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Wyświetlanie 1-2 z 2
Tytuł:
Ha in Sheta
Autorzy:
Ćwiek, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/1632252.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Warszawski. Wydawnictwa Uniwersytetu Warszawskiego
Tematy:
Hatshepsut
Deir el-Bahari
Ha
Sheta
enthronement
purification
Opis:
The coronation cycle in the Portico of the Birth in the temple of Deir el-Bahari includes a scene of purification of Hatshepsut by a god captioned as Ha in Sheta. This seemingly hapax toponym provides the key to a proper understanding of the highly symbolic meaning of the scene. The place name, composed of basic cosmographical hieroglyphs, has at the same time a spelling that refers to a vast semantic field of the notions of “mystery”, “secret”, “be hidden”, etc. It appears that the purification made by a god of the western desert in a “mysterious” place refers to the initiation of the female pharaoh into the secrets of the sun god, enabling her to fulfill her role as the provider of sustenance for humanity. The role of the god Ha as a protector against hunger, rooted in the Old Kingdom tradition and expressed also in the text of BD 178 in the Offering Chapel of Hatshepsut, is crucial in this respect.
Źródło:
Polish Archaeology in the Mediterranean; 2015, 24(2); 83-92
1234-5415
Pojawia się w:
Polish Archaeology in the Mediterranean
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Collision-free autonomous robot navigation in unknown environments utilizing PSO for path planning
Autorzy:
Krell, Evan
Sheta, Alaa
Balasubramanian, Arun Prassanth Ramaswamy
King, Scott A.
Powiązania:
https://bibliotekanauki.pl/articles/91555.pdf
Data publikacji:
2019
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
mobile robot
particle swarm optimization (PSO)
path planning
Opis:
The autonomous navigation of robots in unknown environments is a challenge since it needs the integration of a several subsystems to implement different functionality. It needs drawing a map of the environment, robot map localization, motion planning or path following, implementing the path in real-world, and many others; all have to be implemented simultaneously. Thus, the development of autonomous robot navigation (ARN) problem is essential for the growth of the robotics field of research. In this paper, we present a simulation of a swarm intelligence method is known as Particle Swarm Optimization (PSO) to develop an ARN system that can navigate in an unknown environment, reaching a pre-defined goal and become collision-free. The proposed system is built such that each subsystem manipulates a specific task which integrated to achieve the robot mission. PSO is used to optimize the robot path by providing several waypoints that minimize the robot traveling distance. The Gazebo simulator was used to test the response of the system under various envirvector representing a solution to the optimization problem.onmental conditions. The proposed ARN system maintained robust navigation and avoided the obstacles in different unknown environments. vector representing a solution to the optimization problem.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 4; 267-282
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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