Creating Intelligent Linking for Information Threading in Knowledge Networks

Informledge System (ILS) is a knowledge network with autonomous nodes and intelligent links that integrate and structure the pieces of knowledge. In this paper, we aim to put forward the link dynamics involved in intelligent processing of information in ILS. There has been advancement in knowledge management field which involve managing information in databases from a single domain. ILS works with information from multiple domains stored in distributed way in the autonomous nodes termed as Knowledge Network Node (KNN). Along with the concept under consideration, KNNs store the processed information linking concepts and processors leading to the appropriate processing of information.Comment: 5 Pages, 6 Figures, 2 Tables, India Conference (INDICON), 201

A situation-response model for intelligent pilot aiding

An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations

Virtual personal assistant

Abstract This report discusses ways in which new technology could be harnessed to create an intelligent Virtual Personal Assistant (VPA) with a focus on user-based information. It will look at examples of intelligent programs with natural language processing that are currently available, with different categories of support, and examine the potential usefulness of one specific piece of software as a VPA. This engages the ability to communicate socially through natural language processing, holding (and analysing) information within the context of the user. It is suggested that new technologies may soon make the idea of virtual personal assistants a reality. Experiments conducted on this system, combined with user testing, have provided evidence that a basic program with natural language processing algorithms in the form of a VPA, with basic natural language processing and the ability to function without the need for other type of human input (or programming) may already be viable

A conceptual framework for intelligent real-time information processing

By combining artificial intelligence concepts with the human information processing model of Rasmussen, a conceptual framework was developed for real time artificial intelligence systems which provides a foundation for system organization, control and validation. The approach is based on the description of system processing terms of an abstraction hierarchy of states of knowledge. The states of knowledge are organized along one dimension which corresponds to the extent to which the concepts are expressed in terms of the system inouts or in terms of the system response. Thus organized, the useful states form a generally triangular shape with the sensors and effectors forming the lower two vertices and the full evaluated set of courses of action the apex. Within the triangle boundaries are numerous processing paths which shortcut the detailed processing, by connecting incomplete levels of analysis to partially defined responses. Shortcuts at different levels of abstraction include reflexes, sensory motor control, rule based behavior, and satisficing. This approach was used in the design of a real time tactical decision aiding system, and in defining an intelligent aiding system for transport pilots

Do We Live In An Intelligent Universe?

This essay hypothesizes that the Universe contains a self-reproducing neural network of Black Holes with computational abilities—i.e., the Universe can “think”! It then rephrases the Final Anthropic Principle to state: “Intelligent information-processing must come into existence in each new Universe to assure the birth of intelligent successor universes”. Continued research into the theory of Early Universe and Black Hole information storage, processing and retrieval is recommended, as are observational searches for time-correlated electromagnetic and gravitational wave emission patterns from widely separated Black Hole transient events indicative of the existence of a universal inter-Black Hole faster-than-light communications network

Techniques and potential capabilities of multi-resolutional information (knowledge) processing

A concept of nested hierarchical (multi-resolutional, pyramidal) information (knowledge) processing is introduced for a variety of systems including data and/or knowledge bases, vision, control, and manufacturing systems, industrial automated robots, and (self-programmed) autonomous intelligent machines. A set of practical recommendations is presented using a case study of a multiresolutional object representation. It is demonstrated here that any intelligent module transforms (sometimes, irreversibly) the knowledge it deals with, and this tranformation affects the subsequent computation processes, e.g., those of decision and control. Several types of knowledge transformation are reviewed. Definite conditions are analyzed, satisfaction of which is required for organization and processing of redundant information (knowledge) in the multi-resolutional systems. Providing a definite degree of redundancy is one of these conditions

Intelligent information processing to support decision-making

Proyecto emergente centrado en el tratamiento inteligente de información procedente de diversas fuentes tales como micro-blogs, blogs, foros, portales especializados, etc. La finalidad es generar conocimiento a partir de la información semántica recuperada. Como resultado se podrán determinar las necesidades de los usuarios o mejorar la reputación de diferentes organizaciones. En este artículo se describen los problemas abordados, la hipótesis de trabajo, las tareas a realizar y los objetivos parciales alcanzados.This project is focused on intelligent information processing using different sources such as micro-blogs, blogs, forums, specialized websites, etc. The goal is to obtain new knowledge using semantic information. As a result we can determine user requirements or improve organizations reputation. This paper describes the problems faced, working hypothesis, tasks proposed and goals currently achieved

Expert system development for probabilistic load simulation

A knowledge based system LDEXPT using the intelligent data base paradigm was developed for the Composite Load Spectra (CLS) project to simulate the probabilistic loads of a space propulsion system. The knowledge base approach provides a systematic framework of organizing the load information and facilitates the coupling of the numerical processing and symbolic (information) processing. It provides an incremental development environment for building generic probabilistic load models and book keeping the associated load information. A large volume of load data is stored in the data base and can be retrieved and updated by a built-in data base management system. The data base system standardizes the data storage and retrieval procedures. It helps maintain data integrity and avoid data redundancy. The intelligent data base paradigm provides ways to build expert system rules for shallow and deep reasoning and thus provides expert knowledge to help users to obtain the required probabilistic load spectra

Event Recognition Using Signal Spectrograms in Long Pulse Experiments

As discharge duration increases, real-time complex analysis of the signal becomes more important. In this context, data acquisition and processing systems must provide models for designing experiments which use event oriented plasma control. One example of advanced data analysis is signal classification. The off-line statistical analysis of a large number of discharges provides information to develop algorithms for the determination of the plasma parameters from measurements of magnetohydrodinamic waves, for example, to detect density fluctuations induced by the Alfvén cascades using morphological patterns. The need to apply different algorithms to the signals and to address different processing algorithms using the previous results necessitates the use of an event-based experiment. The Intelligent Test and Measurement System platform is an example of architecture designed to implement distributed data acquisition and real-time processing systems. The processing algorithm sequence is modeled using an event-based paradigm. The adaptive capacity of this model is based on the logic defined by the use of state machines in SCXML. The Intelligent Test and Measurement System platform mixes a local multiprocessing model with a distributed deployment of services based on Jini