Evaluation of simulation systems suitable for teaching compiler construction courses

2020 ◽  
Vol 28 (3) ◽  
pp. 606-625
Author(s):  
Srećko Stamenković ◽  
Nenad Jovanović ◽  
Pinaki Chakraborty
Keyword(s):  
Compiler Construction ◽  
Simulation Systems

Design and analysis of auxiliary power supply simulation systems using the NEDIS language facilities

Cybernetics ◽  
1989 ◽  
Vol 24 (3) ◽  
pp. 315-319
Author(s):  
A. S. Zhernenko ◽  
O. A. Kokov ◽  
S. A. Trufanova ◽  
I. Z. Yakhimovich
Keyword(s):  
Power Supply ◽  
Auxiliary Power ◽  
Simulation Systems

Auto City: A System for Generating 3D Virtual Cities for Simulation Systems on GIS Maps

2009 ◽  
Vol 15 (1) ◽  
pp. 29-39 ◽  
Author(s):  
H. Haldun Göktaş ◽  
Abdullah Çavuşoğlu ◽  
Baha şen
Keyword(s):  
Simulation Systems

Statewide Simulation Systems: The Next Step for Anesthesiology?

2007 ◽  
Vol 25 (2) ◽  
pp. 271-282 ◽  
Author(s):  
Michael Seropian ◽  
Dawn Dillman ◽  
David Farris
Keyword(s):  
Simulation Systems

scholarly journals Collision avoidance during group evasive manoeuvres: a comparison of real versus simulated swarms with manipulated vision and surface wave detectors

2014 ◽  
Vol 281 (1788) ◽  
pp. 20140812 ◽  
Author(s):  
William L. Romey ◽  
Magenta M. Miller ◽  
Jose M. Vidal
Keyword(s):  
Surface Wave ◽  
Sensory Modality ◽  
Simulation Models ◽  
Emergent Properties ◽  
Control Groups ◽  
Group Attraction ◽  
Group Motion ◽  
Coordinate Group ◽  
Group Movements ◽  
Simulation Systems

Coordinated group motion has been studied extensively both in real systems (flocks, swarms and schools) and in simulations (self-propelled particle (SPP) models using attraction and repulsion rules). Rarely are attraction and repulsion rules manipulated, and the resulting emergent behaviours of real and simulation systems are compared. We compare swarms of sensory-deprived whirligig beetles with matching simulation models. Whirligigs live at the water's surface and coordinate their grouping using their eyes and antennae. We filmed groups of beetles in which antennae or eyes had been unilaterally obstructed and measured individual and group behaviours. We then developed and compared eight SPP simulation models. Eye-less beetles formed larger diameter resting groups than antenna-less or control groups. Antenna-less groups collided more often with each other during evasive group movements than did eye-less or control groups. Simulations of antenna-less individuals produced no difference from a control (or a slight decrease) in group diameter. Simulations of eye-less individuals produced an increase in group diameter. Our study is important in (i) differentiating between group attraction and repulsion rules, (ii) directly comparing emergent properties of real and simulated groups, and (iii) exploring a new sensory modality (surface wave detection) to coordinate group movement.

A visual environment for distributed simulation systems

1996 ◽  
Vol 25 (3) ◽  
pp. 13-22 ◽  
Author(s):  
James H. Graham ◽  
Adel S. Elmaghraby ◽  
Irfan Karachiwala ◽  
Hussam Soliman
Keyword(s):  
Distributed Simulation ◽  
Visual Environment ◽  
Simulation Systems

scholarly journals Dynamics and Temperature Simulation in Multi-Axis Milling

2008 ◽  
Vol 43 ◽  
pp. 89-96 ◽  
Author(s):  
Eduard Ungemach ◽  
Tobias Surmann ◽  
Andreas Zabel
Keyword(s):  
Surface Quality ◽  
Matrix Material ◽  
Ground Surface ◽  
Milling Process ◽  
Surface Structures ◽  
Dynamic Effects ◽  
Lightweight Construction ◽  
Surrounding Matrix ◽  
Simulation Systems ◽  
Very High

Lightweight extrusion profiles with reinforcement elements are promising news in the domain of lightweight construction. The machining of them suffers from several problems: Aside from the question of choosing a suitable tool, feed rate, and milling strategy, an excessive rise in temperature could lead to stress and even a distortion due to the differing thermal expansion of the reinforcement material and the surrounding matrix material. A simulation of the milling process could, in addition to force and collision calculations, recognize this case before manufacturing. For certain milling applications like seal surfaces, a certain roughness of the manufactured surface is necessary. In many other cases, a smooth surface of very high quality is desirable. Available simulation systems usually completely lack the simulation of dynamic effects, which have a great effect on the final surface quality, and therefore are not able to predict the resulting surface quality. In this paper simulation methods are presented that are capable of simulating the dynamic behavior of the tool in the milling process and the resulting flank and ground surface structures. Additionally, a fast temperature simulation for heterogeneous workpieces with reinforcement elements, which is based on the finite difference method and cellular automata, is introduced.

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