Extracting human behavior patterns from DNS traffic

Author(s):  
Martín Panza ◽  
Diego Madariaga ◽  
Javier Bustos-Jiménez
1927 ◽  
Vol 21 (2) ◽  
pp. 255-269 ◽  
Author(s):  
George E. G. Catlin

Political science is not a sociological science of everything, a psychological study of all human behavior in all aspects, an anthropological inquiry into miscellaneous human customs, or a philosophy of history. Still less is it a study only of the state, which is a form of social organization resulting from one species of political action, or a study only of governments and the stage properties of law and administration.Politics is concerned with a field of human behavior characterized by the recurrence of specific behavior patterns. These peculiarly political patterns, however, must not be treated simply as a series of incidents in mere temporal juxtaposition. Human history must be studied as natural history and physical phenomena have been studied, that is to say, with a view to the detection of a recurrence in these patterns, and, hence, of a process in accordance with which, in given total situations, given detailed behavior patterns recur. These patterns are “lines of conduct” of an individual or group character, pursued in relation to other individuals or groups, as a matter of human method in dealing with such situations, which situations arise partly from the nature of the non-human environment, partly from the historical combination of human factors. The resultant specific action or behavior recurs with the recurrence of the stimuli of the approximately recurrent situation; for example, a certain general situation known as “the outbreak of hostilities” has certain specific consequences in changes of individual conduct toward members of a given nation, and the need of putting through a domestic policy against opposition brings into play the ever similar methods of party organization.


Home energy saving is very important to realize sustainable improvement. This can be achieved by designing a smart home system that provides a productive and cost-effective environment through optimization of different factors that will be explained in this paper. In this paper, an adaptive smart home system for optimal utilization of power will be designed. The system is based on genetic-fuzzy-neural networks technique, which can capture a human behavior patterns and use it to predict the user's mood. This technique will improve the intelligence of the smart home control to minimize the power losses.


2015 ◽  
Vol 6 (2) ◽  
pp. 1
Author(s):  
Amyr Borges Fortes Neto ◽  
Soraia Raupp Musse ◽  
Catherine Pelachaud

Latest advances in crowd simulation models that attempt to make agents with more realistic human-like behaviors explore heterogeneity of agent behaviors in order to achieve increased overall simulation realism. In general, human behavioral and psychological studies are used as base of knowledge and researchers try to simulate observed human behavior patterns within virtual agents. In this direction, this paper implements an emotion contagion model, within crowd simulation scenarios, in order to create realistic perception of agent behaviors on crowds.


Author(s):  
Alaa Alhamoud ◽  
Pei Xu ◽  
Frank Englert ◽  
Andreas Reinhardt ◽  
Philipp Scholl ◽  
...  

2021 ◽  
Vol 9 (1) ◽  
pp. 67-76
Author(s):  
Maryam Ghasemi ◽  
Abdolreza Roshani ◽  
Peshawa J. Muhammad Ali ◽  
Farhad F. Nia ◽  
Ehsan Nazemi ◽  
...  

In this paper, the implementation of artificial neural networks (multilayer perceptron [MLP] and radial base functions [RBF]) and the upgraded Markov chain model have been studied and performed to identify the human behavior patterns during rock, paper, and scissors game. The main motivation of this research is the design and construction of an intelligent robot with the ability to defeat a human opponent. MATLAB software has been used to implement intelligent algorithms. After implementing the algorithms, their effectiveness in detecting human behavior pattern has been investigated. To ensure the ideal performance of the implemented model, each player played with the desired algorithms in three different stages. The results showed that the percentage of winning computer with MLP and RBF neural networks and upgraded Markov model, on average in men and women is 59%, 76.66%, and 75%, respectively. Obtained results clearly indicate a very good performance of the RBF neural network and the upgraded Markov model in the mental modeling of the human opponent in the game of rock, paper, and scissors. In the end, the designed game has been employed in both hardware and software which include the Zana intelligent robot and a digital version with a graphical user interface design on the stand. To the best knowledge of the authors, the precision of novel presented method for determining human behavior patterns was the highest precision among all of the previous studies.


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