33017168
An ontology engineering methodology for DOGMA
Although ontologies occupy a central place in the Semantic Web and related research domains, there are currently not many fully fledged ontology engineering methodologies available. In this paper, we want to present an integrated methodology for ontology engineering from scratch, inspired by various scientific disciplines, in particular database semantics and natural language processing.
1361502
Model Ontological Commitments Using ORM+ in T-Lex
When designing and developing ontology based applications, we semantically ground them by ontologically committing the application rules to their respective domain. These rules can be, for instance decision rules for a decision support system. For the DOGMA framework we have introduced ORM + , a novel extension of ORM for modeling, visualizing and interchanging ontological commitments. In this paper, we illustrate our ongoing research on ORM + and T-Lex as its supporting tool. We demonstrate in the field of on-line customer management.
16597693
On Conducting a Decision Group to Construct Semantic Decision Tables
Semantic Decision Table (SDT) was introduced to support collaborative decision making. Semantics, a group of decision makers, mutual understanding and collaborative environment(s) are at the heart of SDT. In practice, it is rather difficult to construct SDT within a decision group. We try to tackle this problem by modeling SDT within the context of information system, which is based on McGrath's Conceptual Framework for the Study of Group. Ontologies and DOGMA (Developing Ontology-Grounded Methods and Applications) approach to ontology engineering are proposed to store the semantics and mutual understanding for SDT. In this paper, we also propose a generic method of guiding a group to construct SDT, which is illustrated with an example of online customer management in the privacy domain.
40790501
A Practical Peer-Performance-Aware DHT
How to Build an efficient Distributed Hash Table (DHT) is a fundamental issue in Peer-to-Peer research field. Previous solutions ignore the heterogeneity of the large scale network. However, in practice, the fact is that the resource held by each peer in the Internet is extremely diverse. And the the willing to share local resources of each peer is also diverse. Therefore, the contribution for the system of a peer should depend on the resources it holds or how many resources it want to share, and should not be uniform. In this paper, we propose a Peer-Performance-Aware Distributed Hash Table (PPADHT) which aims to exploit the heterogeneity. It takes the performance difference of peers into consideration to construct a dynamic variation of wrapped butterfly to achieve the goal. We also show how to optimize the performance of PPADHT in the view of hop counts by random graphs. Our simulation results show that the average lookup hop counts of the PPADHT is approximately a log scale with constant out degrees. And it can achieve loadbalance in two ways: both the document load and message routing load, without introducing any additional load on the peer. Here, the load balance means the load is proportion to the performance of peer.
8498633
The Data Scales in Multi-valued Context Based on Formal Concept Analysis
Formal Concept Analysis has very important meaning in mathematical methods for data mining and knowledge processing. In the face of the variety of the data structure, traditional methods can hardly meet decider’s need. This paper summarizes a few of data structure for the concept analysis and present the data scale methods for each other based on their own characters. It not only extends the application of the concept analysis, but also makes the data scale methods more efficiently.
15679648
First-aid: surviving and preventing memory management bugs during production runs
Memory bugs in C/C++ programs severely affect system availability and security. This paper presents First-Aid, a lightweight runtime system that survives software failures caused by common memory management bugs and prevents future failures by the same bugs during production runs. Upon a failure, First-Aid diagnoses the bug type and identifies the memory objects that trigger the bug. To do so, it rolls back the programto previous checkpoints and uses two types of environmental changes that can prevent or expose memory bug manifestation during re-execution. Based on the diagnosis, First-Aid generates and applies runtime patches to avoid the memory bug and prevent its reoccurrence. Furthermore, First-Aid validates the consistent effects of the runtime patches and generates on-site diagnostic reports to assist developers in fixing the bugs.
 We have implemented First-Aid on Linux and evaluated it with seven applications that contain various types of memory bugs, including buffer overflow, uninitialized read, dangling pointer read/write, and double free. The results show that First-Aid can quickly diagnose the tested bugs and recover applications from failures (in 0.084 to 3.978 seconds). The results also show that the runtime patches generated by First-Aid can prevent future failures caused by the diagnosed bugs. Additionally, First-Aid provides detailed diagnostic information on both the root cause and the manifestation of the bugs. Furthermore, First-Aid incurs low overhead (0.4-11.6% with an average of 3.7%) during normal execution for the tested buggy applications, SPEC INT2000, and four allocation intensive programs.
38545491
Defining Re-usable Composite Aspect Patterns: An FDAF Based Approach
Architecting secure systems is an important and challenging problem. Solutions to model individual, or atomic, security capabilities have been proposed, including security patterns, component based, aspect-oriented, and service-oriented approaches. However, little work is available on how to model reusable compositions of security capabilities, where the security capabilities interact with each other and other parts of the system design. Here, an aspect-oriented approach to modeling composite aspects is presented. The approach is defined as an extension to the Formal Design Analysis Framework (FDAF). The FDAF metamodel is extended to support the static representation of composite aspects and an approach to defining the compositions is introduced. A composite aspect that provides Account Lockout with Selective Event Logging (ALSEL) capabilities is used as an example.
9189850
The Parameter Optimization of Human-Simulated Intelligent Controller Based on Improved Genetic Algorithm
The human-simulated intelligent controller, using a hierarchical and multi-mode control structure, effectively solves the control difficult problems of many complex systems. But there are many parameters to be determined. In order to solve them, the paper introduces an improved genetic algorithm (IGA) which is combined with orthogonal design method. It is served as the simulation experiment platform by the cart-double pendulum. Through selected the reasonable fitness function and determined the appropriate parameters range, using the IGA, the parameters of the human-simulated intelligent controller are optimized. The simulation results show the IGA is better than the manual adjustment method. So it is proved that the IGA is more effective in solving the parameter optimization of human-simulated intelligent controller, and also promotes the more extended application space of intelligent control theory.