Working with Partial Systems

2019 ◽  
pp. 181-211
Author(s):  
Michael D. Reiter
Keyword(s):  
2020 ◽  
Vol 164 ◽  
pp. 03051 ◽  
Author(s):  
Kirill Kobzev

The most important link in the forging equipment is a crank mechanism. Their significant drawback is the unbalanced inertia forces of the moving masses of the crank mechanism, which cause vibration. The analysis of the phenomena occurring in the mechanism and the assessment of the technological process are based on the theory of chains, which allows analytically analyzing the dynamic characteristics of systems with a large number of degrees of freedom, based on the analysis of one structural element. The study of the process of force interaction inevitably comes down to the construction of a mathematical model of mechanisms, the formative movement of which leads to its formation. One of the partial systems makes an irregular programmed motion, meaning the crank drive mechanism. In addition, unwanted vibrations caused by kinematic excitation are superimposed on this drive. According to numerous papers on this topic, significant dynamic errors arise due to vibration accelerations. One of the main tasks in reducing the vibration activity and, accordingly, the level of acoustic emission of the process under study is to ensure the required law of motion of the instrument. On this basis, the study of the stability of formative movements is of particular importance. This question is complicated by the fact that in the processing, there is a change in the process parameters and, consequently, in the characteristics of the friction coupling. The latter circumstance presupposes the evolution of the system under study, and therefore the need for process control.


Author(s):  
Christian Beckhoff ◽  
Alexander Wold ◽  
Anders Fritzell ◽  
Dirk Koch ◽  
Jim Torresen
Keyword(s):  

Author(s):  
Jun-ichi Imai ◽  
◽  
Hiroyuki Shioya ◽  
Masahito Kurihara ◽  

Some mathematical models have been proposed for theoretical analyses of genetic algorithms (GAs). However, these works have limited their objects to a few kinds of GAs in order to formulate them accurately. In this paper, we regard a GA as an information source that generates input-output data. That is, we regard a population and its next population generated by the GA as input and output respectively. Then we model the GA by learning from these data. Since this method uses only the input-output relations of data and ignores interior structures, we can describe a variety of GAs in a common form, and analyze them from a new point of view. We use some mixture models for a representation of these input-output relations in this paper. By using a mixture model for modeling a GA, we can represent the GA system as a combination of some partial systems. In this paper, we treat two types of mixture models, and investigate how these models are effective for analyzing GAs through some numerical experiments.


Author(s):  
Pamela J. Shoemaker

One of the oldest social science theories applied to the study of communication, the gatekeeping approach emphasizes the movement of bits of information through channels, with an emphasis on decision points (gates) and decision-makers (gatekeepers). Forces on both sides of a gate can either help or hinder the information’s passage through a channel. The gatekeeping process shapes and produces various images of reality, not only because some bits of information are selected and others rejected, but because communication agents put information together in different ways. In addition, the timing and repetition of information can affect the prominence of events or topics and can influence the probability of future information diffusion. Gatekeeping was originally modeled as a series of linear processes within the mass media, but in the late 20th century the flow of information through the mass and social media began to interact. Information is now understood to flow among journalists, among social media users, and among agents of both types of media. All such communication agents are gatekeepers. In addition, we can study these networked interconnections as one level of analysis, with the supra-gatekeepers (such as Facebook or Twitter) adding their own gatekeeping processes over and beyond those of their own clients of the mass media. In addition to looking at various pairwise relationships between gatekeepers, gatekeeping theory should go beyond to instead consider the entire web of gatekeepers as a whole or system. A system is composed of elements (gatekeepers), interactions (relationships among them), and a goal or function. Multiple functions have been proposed by 20th-century scholars (such as socialization, entertainment, or surveillance) for the mass media, but scholars should now consider the function(s) of the gatekeeping system (mass and social media, as well as supra-gatekeepers) as a whole. Although each type of medium can be analyzed as its own system, such analysis would not facilitate new thinking about the various ways in which these partial systems affect one another and how the whole system functions beyond the simple addition of its parts.


2017 ◽  
Vol 80 (1) ◽  
pp. 65-89 ◽  
Author(s):  
Giuseppe Cavaliere ◽  
Luca De Angelis ◽  
Luca Fanelli

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