complex software systems as well.
11509547
Illumination invariant face recognition based on neural network ensemble
An illumination invariant face recognition method based on neural network ensemble architecture is proposed. Given a face image with an arbitrary illumination direction, it can complete recognition in a uniform way with high performance without knowing or estimating the illumination direction. Experimental result shows that the recognition ratio of the ensemble architecture is higher than the conventional approach that uses a single neural network to recognize faces of a specific illumination direction.
4695766
Threat-Driven Architectural Design of Secure Information Systems
To deal with software security issues in the early stages of system development, this paper presents a threatdriven approach to the architectural design and analysis of secure information systems. In this approach, we model security threats to systems with misuse cases and mitigation requirements with mitigation use cases at the requirements analysis phase. Then we drive system architecture design (including the identification of architectural components and their connections) by use cases, misuse cases, and mitigation use cases. According to the misuse case-based threat model, we analyze whether or not a candidate architecture is resistant to the identified security threats and what constraints must be imposed on the choices of system implementation. This provides a smooth transition from requirements specification to high-level design and greatly improves the traceability of security concerns in high assurance information systems. We demonstrate our approach through a case study on a security-intensive payroll information system.
14562584
Integrating functional and security requirements with use case decomposition
Misuse case modeling is a viable option to depict the security requirements together with functional requirements. To investigate the interplay between functional and security requirements, this paper presents an approach to decomposing use cases, misuse cases, and mitigation use cases. We identify relationships among decomposed cases for each case type (use, misuse, mitigation use) and ensure consistency among the cases as decomposition occurs by properly modeling shared and optional cases. We also assign applicable actors to the decomposed cases. Decomposition is conducted for each case type independently and then integrated with the "threatens" and "mitigates" relationships. We provide processes for the proper use of the "threatens" relationship between misuse cases and use cases and the "mitigates" relationship between mitigation use cases and misuse cases at different levels of abstraction. Thus, a complete set of security-centric requirements can be specified from the project outset to guide subsequent software development phases
12991047
The Application of Adaptive Partitioned Random Search in Feature Selection Problem
Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.
16362067
A federated approach to distributed network simulation
We describe an approach and our experiences in applying federated simulation techniques to create large-scale parallel simulations of computer networks. Using the federated approach, the topology and the protocol stack of the simulated network is partitioned into a number of submodels, and a simulation process is instantiated for each one. Runtime infrastructure software provides services for interprocess communication and synchronization (time management). We first describe issues that arise in homogeneous federations where a sequential simulator is federated with itself to realize a parallel implementation. We then describe additional issues that must be addressed in heterogeneous federations composed of different network simulation packages, and describe a dynamic simulation backplane mechanism that facilitates interoperability among different network simulators. Specifically, the dynamic simulation backplane provides a means of addressing key issues that arise in federating different network simulators: differing packet representations, incomplete implementations of network protocol models, and differing levels of detail among the simulation processes. We discuss two different methods for using the backplane for interactions between heterogeneous simulators: the cross-protocol stack method and the split-protocol stack method. Finally, results from an experimental study are presented for both the homogeneous and heterogeneous cases that provide evidence of the scalability of our federated approach on two moderately sized computing clusters. Two different homogeneous implementations are described: Parallel/Distributed ns (pdns) and the Georgia Tech Network Simulator (GTNetS). Results of a heterogeneous implementation federating ns with GloMoSim are described. This research demonstrates that federated simulations are a viable approach to realizing efficient parallel network simulation tools.
2868377
Intelligent decision system and its application in business innovation self assessment
In this paper, it is described how a multiple criteria decision analysis software tool, the Intelligent Decision System (IDS), can be used to help business self-assessment. Following a brief outline of a model for assessing business innovation capability and the IDS software, the process of using IDS to implement different types of assessment questions is discussed. It is demonstrated that IDS is a flexible tool capable of handling different types of data in self-assessment, including uncertain and incomplete data, and providing a wide range of information including scores, performance diversity, strength and weakness profile and graphics.
14141173
Distributed network simulations using the dynamic simulation backplane
Presents an approach for creating distributed, component-based simulations of communication networks by interconnecting models of sub-networks drawn from different network simulation packages. This approach supports the rapid construction of simulations for large networks by reusing existing models and software, and fast execution using parallel discrete event simulation techniques. A dynamic simulation backplane is proposed that provides a common format and protocol for message exchange, and services for transmitting data and synchronizing heterogeneous network simulation engines. In order to achieve plug-and-play interoperability, the backplane uses existing network communication standards and dynamically negotiates among the participant simulators to define a minimal subset of required information that each simulator must supply, as well as other optional information. The backplane then automatically creates a message format that can be understood by all participating simulators and dynamically creates the content of each message by using callbacks to the simulation engines. We describe our approach to interoperability as well as an implementation of the backplane. We present results that demonstrate the proper operation of the backplane by distributing a network simulation between two different simulation packages, ns2 and GloMoSim. Performance results show that the overhead for the creation of the dynamic messages is minimal. Although this work is specific to network simulations, we believe our methodology and approach can be used to achieve interoperability in other distributed computing applications as well.
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.