New model of electron free path in multiple layers for Monte Carlo simulation

1981 ◽  
Vol 39 (6) ◽  
pp. 512-514 ◽  
Author(s):  
Seiji Horiguchi ◽  
Masanori Suzuki ◽  
Toshio Kobayashi ◽  
Hideo Yoshino ◽  
Yutaka Sakakibara
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Free Path ◽  
New Model ◽  
Electron Free Path

Addendum: New model of electron free path in multiple layers for Monte Carlo simulation

1982 ◽  
Vol 53 (8) ◽  
pp. 5985-5985 ◽  
Author(s):  
R. J. Hawryluk ◽  
A. M. Hawryluk ◽  
H. I. Smith
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Free Path ◽  
New Model ◽  
Electron Free Path

scholarly journals A Novel Monte-Carlo Simulation-Based Model for Malware Detection (eRBCM)

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2881
Author(s):  
Muath Alrammal ◽  
Munir Naveed ◽  
Georgios Tsaramirsis
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Systems ◽  
Malware Detection ◽  
New Model ◽  
Malicious Activity ◽  
Model Based ◽  
Simulation Based ◽  
Computer Based ◽  
Reinforcement Model

The use of innovative and sophisticated malware definitions poses a serious threat to computer-based information systems. Such malware is adaptive to the existing security solutions and often works without detection. Once malware completes its malicious activity, it self-destructs and leaves no obvious signature for detection and forensic purposes. The detection of such sophisticated malware is very challenging and a non-trivial task because of the malware’s new patterns of exploiting vulnerabilities. Any security solutions require an equal level of sophistication to counter such attacks. In this paper, a novel reinforcement model based on Monte-Carlo simulation called eRBCM is explored to develop a security solution that can detect new and sophisticated network malware definitions. The new model is trained on several kinds of malware and can generalize the malware detection functionality. The model is evaluated using a benchmark set of malware. The results prove that eRBCM can identify a variety of malware with immense accuracy.

New model for Monte Carlo simulation of hot electrons in quantum wires

1994 ◽  
Vol 9 (5S) ◽  
pp. 958-960 ◽  
Author(s):  
H Momose ◽  
N Mori ◽  
K Taniguchi ◽  
C Hamaguchi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Quantum Wires ◽  
Hot Electrons ◽  
New Model

Calculating false cognates

Diachronica ◽  
2015 ◽  
Vol 32 (3) ◽  
pp. 331-364
Author(s):  
Marwan Kilani
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Word List ◽  
Theoretical Description ◽  
Test Case ◽  
Semantic Field ◽  
New Model ◽  
The Individual ◽  
Real Test

This paper presents an extension of Baxter & Manaster-Ramer’s (2000) approach to the problem of false cognates in the determination of relationships between languages. Their approach uses a Monte Carlo simulation to estimate how many lexical similarities we can expect to be due to chance between two lexical lists from different languages, and consequently how many are too many to be all false cognates. Although very efficient, their model has the shortcoming of being applicable only to simple lexical lists such as the Swadesh list, with one-to-one semantic correspondences between the individual terms. Here I present a new model that can be applied to any kind of word list, and can include comparisons between multiple terms sharing the same semantic field. After a theoretical description, a controlled test and a contra-test, I finally apply the method to a real test case, investigating the probability of relation between Pre-Greek, the nonIndo-European substrate of classical Greek, and Proto-Basque, Proto-Uralic and ‘Proto-Altaic’.

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