A development framework for artificial intelligence based distributed operations support systems

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself

A Distributed Intelligenge Paradigm for Knowledge Management

In the last ten years, knowledge management (KM) has become a new fashioned managerial practice. Though KM theories seem to benefit from a "contamination" with cognitive and social sciences, which emphasize a subjective, contextual, and distributed approach to knowledge representation and integration, current technologies support what we may call a "god's eye" paradigm, in which knowledge is viewed as an objective resource. In this paper we discuss artificial intelligence theories and technologies that can support a shift to a new paradigm, called the "distributed intelligence" paradigm, in designing KM systems. Using the evolution of KM systems within Arthur Andersen Consulting as a motivating case study, we propose the framework of it MultiContext Systems as a specification language for distributed intelligence KM systems, and sketch an agent-based architecture as an example of a KM system which embodies the assumptions of the distributed intelligence paradigm

A Product Life Cycle Ontology for Additive Manufacturing

The manufacturing industry is evolving rapidly, becoming more complex, more interconnected, and more geographically distributed. Competitive pressure and diversity of consumer demand are driving manufacturing companies to rely more and more on improved knowledge management practices. As a result, multiple software systems are being created to support the integration of data across the product life cycle. Unfortunately, these systems manifest a low degree of interoperability, and this creates problems, for instance when different enterprises or different branches of an enterprise interact. Common ontologies (consensus-based controlled vocabularies) have proved themselves in various domains as a valuable tool for solving such problems. In this paper, we present a consensus-based Additive Manufacturing Ontology (AMO) and illustrate its application in promoting re-usability in the field of dentistry product manufacturing

Information Systems Effect on Enabling Knowledge Management

Purpose: This research aims to neutralize the impact of information systems on enabling knowledge management in the banking sector in Syria.   Theoretical framework: IT resources positively affect knowledge management capability. As studies (Watson 2007; O'Brien & Marakas 2011; Mao et al., 2016) and. We document a relationship between information systems enabling knowledge management in Syrian banks   Design/methodology/approach: This study of measuring this effect was based on the design of a questionnaire distributed to 369 individuals working in Syrian government banks in 2022.   Findings: This study concluded that there is a direct impact of information systems on enabling knowledge management, and the technological requirements of information systems have a greater impact than the organizational requirements. The study also showed that there were differences between the answers of the sample members in all the research axes, as it showed the lack of information systems or enabling knowledge management in banks for most workers from the second and third job categories, as opposed to workers from the first job category with great job experience, whose answers were positive towards the two research variables.   Research, Practical & Social implications: This article offers empirical support for theory-based claims and helps create a empirical framework for the success of knowledge management activities.   Originality/value: Very few research on management level employees' opinions of knowledge sharing in banks have been done in Syria

A Survey Of Knowledge Management Skills Acquisition In An Online Team-Based Distributed Computing Course

This paper investigates students’ perceptions of their acquisition of knowledge management skills, namely thinking and team-building skills, resulting from the integration of various resources and technologies into an entirely team-based, online upper level distributed computing (DC) information systems (IS) course. Results seem to indicate that more support of the thinking skills was provided by the offline resources than by the online resources, while both the online and offline resources were perceived as providing a lot of support for the team-building skills

The viability of IS enhanced knowledge sharing in mission-critical command and control centers

Engineering processes such as the maintenance of mission-critical infrastructures are highly unpredictable processes that are vital for everyday life, as well as for national security goals. These processes are categorized as Emergent Knowledge Processes (EKP), organizational processes that are characterized by a changing set of actors, distributed knowledge bases, and emergent knowledge sharing activities where the process itself has no predetermined structure. The research described here utilizes the telecommunications network fault diagnosis process as a specific example of an EKP. The field site chosen for this research is a global undersea telecommunication network where nodes are staffed by trained personnel responsible for maintaining local equipment using Network Management Systems. The overall network coordination responsibilities are handled by a centralized command and control center, or Network Management Center. A formal case study is performed in this global telecommunications network to evaluate the design of an Alarm Correlation Tool (ACT). This work defines a design methodology for an Information System (IS) that can support complex engineering diagnosis processes. As such, a Decision Support System design model is used to iterate through a number of design theories that guide design decisions. Utilizing the model iterations, it is found that IS design theories such as Decision Support Systems (DSS), Expert Systems (ES) and Knowledge Management Systems (KMS) design theories, do not produce systems appropriate for supporting complex engineering processes. A design theory for systems that support EKPs is substituted as the project\u27s driving theory during the final iterations of the DSS Design Model. This design theory poses the use of naive users to support the design process as one of its key principles. The EKP design theory principles are evaluated and addressed to provide feedback to this recently introduced Information System Design Theory. The research effort shows that use of the EKP design theory is also insufficient in designing complex engineering systems. As a result, the main contribution of this work is to augment design theory with a methodology that revolves around the analysis of the knowledge management and control environment as a driving force behind IS design. Finally, the research results show that a model-based knowledge captunng algorithm provides an appropriate vehicle to capture and manipulate experiential engineering knowledge. In addition, it is found that the proposed DSS Design Model assists in the refinement of highly complex system designs. The results also show that the EKP design theory is not sufficient to address all the challenges posed by systems that must support mission-critical infrastructures

BibGlimpse: The case for a light-weight reprint manager in distributed literature research

Background While text-mining and distributed annotation systems both aim at capturing knowledge and presenting it in a standardized form, there have been few attempts to investigate potential synergies between these two fields. For instance, distributed annotation would be very well suited for providing topic focussed, expert knowledge enriched text corpora. A key limitation for this approach is the availability of literature annotation systems that can be routinely used by groups of collaborating researchers on a day to day basis, not distracting from the main focus of their work. Results For this purpose, we have designed BibGlimpse. Features like drop-to-file, SVM based automated retrieval of PubMed bibliography for PDF reprints, and annotation support make BibGlimpse an efficient, light-weight reprint manager that facilitates distributed literature research for work groups. Building on an established open search engine, full-text search and structured queries are supported, while at the same time making shared collections of annotated reprints accessible to literature classification and text-mining tools. Conclusion BibGlimpse offers scientists a tool that enhances their own literature management. Moreover, it may be used to create content enriched, annotated text corpora for research in text-mining

Ground Based Operations Support By Artificial Intelligence

The increasing number and sustained duration of future manned or unmanned space missions, the growing complexity of spacecraft, the increasing variety of payloads and the demand for maximum economic efficiency of space operations will lead to the evolution of large-scale ground based operations infrastructures of increasing complexity and sophistication. In order to enhance the manageability and safety of operations under these aspects and to limit the amount of highly skilled personnel required, thereby supporting an early economic attractivity of space, the utilization of Artificial Intelligence (AI) as support for ground based operations appears to be a promising method which has received growing attention in recent years. In this paper, after an outline of the main areas of ground based operations support by AI, also these questions of the management of large distributed AI-systems within a complex communication environment are therefore addressed and required technology developments indicated which comprise in particular the direct or indirect utilization of databases and simulation facilities as knowledge sources for large AI-systems