484,286 research outputs found

    Spatial ability, urban wayfinding and location-based services:a review and first results

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    Location-Based Services (LBS) are a new industry at the core of which are GISand spatial databases. With increasing mobility of individuals, the anticipatedavailability of broadband communications for mobile devices and growingvolumes of location specific information available in databases there willinevitably be an increase in demand for services providing location relatedinformation to people on the move. New Information and CommunicationTechnologies (NICTs) are providing enhanced possibilities for navigating ?smartcities?. Urban environments, meanwhile, have increasing spatial complexity.Navigating urban environments is becoming an important issue. The time is ripefor a re-appraisal of urban wayfinding. This paper critically reviews the currentLBS applications and raises a series of questions with regard to LBS for urbanwayfinding. Research is being carried out to measure individuals? spatialability/awareness and their degree of preference for using LBS in wayfinding. Themethodology includes both the use of questionnaires and a virtual reality CAVE.Presented here are the results of the questionnaire survey which indicate therelationships between individuals? spatial ability, use of NICTs and modepreference for receiving wayfinding cues. Also discussed are our future researchdirections on LBS, particular on issues of urban wayfinding using NICTs

    An improved generalized inverse algorithm for linear inequalities and its applications

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    Iterative, two-class algorithm for linear inequalitie

    Error Patterns

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    In coding theory the problem of decoding focuses on error vectors. In the simplest situation code words are (0,1)(0,1)-vectors, as are the received messages and the error vectors. Comparison of a received word with the code words yields a set of error vectors. In deciding on the original code word, usually the one for which the error vector has minimum Hamming weight is chosen. In this note some remarks are made on the problem of the elements 1 in the error vector, that may enable unique decoding, in case two or more code words have the same Hamming distance to the received message word, thus turning error detection into error correction. The essentially new aspect is that code words, message words and error vectors are put in one-one correspondence with graphs