Copyright (c) 2009 All rights reserved. http://works.bepress.com/fkurfess Recent documents in Franz J. Kurfess en-us Sun, 31 May 2009 05:54:58 PDT 3600 http://works.bepress.com/fkurfess/22 http://works.bepress.com/fkurfess/22 Thu, 09 Oct 2008 16:37:00 PDT The financial pressure to meet the need for change in computer-based systems through evolution rather than through revolution has spawned the discipline of reengineering. One driving factor of reengineering is that it is increasingly becoming the case that enhanced requirements placed on computer-based systems are overstressing the processing resources of the systems. Thus, the distribution of processing load over highly parallel and distributed hardware architectures has become part of the reengineering process for computer-based Navy systems. This paper presents an intermediate representation (IR) for capturing features of computer-based systems to enable reengineering for concurrency. A novel feature of the IR is that it incorporates the mission critical software architecture, a view that enables information to be captured at five levels of granularity: the element/program level, the task level, the module/class/package level, the method/procedure level, and the statement/instruction level. An approach to reverse engineering is presented, in which the IR is captured, and is analyzed to identify potential concurrency. Thus, the paper defines concurrency metrics to guide the reengineering tasks of identifying, enhancing, and assessing concurrency, and for performing partitioning and assignment. Concurrency metrics are defined at several tiers of the mission critical software architecture. In addition to contributing an approach to reverse engineering for computer-based systems, the paper also discusses a reverse engineering analysis toolset that constructs and displays the IR and the concurrency metrics for Ada programs. Additionally, the paper contains a discussion of the context of our reengineering efforts within the United States Navy, by describing two reengineering projects focused on sussystems of the AEGIS Weapon System. Lonnie R. Welch Articles http://works.bepress.com/fkurfess/23 http://works.bepress.com/fkurfess/23 Thu, 09 Oct 2008 16:36:30 PDT Many computational methods are based on the manipulation of entities with internal structure, such as objects, records, or data structures. Most conventional approaches based on neural networks have problems dealing with such structured entities. The algorithms presented in this paper represent a novel approach to neural-symbolic integration that allows for symbolic data in the form of objects to be translated to a scalar representation that can then be used by connectionist systems. We present the implementation of two translation algorithms that aid in performing object-oriented function approximation. We argue that objects provide an abstract representation of data that is well suited for the input and output of neural networks, as well as other statistical learning techniques. By examining the results of a simple sorting example, we illustrate the efficacy of these techniques. Dennis J. Taylor Conference Proceedings http://works.bepress.com/fkurfess/21 http://works.bepress.com/fkurfess/21 Thu, 21 Aug 2008 11:50:24 PDT In this paper we put forth a vision for organizations to fully embrace computer support. We propose a business-process oriented architecture for Electronic Enterprise Engineering (EEE) that will enable enterprises to manage and evolve all technological and organizational processes effectively; integrate and manage all enterprise information electronically; and empower knowledge workers at all levels with broad decision support capabilities. Our goal is for the EEE architecture to empower an enterprise to make the best use of its informational assets to operate effectively in this new era of electronic commerce. As part of this project we are developing a standard-based, customizable, integrated tool set called the Support Environment for Enterprise Engineering (SEEE). This paper presents the current SEEE architecture and shouts how it supports the three EEE goals. Michael Bieber Conference Proceedings http://works.bepress.com/fkurfess/20 http://works.bepress.com/fkurfess/20 Thu, 21 Aug 2008 11:50:19 PDT In this paper, the memory capacity of incompletely connected associative memories is investigated. First, the capacity is derived for memories with fixed parameters. Optimization of the parameters yields a maximum capacity between 0.53 and 0.69 for hetero-association and half of it for auto-association improving previously reported results. The maximum capacity grows with increasing connectivity of the memory and requires sparse input and output patterns. Further, parameters can be chosen in such a way that the information content per pattern asymptotically approaches 1 with growing size of the memory. Holger Bosch Articles http://works.bepress.com/fkurfess/19 http://works.bepress.com/fkurfess/19 Thu, 21 Aug 2008 11:49:47 PDT Knowledge representation and reasoning methods in artificial intelligence almost exclusively rely on symbol-oriented methods: Statements describing aspects and objects of the system to be modeled are represented through symbols (mostly text strings), and these symbols are stored in a computer, and manipulated according to the inference rules prescribed by the reasoning method. This works reasonably well in situations where knowledge is available in explicit form, typically through experts or written documents. In situations where knowledge is only available implicitly, e.g. in large data sets, other methods, often based on statistical approaches, have been used more successfully. Many of these methods are based on neural network techniques, which typically represent and process knowledge at a level below symbols; this is often referred to as sub-symbolic representation. This contribution discusses approaches to integrate symbol-oriented reasoning methods with sub-symbolic ones into hybrid systems. Franz J. Kurfess Conference Proceedings http://works.bepress.com/fkurfess/18 http://works.bepress.com/fkurfess/18 Thu, 21 Aug 2008 11:49:15 PDT This paper describes a distributed software requirements gathering methodology dealing with knowledge management for environmentally safer production and lifecycle aspects of tank ammunition. A requirements elicitation methodology is adapted and implemented as a distributed access tool on the Internet. This tool is used for gathering the requirements related information for a specific ammunition production process. During product development, requirements negotiation is the process where the customer needs are identified. This process is regarded as one of the most important parts of building a system because during this stage it is decided precisely what will be built. The concept has been extended from software centered systems to manufacturing processes, and also towards higher level concerns such as environmental awareness to be represented in the requirements of the product or system. The knowledge about what to build develops and evolves as a result of a collaborative requirement entry by different types of users and developers Ali H. Dogru Conference Proceedings http://works.bepress.com/fkurfess/17 http://works.bepress.com/fkurfess/17 Thu, 21 Aug 2008 11:48:39 PDT A method is disclosed for automatic level matching in a local network, particularly for a multicomputer arrangement, comprising an optical bus system, for the purpose of collision recognition. Given a required level matching, the process is executed such that a fundamental phase is provided in which level matching devices respectively individually assigned to the computers are synchronized with one another. A first matching phase is provided in which all level matching devices simultaneously execute a process for setting a reference voltage to the lowest received level, whereby the sum of all attenuation components of the signal path at the receiving side of the appertaining computer is taken into consideration. A second matching phase is provided in which all level matching devices successively execute a process for setting the transmission level of their own transmitter such that the emitted light power at its own receiver leads to the receiving power registered as lowest, whereby the sum of all attenuation components of the signal path at the transmitting side of the appertaining computer is taken into consideration. Hans Thinschmidt Patents http://works.bepress.com/fkurfess/16 http://works.bepress.com/fkurfess/16 Wed, 20 Aug 2008 16:37:03 PDT As the second part of a special issue on "Neural Networks and Structured Knowledge," the contributions collected here concentrate on the extraction of knowledge, particularly in the form of rules, from neural networks, and on applications relying on the representation and processing of structured knowledge by neural networks. The transformation of the low-level internal representation in a neural network into higher-level knowledge or information that can be interpreted more easily by humans and integrated with symbol-oriented mechanisms is the subject of the first group of papers. The second group of papers uses specific applications as starting point, and describes approaches based on neural networks for the knowledge representation required to solve crucial tasks in the respective application. Franz J. Kurfess Articles http://works.bepress.com/fkurfess/15 http://works.bepress.com/fkurfess/15 Wed, 20 Aug 2008 16:37:00 PDT As more and more knowledge and information becomes available through computers, a critical capability of systems supporting knowledge management is the classification of documents into categories that are meaningful to the user. In a step beyond the use of keywords, we developed a system that analyzes the sentences contained in unstructured or semi-structured documents, and utilizes an ontology reflecting the domain knowledge for a semantic classification of the documents. An experimental system has been implemented for the analysis of small documents in combination with a limited ontology; an extension to larger sets of documents and extended ontologies, together with an application to practical tasks, is the focus of ongoing work. Ching Kang Cheng Conference Proceedings http://works.bepress.com/fkurfess/14 http://works.bepress.com/fkurfess/14 Wed, 20 Aug 2008 16:36:56 PDT This collection of articles is the first of two parts of a special issue on "Neural Networks and Structured Knowledge." The contributions to the first part shed some light on the issues of knowledge representation and reasoning with neural networks. Their scope ranges from formal models for mapping discrete structures like graphs or logical formulae onto different types of neural networks, to the construction of practical systems for various types of reasoning. In the second part to follow, the emphasis will be on the extraction of knowledge from neural networks, and on applications of neural networks and structured knowledge to practical tasks. Franz J. Kurfess Articles