Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations

Automatic Speech Recognition in Air Traffic Control: a Human Factors Perspective

The introduction of Automatic Speech Recognition (ASR) technology into the Air Traffic Control (ATC) system has the potential to improve overall safety and efficiency. However, because ASR technology is inherently a part of the man-machine interface between the user and the system, the human factors issues involved must be addressed. Here, some of the human factors problems are identified and related methods of investigation are presented. Research at M.I.T.'s Flight Transportation Laboratory is being conducted from a human factors perspective, focusing on intelligent parser design, presentation of feedback, error correction strategy design, and optimal choice of input modalities

Utilizing Bayesian Techniques for User Interface Intelligence

The purpose of this research is to study the injection of an intelligent agent into modern user interface technology. This agent is intended to manage the complex interactions between the software system and the user, thus making the complexities transparent to the user. The background study will show that while interesting and promising research exists in the domain of intelligent interface agents, very little research has been published that indicates true success in representing the uncertainty involved in predicting user intent. The interface agent architecture presented in this thesis will offer one solution for solving the problem using a newly developed Bayesian-based agent called the Intelligent Interface Agent (IIA). The proof of concept of this architecture has been implemented in an actual expert system, and this thesis presents the results of the implementation. The conclusions of this thesis will show the viability of this new agent architecture, as well as promising future research in examination of cognitive models, development of an intelligent interface agent interaction language, expansion of meta-level interface learning, and refinement of the PESKI user interface

In loco intellegentia: Human factors for the future European train driver

The European Rail Traffic Management System (ERTMS) represents a step change in technology for rail operations in Europe. It comprises track-to-train communications and intelligent on-board systems providing an unprecedented degree of support to the train driver. ERTMS is designed to improve safety, capacity and performance, as well as facilitating interoperability across the European rail network. In many ways, particularly from the human factors perspective, ERTMS has parallels with automation concepts in the aviation and automotive industries. Lessons learned from both these industries are that such a technology raises a number of human factors issues associated with train driving and operations. The interaction amongst intelligent agents throughout the system must be effectively coordinated to ensure that the strategic benefits of ERTMS are realised. This paper discusses the psychology behind some of these key issues, such as Mental Workload (MWL), interface design, user information requirements, transitions and migration and communications. Relevant experience in aviation and vehicle automation is drawn upon to give an overview of the human factors challenges facing the UK rail industry in implementing ERTMS technology. By anticipating and defining these challenges before the technology is implemented, it is hoped that a proactive and structured programme of research can be planned to meet them

Unconventional Cognitive Intelligent Robotic Control: Quantum Soft Computing Approach in Human Being Emotion Estimation -- QCOptKB Toolkit Application

Strategy of intelligent cognitive control systems based on quantum and soft computing presented. Quantum self-organization knowledge base synergetic effect extracted from intelligent fuzzy controllers imperfect knowledge bases described. That technology improved of robustness of intelligent cognitive control systems in hazard control situations described with the cognitive neuro-interface and different types of robot cooperation. Examples demonstrated the introduction of quantum fuzzy inference gate design as prepared programmable algorithmic solution for board embedded control systems. The possibility of neuro-interface application based on cognitive helmet with quantum fuzzy controller for driving of the vehicle is shown

Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

A software application to assist end-users of the high burst rate (HBR) link evaluation terminal (LET) for satellite communications is being developed. The HBR LET system developed at NASA Lewis Research Center is an element of the Advanced Communications Technology Satellite (ACTS) Project. The HBR LET is divided into seven major subsystems, each with its own expert. Programming scripts, test procedures defined by design engineers, set up the HBR LET system. These programming scripts are cryptic, hard to maintain and require a steep learning curve. These scripts were developed by the system engineers who will not be available for the end-users of the system. To increase end-user productivity a friendly interface needs to be added to the system. One possible solution is to provide the user with adequate documentation to perform the needed tasks. With the complexity of this system the vast amount of documentation needed would be overwhelming and the information would be hard to retrieve. With limited resources, maintenance is another reason for not using this form of documentation. An advanced form of interaction is being explored using current computer techniques. This application, which incorporates a combination of multimedia and artificial intelligence (AI) techniques to provided end-users with an intelligent interface to the HBR LET system, is comprised of an intelligent assistant, intelligent tutoring, and hypermedia documentation. The intelligent assistant and tutoring systems address the critical programming needs of the end-user

Automation and robotics technology for intelligent mining systems

The U.S. Bureau of Mines is approaching the problems of accidents and efficiency in the mining industry through the application of automation and robotics to mining systems. This technology can increase safety by removing workers from hazardous areas of the mines or from performing hazardous tasks. The short-term goal of the Automation and Robotics program is to develop technology that can be implemented in the form of an autonomous mining machine using current continuous mining machine equipment. In the longer term, the goal is to conduct research that will lead to new intelligent mining systems that capitalize on the capabilities of robotics. The Bureau of Mines Automation and Robotics program has been structured to produce the technology required for the short- and long-term goals. The short-term goal of application of automation and robotics to an existing mining machine, resulting in autonomous operation, is expected to be accomplished within five years. Key technology elements required for an autonomous continuous mining machine are well underway and include machine navigation systems, coal-rock interface detectors, machine condition monitoring, and intelligent computer systems. The Bureau of Mines program is described, including status of key technology elements for an autonomous continuous mining machine, the program schedule, and future work. Although the program is directed toward underground mining, much of the technology being developed may have applications for space systems or mining on the Moon or other planets

Cooperative analysis expert situation assessment research

For the past few decades, Rome Air Development Center (RADC) has been conducting research in Artificial Intelligence (AI). When the recent advances in hardware technology made many AI techniques practical, the Intelligence and Reconnaissance Directorate of RADC initiated an applications program entitled Knowledge Based Intelligence Systems (KBIS). The goal of the program is the development of a generic Intelligent Analyst System, an open machine with the framework for intelligence analysis, natural language processing, and man-machine interface techniques, needing only the specific problem domain knowledge to be operationally useful. The development of KBIS is described