A proposed validation framework for expert elicited Bayesian Networks

The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.     

A framework for performance measurement in the e-business environment

The advent of networked economy calls for new understanding of business, and it is evidenced by the visible trend of traditional businesses either migrating to e-business or expanding to embrace electronic commerce. Constant change in the environment means continually evolving strategies, new products, new processes and new technologies to adopt. E-business metrics are needed to measure performance with the firm’s strategic focus in mind, and they must go beyond the Web metrics that are discussed in the usual electronic commerce context. The basic objective of this paper is to present a framework for developing performance measurement metrics in the e-business environment. The proposed framework, designed by incorporating the balanced scorecard methodology with existing taxonomies of e-business models and the theories behind them, is intended to enable firms to develop new metrics that are needed to implement e-business strategies and tactics.     

A framework for virtual organization creation in a breeding environment

Effectiveness in the process of creating virtual organizations (VO) is an important pre-condition for having a truly dynamic VOs, in response to collaboration opportunities in fast changing market contexts. A realistic approach to materialize agility in VO creation is defined under the assumption of a VO Breeding Environment (VBE), that guarantees the preparedness of its members to quickly get engaged in collaboration processes. After a survey of past approaches and a characterization of the VBE concept, a discussion of the process and suggested functionalities towards a VO creation framework are presented in this context. Finally a list of supporting tools is described and future research challenges are pointed out.     

A workload-dependent task assignment policy for crowdsourcing

Crowdsourcing marketplaces have emerged as an effective tool for high-speed, low-cost labeling of massive data sets. Since the labeling accuracy can greatly vary from worker to worker, we are faced with the problem of assigning labeling tasks to workers so as to maximize the accuracy associated with their answers. In this work, we study the problem of assigning workers to tasks under the assumption that workers’ reliability could change depending on their workload, as a result of, e.g., fatigue and learning. We offer empirical evidence of the existence of a workload-dependent accuracy variation among workers, and propose solution procedures for our Crowdsourced Labeling Task Assignment Problem, which we validate on both synthetic and real data sets.     

A personal computer based expert system framework for the design of experiments

In the field of industrial engineering, experimental design play a large role in the manufacturing quality. Knowledge based systems for parameter design will provide the quality engineer with a powerful tool to increase quality. Just as the past ten years saw a movement away from inspection to statistical process control, the future will see a shift from statistical process control to system and parameter design. Improvements in quality will increasingly come from products that are robust in design which will perform well in the very variable environment that is the global market.     

Visual programming environment for hybrid expert systems

This paper proposes an architecture for hybrid expert system development which combines expert problem-solving functions and other conventional computational functions by visual programming technology. The visual programming technique is used both for task-specific knowledge representation and for procedural programming for connecting functional components. In knowledge representation, knowledge is visually represented in the form of decision tables and decision trees. In procedural visual programming, each functional object is displayed as a box-shaped icon with accessible ports which are connected by wires on the graphic editor. Based on the architecture, an expert system shell for the classification task, called HOLON/VP(DT), is incorporated in a visual programming system called HOLON/VP. This paper briefly describes the tool and its evaluation based on some application systems developed with the tool.     

A formalized delegation model for multimedia social networks

In response to the issues of second-hand sharing and repeat delegation of the digital content in existing multimedia social networks, this paper proposed a novel formalized delegation model for multimedia social network. In accordance with this model, delegators can independently lay down delegation policies. Further, related delegation constraints and strategies were identified to solve delegation conflicts. When a conflict arises among several delegations, strategies could be used to solve the conflict. This delegation model can control the authorities and are delegated consistently until the authorization expires or is revoked. And also, the paper presented essential security policies that lead to revoking different authorities. A use case of real multimedia social network further verified the efficiency and effectiveness of the proposed model.     

An agent-based framework for cooperating expert systems in concurrent engineering

This paper describes an agent-based framework with a tandem integration architecture for cooperating distributed, heterogeneous, and autonomous concurrent engineering systems. The approach has been experimented with using the prototype AGENTS system. It is demonstrated that design tools can be dynamically connected and configured to construct highly complex systems on an incremental basis, designing and proving one system at a time without bothering the rest. A major advantage of the approach is the balance between the interoperability and the autonomy of individual systems.     

A theoretic and practical framework for scheduling in a stochastic environment

There are many systems and techniques that address stochastic planning and scheduling problems, based on distinct and sometimes opposite approaches, especially in terms of how generation and execution of the plan, or the schedule, are combined, and if and when knowledge about the uncertainties is taken into account. In many real-life problems, it appears that many of these approaches are needed and should be combined, which to our knowledge has never been done. In this paper, we propose a typology that distinguishes between proactive, progressive, and revision approaches. Then, focusing on scheduling and schedule execution, a theoretic model integrating those three approaches is defined. This model serves as a general template to implement a system that will fit specific application needs: we introduce and discuss our experimental prototypes which validate our model in part, and suggest how this framework could be extended to more general planning systems.     

NEPTUNE: A new expert planning tool for users in a network environment

MARS (mission activities and resources scheduler) is a planning and scheduling tool for both automatic and interactive generation of spacecraft timelines of realistic complexity, which has been extensively tested, e.g. for HERMES, EURECA, or Spacelab mission planning. In its new version it has been extended to include full distributed mission planning capability (as required for the COLUMBUS mission planning scenario) under the ESA contract NEPTUNE (new expert planning tool for users in a network environment). This paper describes the main features of the planning tool MARS in its new NEPTUNE version and sketches its applicability to the distributed mission planning scenario and for other (non-space) domains.     

Integrating expert systems and operations research: A conceptual framework

Expert System technologies can provide significant benefits if integrated with operations research (OR) applications, either by using free-standing systems or by integrating them into existing OR tools. This paper first distinguishes between physical and functional integration, and then focuses on aspects of the latter. Process and technique-oriented functional integration are defined, and several conceptual issues reviewed. These include the need for and resources necessary for such integration, difficulties associated with achieving successful integrated ES-OR applications, and the integration's impact on operations researchers and their organizations.     

GAMEES: a probabilistic environment for expert systems

This paper describes GAMEES (Graphical Modelling Environment for Expert Systems), an interactive graphical environment for building and processing Belief Networks and Influence Diagrams. We review the existing systems designed for analogous purposes, and, after a brief introduction to Belief Networks and Influence Diagrams, we describe the graphical interface, discuss algorithms for probabilistic inference on these networks and illustrate the current implementation of GAMEES. The system has been designed for being integrated within wider expert systems and actually it is part of the Therapy Advisor module within an expert system for the management of anemic patients.     

A framework for secure IT operations in an uncertain and changing environment

In this paper, a quantitative approach is proposed that addresses various decision making challenges within the IT security process of an organization. The approach serves as a framework that facilitates multiple applications to optimize the security of IT systems in different environmental settings. Addressing this problem is a critical challenge for almost all organizations and it still lacks a comprehensive and consistent quantitative treatment. The key question of the corresponding decision problem is which safeguards to select in order to achieve sufficient security. The proposed framework addresses this by establishing a generally applicable problem structure and by reusing existing knowledge in order to reduce implementation costs of the approach. Based on this foundation, efficient MILP models are applied to support the establishment of an effective IT security strategy. Depending on the knowledge an organization is able to provide, decisions take uncertainty and even dynamic aspects into account. As a result, deployed safeguards are robust against uncertain security threats and remain stable over several planning periods even if the system or the threat environment changes. This is a significant advancement that results in higher security in the short-term and lower costs in the mid- and long-term.     

A genetic fuzzy expert system for automatic question classification in a competitive learning environment

Intelligent tutoring systems are efficient tools to automatically adapt the learning process to the student’s progress and needs. One of the possible adaptations is to apply an adaptive question sequencing system, which matches the difficulty of the questions to the student’s knowledge level. In this context, it is important to correctly classify the questions to be presented to students according to their difficulty level. Many systems have been developed for estimating the difficulty of questions. However the variety in the application environments makes difficult to apply the existing solutions directly to other applications. Therefore, a specific solution has been designed in order to determine the difficulty level of open questions in an automatic and objective way. This solution can be applied to activities with special temporal and running features, as the contests developed through QUESTOURnament, which is a tool integrated into the e-learning platform Moodle. The proposed solution is a fuzzy expert system that uses a genetic algorithm in order to characterize each difficulty level. From the output of the algorithm, it defines the fuzzy rules that are used to classify the questions. Data registered from a competitive activity in a Telecommunications Engineering course have been used in order to validate the system against a group of experts. Results show that the system performs successfully. Therefore, it can be concluded that the system is able to do the questions classification labour in a competitive learning environment.     

Capturing and incorporating expert knowledge into machine learning models for quality prediction in manufacturing

Journal of Intelligent Manufacturing - Increasing digitalization enables the use of machine learning (ML) methods for analyzing and optimizing manufacturing processes. A main application of ML is...     

Distributed environment: A conceptual framework using objects

We present a conceptual framework for a distributed office system using concepts inherent to object-oriented formalism. The functions of the active object and the procedure servers are described. So are the attributes of the objects stored in these two servers. In order to endow the individual workstations with as much autonomy as possible, we develop a coarse-grained algorithm for active and procedural object distribution. An office model should have a high level of evolvability. To accommodate this phenomenon we devise a mechanism to enable the model to transit one state to another with a minimum level of perturbation.     

A conceptual framework for component context specification and representation in a metaCASE environment

A lack of design information can be a significant barrier for systems developers when developing and reusing a component. This paper tackles this problem by presenting and exemplifying the conceptual framework of component context and its hypertext representation in a metaCASE environment. It discusses the linking of contextual knowledge to components in systems analysis and design. The contextual knowledge includes the conceptual dependencies of component definition, reuse, and implementation, as well as the reasoning and rationale behind design and reuse processes. We also illustrate the hypertext approach to contextual knowledge representation that enables designers to express, record, explore, recognize, and negotiate their shared context within a metaCASE environment.

A network based mechanism for managing decomposable tasks via crowdsourcing

If a task is decomposable in a competitive crowdsourcing environment, thereby allowing collaboration, rational workers may choose to divide it into multiple sub-tasks among themselves. But as the winners are selected independently, there is no benefit out of this decomposition. We show that by the appropriate combination of such decomposed solutions, obtained from multiple workers, we can achieve a better solution for a given task. We present a network based mechanism to choose the best mixture of sub-tasks in a competitive environment for selecting collaborating winners.