51 research outputs found

    Crew aiding and automation: A system concept for terminal area operations, and guidelines for automation design

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    This research and development program comprised two efforts: the development of guidelines for the design of automated systems, with particular emphasis on automation design that takes advantage of contextual information, and the concept-level design of a crew aiding system, the Terminal Area Navigation Decision Aiding Mediator (TANDAM). This concept outlines a system capable of organizing navigation and communication information and assisting the crew in executing the operations required in descent and approach. In service of this endeavor, problem definition activities were conducted that identified terminal area navigation and operational familiarization exercises addressing the terminal area navigation problem. Both airborne and ground-based (ATC) elements of aircraft control were extensively researched. The TANDAM system concept was then specified, and the crew interface and associated systems described. Additionally, three descent and approach scenarios were devised in order to illustrate the principal functions of the TANDAM system concept in relation to the crew, the aircraft, and ATC. A plan for the evaluation of the TANDAM system was established. The guidelines were developed based on reviews of relevant literature, and on experience gained in the design effort

    Quality of experience in affective pervasive environments

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    The confluence of miniaturised powerful devices, widespread communication networks and mass remote storage has caused a fundamental shift in the user interaction design paradigm. The distinction between system and user in pervasive environments is evolving into an increasingly integrated loop of interaction, raising a number of opportunities to provide enhanced and personalised experiences. We propose a platform, based on a smart architecture, to address the identified opportunities in pervasive computing. Smart systems aim at acting upon an environment for improving quality of experience: a subjective measure that has been defined as an emotional reaction to products or services. The inclusion of an emotional dimension allows us to measure individual user responses and deliver personalised services with the potential to influence experiences positively. The platform, Cloud2Bubble, leverages pervasive systems to aggregate user and environment data with the goal of addressing personal preferences and supra-functional requirements. This, combined with its societal implications, results in a set of design principles as a concrete fruition of design contractualism. In particular, this thesis describes: - a review of intelligent ubiquitous environments and relevant technologies, including a definition of user experience as a dynamic affective construct; - a specification of main components for personal data aggregation and service personalisation, without compromising privacy, security or usability; - the implementation of a software platform and a methodological procedure for its instantiation; - an evaluation of the developed platform and its benefits for urban mobility and public transport information systems; - a set of design principles for the design of ubiquitous systems, with an impact on individual experience and collective awareness. Cloud2Bubble contributes towards the development of affective intelligent ubiquitous systems with the potential to enhance user experience in pervasive environments. In addition, the platform aims at minimising the risk of user digital exposure while supporting collective action.Open Acces

    Artificial Intelligence Research Branch future plans

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    This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Aneesah: a novel methodology and algorithms for sustained dialogues and query refinement in natural language interfaces to databases

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    This thesis presents the research undertaken to develop a novel approach towards the development of a text-based Conversational Natural Language Interface to Databases, known as ANEESAH. Natural Language Interfaces to Databases (NLIDBs) are computer applications, which replace the requirement for an end user to commission a skilled programmer to query a database by using natural language. The aim of the proposed research is to investigate the use of a Natural Language Interface to Database (NLIDB) capable of conversing with users to automate the query formulation process for database information retrieval. Historical challenges and limitations have prevented the wider use of NLIDB applications in real-life environments. The challenges relevant to the scope of proposed research include the absence of flexible conversation between NLIDB applications and users, automated database query building from multiple dialogues and flexibility to sustain dialogues for information refinement. The areas of research explored include; NLIDBs, conversational agents (CAs), natural language processing (NLP) techniques, artificial intelligence (AI), knowledge engineering, and relational databases. Current NLIDBs do not have conversational abilities to sustain dialogues, especially with regards to information required for dynamic query formulation. A novel approach, ANEESAH is introduced to deal with these challenges. ANEESAH was developed to allow users to communicate using natural language to retrieve information from a relational database. ANEESAH can interact with the users conversationally and sustain dialogues to automate the query formulation and information refinement process. The research and development of ANEESAH steered the engineering of several novel NLIDB components such as a CA implemented NLIDB framework, a rule-based CA that combines pattern matching and sentence similarity techniques, algorithms to engage users in conversation and support sustained dialogues for information refinement. Additional components of the proposed framework include a novel SQL query engine for the dynamic formulation of queries to extract database information and perform querying the query operations to support the information refinement. Furthermore, a generic evaluation methodology combining subjective and objective measures was introduced to evaluate the implemented conversational NLIDB framework. Empirical end user evaluation was also used to validate the components of the implemented framework. The evaluation results demonstrated ANEESAH produced the desired database information for users over a set of test scenarios. The evaluation results also revealed that the proposed framework components can overcome the challenges of sustaining dialogues, information refinement and querying the query operations

    A Comprehensive Survey of Natural Language Generation Advances from the Perspective of Digital Deception

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    In recent years there has been substantial growth in the capabilities of systems designed to generate text that mimics the fluency and coherence of human language. From this, there has been considerable research aimed at examining the potential uses of these natural language generators (NLG) towards a wide number of tasks. The increasing capabilities of powerful text generators to mimic human writing convincingly raises the potential for deception and other forms of dangerous misuse. As these systems improve, and it becomes ever harder to distinguish between human-written and machine-generated text, malicious actors could leverage these powerful NLG systems to a wide variety of ends, including the creation of fake news and misinformation, the generation of fake online product reviews, or via chatbots as means of convincing users to divulge private information. In this paper, we provide an overview of the NLG field via the identification and examination of 119 survey-like papers focused on NLG research. From these identified papers, we outline a proposed high-level taxonomy of the central concepts that constitute NLG, including the methods used to develop generalised NLG systems, the means by which these systems are evaluated, and the popular NLG tasks and subtasks that exist. In turn, we provide an overview and discussion of each of these items with respect to current research and offer an examination of the potential roles of NLG in deception and detection systems to counteract these threats. Moreover, we discuss the broader challenges of NLG, including the risks of bias that are often exhibited by existing text generation systems. This work offers a broad overview of the field of NLG with respect to its potential for misuse, aiming to provide a high-level understanding of this rapidly developing area of research

    Parsing Inside-Out

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    The inside-outside probabilities are typically used for reestimating Probabilistic Context Free Grammars (PCFGs), just as the forward-backward probabilities are typically used for reestimating HMMs. I show several novel uses, including improving parser accuracy by matching parsing algorithms to evaluation criteria; speeding up DOP parsing by 500 times; and 30 times faster PCFG thresholding at a given accuracy level. I also give an elegant, state-of-the-art grammar formalism, which can be used to compute inside-outside probabilities; and a parser description formalism, which makes it easy to derive inside-outside formulas and many others.Comment: Ph.D. Thesis, 257 pages, 40 postscript figure

    Proceedings of the Air Transportation Management Workshop

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    The Air Transportation Management (ATM) Workshop was held 31 Jan. - 1 Feb. 1995 at NASA Ames Research Center. The purpose of the workshop was to develop an initial understanding of user concerns and requirements for future ATM capabilities and to initiate discussions of alternative means and technologies for achieving more effective ATM capabilities. The topics for the sessions were as follows: viewpoints of future ATM capabilities, user requirements, lessons learned, and technologies for ATM. In addition, two panel sessions discussed priorities for ATM, and potential contributions of NASA to ATM. The proceedings contain transcriptions of all sessions
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