35964038
Learning Engineering Models with the Minimum Description Length Principle
This paper discusses discovery of mathematical models from engineering data sets. KEDS, a Knowledge-based Equation Discovery System, identifies several potentially overlapping regions in the problem space, each associated with an equation of different complexity and accuracy. The minimum description length principle, together with the KEDS algorithm, is used to guide the partitioning of the problem space. The KEDSMDL algorithm has been tested on discovering models for predicting the performance efficiencies of an internal combustion engine.
12858200
Building Robust Learning Systems by Combining Induction and Optimization
Each concept description language and search strategy has an inherent inductive bias, a preference for some hypotheses over others. No single inductive bias performs optimally on all problems. This paper describes a system that couples induction with optimization to carry out an efficient search of large regions of inductive bias space. Experimental results are reported demonstrating the system's capacity to choose optimal biases even for complex and noisy problems.
6309018
Knowledge-based learning integrating acquisition and learning
Empirical learning algorithms are hampered by their inability to use domain knowledge to guide the induction of new rules. This paper describes knowledge-based learning, an approach to learning that selects the examples and relevant attributes for an empirical algorithm. Knowledge-based learning can be used for developing rules for engineering expert systems. Engineers often have some rules for problem solving, but also many experiences (examples) that facilitate solving problems. Knowledge-based learning systems are able to use both forms of knowledge.
37627056
SWIFT: system workbench for integrating and facilitating teams
There have been many R&D efforts in recent years to develop computer environments that directly enhance group problem-solving productivity. An example of such efforts is the computer-based virtual teaming technology (VTT) developed at the knowledge-based Engineering Sytems Research Laboratory (KESRL). The core software environment for KESRL's VTT is called SWIFT and is based on the knowledge processing technology (KPT) previously developed at KESRL to support various engineering design tasks. SWIFT is a flexible environment which enables the rapid development of collaborative applications, linking workers in distributed environments, of many domains. The paper presents the overall system architecture of SWIFT, and introduces the current and future R&D efforts at KESRL in realizing SWIFT for significant industrial applications.<<ETX>>
35812356
A Study of How Domain Knowledge Improves Knowledge-Based Learning Systems
Abstract A knowledge-based learning system is developed to demonstrate that intelligently selecting a subset of examples based on domain knowledge for rule induction can be more productive than using all provided examples. Knowledge-based learning uses an incomplete domain theory and examples to induce knowledge missing in the theory. Knowledge-based learning systems determine where knowledge is missing in a domain theory, select a relevant subset of examples to use in induction, and induce new rules or modify existing rules.
5343942
Knowledge-Based Equation Discovery in Engineering Domains
Machine learning techniques that can compress datasets into relationships that underlie the data have great utility for engineers. Most model discovery systems are not well suited to discovering comprehensible models in engineering domains. In this paper we present KEDS, a Knowledge-based Equation Discovery System, which uses a model-driven approach to discover equations and thereby build models from engineering data.
13902125
GCA: A Coclustering Algorithm for Thalamo-Cortico-Thalamic Connectivity Analysis
The reciprocal connectivity between the cerebral cortex and the thalamus in a human brain is involved in consciousness and related to various brain disorders, thus, in-vivo analysis of this connectivity is critically important for brain diagnosis and surgery planning. While existing work either focuses on fiber tracking analysis or on thalamic nuclei segmentation, to our best knowledge, no techniques yet exist for performing in-vivo analysis of thalamo-cortico-thalamic connectivity. In this paper, (i) we propose a new partitioning paradigm, called coclustering, to model this problem. In contrast to the traditional clustering paradigm, a coclustering procedure not only simultaneously partitions cortical voxels and thalamic voxels into groups, but also identifies the corresponding strong connectivities between the two classes of groups; (ii) we develop the first coclustering algorithm, genetic coclustering algorithm (GCA), to solve the coclustering problem; and (iii) we apply GCA to perform in-vivo analysis of the thalamo-cortico-thalamic connectivity and produce a strikingly clear 3D visualization of the seven thalamic nuclei groups as well as their connectivities to the corresponding cortical regions of a human brain
13993895
A formal framework for agent itinerary specification, security reasoning and logic analysis
Mobile agent technology supports object migration from one site to another autonomously and proactively, performing its designated location-dependent tasks. Although the concept of proactive mobility has recently been demonstrated in several research prototypes, there is a lack of formal treatment of such mobility from the perspective of a distributed programming language. How to specify, model and reason about travel itineraries of mobile agents is fundamentally important for the development of secure and reliable mobile agent systems. In this paper, first, we introduce an itinerary language, MAIL, to model the mobile behavior of proactive agents. The language is structured and compositional so that an itinerary can be constructed recursively from primitive itineraries. We then define the operational semantics of the language in terms of a set of inference rules and prove that MAIL is expressive enough for most migration patterns. Finally, we show that MAIL is amenable to formal methods to reason about mobility and verify correctness and safety properties.
1262760
Providing robust and ubiquitous security support for mobile ad-hoc networks
Providing security support for mobile ad-hoc networks is challenging for several reasons: (a) wireless networks are susceptible to attacks ranging from passive eavesdropping to active interfering, occasional break-ins by adversaries may be inevitable in a large time window; (b) mobile users demand "anywhere, anytime" services; (c) a scalable solution is needed for a large-scale mobile network. In this paper, we describe a solution that supports ubiquitous security services for mobile hosts, scales to network size, and is robust against break-ins. In our design, we distribute the certification authority functions through a threshold secret sharing mechanism, in which each entity holds a secret share and multiple entities in a local neighborhood jointly provide complete services. We employ localized certification schemes to enable ubiquitous services. We also update the secret shares to further enhance robustness against break-ins. Both simulations and implementation confirm the effectiveness of our design.
17835959
Toward resilient security in wireless sensor networks
Node compromise poses severe security threats in wireless sensor networks. Unfortunately, existing security designs can address only a small, fixed threshold number of compromised nodes; the security protection completely breaks down when the threshold is exceeded. In this paper, we seek to overcome the threshold limitation and achieve resiliency against an increasing number of compromised nodes. To this end, we propose a novel location-based approach in which the secret keys are bound to geographic locations, and each node stores a few keys based on its own location. The location-binding property constrains the scope for which individual keys can be (mis)used, thus limiting the damages caused by a collection of compromised nodes. We illustrate this approach through the problem of report fabrication attacks, in which the compromised nodes forge non-existent events. We evaluate our design through extensive analysis, implementation and simulations, and demonstrate its graceful performance degradation in the presence of an increasing number of compromised nodes.
15432335
A model for abstract process specification, verification and composition
An abstract business process contains a description the protocol that a business process engages in without revealing the internal computation of the process. This description provides the information necessary to compose the process with other Web services. BPEL supports this by providing distinct dialects for specifying abstract and executable processes. Unfortunately, BPEL does not prevent complex computations from being included in an abstract process. This complicates the protocol description, unnecessarily reveals implementation details, and makes it difficult to analyze correctness.
 We propose some restrictions on the data manipulation constructs that can be used in an abstract BPEL process. The restrictions permit a full description of a protocol while hiding computation. A restricted abstract process can easily be converted into an abstract BPEL process or expanded into an executable BPEL process. Based on these restrictions we propose a formal model for a business process and use it as the basis of an algorithm for demonstrating the correctness of a protocol described by a restricted abstract process. We then sketch an algorithm for synthesizing a protocol based on a formal specification of its outcome and the tasks available for its construction.