scholarly journals Classical Models for Twin Data: The Case of Categorical Data

Author(s):  
Karl G. Jöreskog
2014 ◽  
Vol 13 (8) ◽  
pp. 4723-4728
Author(s):  
Pratiksha Saxena ◽  
Smt. Anjali

In this paper, an integrated simulation optimization model for the assignment problems is developed. An effective algorithm is developed to evaluate and analyze the back-end stored simulation results. This paper proposes simulation tool SIMASI (Simulation of assignment models) to simulate assignment models. SIMASI is a tool which simulates and computes the results of different assignment models. This tool is programmed in DOT.NET and is based on analytical approach to guide optimization strategy. Objective of this paper is to provide a user friendly simulation tool which gives optimized assignment model results. Simulation is carried out by providing the required values of matrix for resource and destination requirements and result is stored in the database for further comparison and study. Result is obtained in terms of the performance measurements of classical models of assignment system. This simulation tool is interfaced with an optimization procedure based on classical models of assignment system. The simulation results are obtained and analyzed rigorously with the help of numerical examples. 


2014 ◽  
Vol 24 (11) ◽  
pp. 2628-2641 ◽  
Author(s):  
Li-Fei CHEN ◽  
Gong-De GUO
Keyword(s):  

2020 ◽  
Vol 13 (5) ◽  
pp. 1020-1030
Author(s):  
Pradeep S. ◽  
Jagadish S. Kallimani

Background: With the advent of data analysis and machine learning, there is a growing impetus of analyzing and generating models on historic data. The data comes in numerous forms and shapes with an abundance of challenges. The most sorted form of data for analysis is the numerical data. With the plethora of algorithms and tools it is quite manageable to deal with such data. Another form of data is of categorical nature, which is subdivided into, ordinal (order wise) and nominal (number wise). This data can be broadly classified as Sequential and Non-Sequential. Sequential data analysis is easier to preprocess using algorithms. Objective: The challenge of applying machine learning algorithms on categorical data of nonsequential nature is dealt in this paper. Methods: Upon implementing several data analysis algorithms on such data, we end up getting a biased result, which makes it impossible to generate a reliable predictive model. In this paper, we will address this problem by walking through a handful of techniques which during our research helped us in dealing with a large categorical data of non-sequential nature. In subsequent sections, we will discuss the possible implementable solutions and shortfalls of these techniques. Results: The methods are applied to sample datasets available in public domain and the results with respect to accuracy of classification are satisfactory. Conclusion: The best pre-processing technique we observed in our research is one hot encoding, which facilitates breaking down the categorical features into binary and feeding it into an Algorithm to predict the outcome. The example that we took is not abstract but it is a real – time production services dataset, which had many complex variations of categorical features. Our Future work includes creating a robust model on such data and deploying it into industry standard applications.


Author(s):  
Christian Uva

Spectacle, myth, fable. These are the main categories that have traditionally defined Sergio Leone’s cinematic production, but it is necessary to underline how much they are fueled by a profound, layered political interest. Leone’s cinema bears witness to a critical outlook both on the subjects it showcases and on its representational means. Far from any militancy and escaping ideological classifications, Leone’s perspective is problematic and unreconciled: it is grounded in the coexistence of different elements in a state of perennial productive tension and instability. The adjective “political” takes on a deeper meaning when it is used to denote the director’s ability to narrate and interpret key aspects of Italian national identity and history. The abstract quality of his production relies on an original use of different genres, particularly sword-and-sandal and the Spaghetti Western, which allowed Leone to insert frequent symbolic references to both history and then-current events. On the stylistic level, his constant disobedience to classical models and his need to revolutionize forms were motivated by an authorial desire to make films politically, though still within a conception of cinema as an industrial spectacle.


Author(s):  
Christian D. Liddy

The political narrative of late medieval English towns is often reduced to the story of the gradual intensification of oligarchy, in which power was exercised and projected by an ever smaller ruling group over an increasingly subservient urban population. This book takes its inspiration not from English historiography, but from a more dynamic continental scholarship on towns in the southern Low Countries, Germany, and France. Its premise is that scholarly debate about urban oligarchy has obscured contemporary debate about urban citizenship. It identifies from the records of English towns a tradition of urban citizenship, which did not draw upon the intellectual legacy of classical models of the ‘citizen’. This was a vernacular citizenship, which was not peculiar to England, but which was present elsewhere in late medieval Europe. It was a citizenship that was defined and created through action. There were multiple, and divergent, ideas about citizenship, which encouraged townspeople to make demands, to assert rights, and to resist authority. This book exploits the rich archival sources of the five major towns in England—Bristol, Coventry, London, Norwich, and York—in order to present a new picture of town government and urban politics over three centuries. The power of urban governors was much more precarious than historians have imagined. Urban oligarchy could never prevail—whether ideologically or in practice—when there was never a single, fixed meaning of the citizen.


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