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Wyświetlanie 1-3 z 3
Tytuł:
Turing machine approach to runtime software adaptation
Autorzy:
Rudy, J.
Powiązania:
https://bibliotekanauki.pl/articles/952943.pdf
Data publikacji:
2014
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
runtime change
dynamic modification
computability theory
turing machines
Opis:
In this paper, the problem of applying changes to software at runtime is considered. The computability theory is used in order to develop a more general and programming-language-independent model of computation with support for runtime changes. Various types of runtime changes were defined in terms of computable functions and Turing machines. The properties of such functions and machines were used to prove that arbitrary runtime changes on Turing machines are impossible in general cases. A method of Turing machine decomposition into subtasks was presented and runtime changes were defined through transformations of the subtask graph. Requirements for the possible changes were considered with regard to the possibility of subtask execution during such changes. Finally, a runtime change model of computation was defined by extension of the Universal Turing Machine.
Źródło:
Computer Science; 2014, 15 (3); 293-310
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dynamic Turing Machine: model and properties for runtime code changes
Autorzy:
Rudy, J.
Powiązania:
https://bibliotekanauki.pl/articles/305728.pdf
Data publikacji:
2016
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
computability theory
models of computation
Turing machine
runtime code changes
Opis:
In this paper, a dynamic model of computation based on the Universal Turing Machine is proposed. This model is capable of applying runtime code modifications for 3-symbol deterministic Turing Machines at runtime and requires a decomposition of the simulated machine into parts called subtasks. The algorithm for performing runtime changes is considered, and the ability to apply runtime changes is studied through computer simulations. Theoretical properties of the proposed model, including computational power as well as time and space complexity, are studied and proven. Connections between the proposed model and Oracle Machines are discussed. Moreover, a possible method of implementation in real-life systems is proposed.
Źródło:
Computer Science; 2016, 17 (2); 187-224
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Lifelogging system based on averaged Hidden Markov Models: dangerous activities recognition for caregiver support
Autorzy:
Postawka, A.
Rudy, J.
Powiązania:
https://bibliotekanauki.pl/articles/305668.pdf
Data publikacji:
2018
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
lifelogging
abnormal human activity recognition
machine vision
Microsoft Kinect
Hidden Markov Models
Opis:
In this paper, a prototype lifelogging system for monitoring people with cognitive disabilities and elderly people as well as a method for the automatic detection of dangerous activities are presented. The system allows for the remote monitoring of observed people via an Internet website and respects the privacy of the people by displaying their silhouettes instead of their actual images. The application allows for the viewing of both real-time and historical data. The lifelogging data (skeleton coordinates) needed for posture and activity recognition are acquired using Microsoft Kinect 2.0. Several activities are marked as potentially dangerous and generate alarms sent to caregivers upon detection. Recognition models are developed using Averaged Hidden Markov Models with multiple learning sequences. Action recognition includes methods for dierentiating between normal and potentially dangerous activities (e.g., self-aggressive autistic behavior) using the same motion trajectory. Some activity recognition examples and results are presented.
Źródło:
Computer Science; 2018, 19 (3); 257-278
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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