Belief rule-base expert system with multilayer tree structure for complex problems modeling

Belief rule-base (BRB) expert system is one of recognized and fast-growing approaches in the areas of complex problems modeling. However, the conventional BRB has to suffer from the combinatorial explosion problem since the number of rules in BRB expands exponentially with the number of attributes in complex problems, although many alternative techniques have been looked at with the purpose of downsizing BRB. Motivated by this challenge, in this paper, multilayer tree structure (MTS) is introduced for the first time to define hierarchical BRB, also known as MTS-BRB. MTS- BRB is able to overcome the combinatorial explosion problem of the conventional BRB. Thereafter, the additional modeling, inferencing, and learning procedures are proposed to create a self-organized MTS-BRB expert system. To demonstrate the development process and benefits of the MTS-BRB expert system, case studies including benchmark classification datasets and research and development (R&D) project risk assessment have been done. The comparative results showed that, in terms of modelling effectiveness and/or prediction accuracy, MTS-BRB expert system surpasses various existing, as well as traditional fuzzy system-related and machine learning-related methodologie

Modern Information Systems

The development of modern information systems is a demanding task. New technologies and tools are designed, implemented and presented in the market on a daily bases. User needs change dramatically fast and the IT industry copes to reach the level of efficiency and adaptability for its systems in order to be competitive and up-to-date. Thus, the realization of modern information systems with great characteristics and functionalities implemented for specific areas of interest is a fact of our modern and demanding digital society and this is the main scope of this book. Therefore, this book aims to present a number of innovative and recently developed information systems. It is titled "Modern Information Systems" and includes 8 chapters. This book may assist researchers on studying the innovative functions of modern systems in various areas like health, telematics, knowledge management, etc. It can also assist young students in capturing the new research tendencies of the information systems' development

Effects of Gamification on Knowledge Acquisition: Aviation Weather Online Training

Due to the high popularity of gaming, researchers have begun to implement aspects of these games into real life (known as gamification). Motivation and engagement may be influenced by certain game mechanics and user types, which then could also impact learning. A gap still exists as to whether leaderboards and narratives impact motivation or engagement when implemented in a non-game context (i.e., an online training program). Studies indicate that aviation weather training for general aviation pilots is underdeveloped, particularly for NEXRAD. In considering the competitive/ goal-oriented nature of pilots, gamification elements such as Achievements and Stories could best motivate pilots-in-training through elevated engagement and motivation. Therefore, the purpose of the current study was to determine effectiveness of two types of gamification mechanics—narrative and leaderboard—on motivation, engagement, and learning in a Next Generation Radar (NEXRAD) online training program. In order to test this intervention, the study used a 2x2 between-subjects experimental design. It was hypothesized that there would be a significant effect of narrative presence and leaderboard presence on the multivariate dependent variable (engagement, motivation, and knowledge acquisition). Participants (n = 41) took part in an online NEXRAD training program—administered through Qualtrics—and received either the narrative intervention, leaderboard intervention, both, or neither. Participants were measured on their NEXRAD knowledge acquisition before and after the training. Following the training program, participants reported their motivation, engagement, and reactions to the training. Results from this study did not support the hypotheses. Gaps in this realm of training still exist and closing them is imperative in improving pilots’ understanding of the material and overall safety of flight

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

Naturalistic Study Examining the Data/Frame Model of Sensemaking by Assessing Experts in Complex, Time-Pressured Aviation Domains

Research on expert chess players, radiologists and landmine detection personnel suggests a use of cognitive frameworks, alternatively referred to as schemas, templates, scripts, frames and models, to effectively perceive, interpret, understand, recall, and anticipate information. These experts may use cognitive frameworks to capture past experience in ways that support rapid pattern recognition, adaptive responses and proactivity. The proposed research approach assumes that experienced pilots will similarly rely on cognitive frameworks to handle information and make sense of complex, fast-moving situations experienced in their information-dense environments. Predictions from Klein et al.\u27s (2006) Data/Frame Model of Sensemaking were used to evaluate event-based interview data collected from uninhabited aerial system (UAS) pilots and high performance military aircraft pilots (F-16 and UH-60 Black Hawk) in order to assess the methods with which these experts handle large amounts of critical information in their operations. This effort may benefit the sensemaking model, a model based largely on domains in which situations unfold over time and decision-making can be adapted, such as in information operations, nursing and fire fighting, by comparing its predictions with data collected from UAS pilots. The UAS operations domain, in particular, has characteristics that differ from those of domains on which the model is based because UAS pilot sensemaking must support decisions and continuous adjustments of an aircraft operating in a dynamic, potentially complex, and rapidly shifting environment from which the pilot is physically removed. The military aviation domain may be similar to studied domains that some decisions need to be made rapidly, and situations can change rapidly; nevertheless, as a new domain to the model, offers the potential to reveal new insights. Based on this research, recommendations are offered for aviation training and other information-rich domains, and evidence is provided that addresses the question, How much information can a person handle

Spinoff 1997: 25 Years of Reporting Down-to-Earth Benefits

The 25th annual issue of NASA's report on technology transfer and research and development (R&D) from its ten field centers is presented. The publication is divided into three sections. Section 1 comprises a summary of R&D over the last 25 years. Section 2 presents details of the mechanisms NASA uses to transfer technology to private industry as well as the assistance NASA provides in commercialization efforts. Section 3, which is the focal point of the publication, features success stories of manufacturers and entrepreneurs in developing commercial products and services that improve the economy and life in general

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

Game Assessment For Miltary Application

The primary purpose of conducting this research was to establish game assessment guidelines and characteristics for integrating elected characteristics of games into ongoing instructional approaches. The cost of repurposing commercial-off-the-shelf (COTS) games could offer a considerably lower cost alternative than the cost of creating a new instructional game developed for a specific instructional goal. The McNeese Game Assessment Tool (MGAT), created for the assessment of games in this usability study, is currently in a beta stage and was found to have potential for future game assessment. The overall assessment indicated that the tool was effective in analyzing game products for reuse potential and that the five instruments that make up the tool did meet the purpose of the design. However, the study also indicated that the instruments needed recommended modifications and further testing with a larger population group before the tool could be utilized. The assessment process identified in this study was a step forward in the area of game and simulation integration research. This study indicated that more research is needed in the area of instructional design to enhance instructional integration goals for future game, simulation and training applications