Urban spatial growth modeling using logistic regression and cellular automata: A case study of Hangzhou

Programming tasks are an important part of teaching computer programming as they foster students to develop essential programming skills and techniques through practice. The design of educational problems plays a crucial role in the extent to which the experiential knowledge is imparted to the learner both in terms of quality and quantity. Badly designed tasks have been known to put-off students from practicing programming. Hence, there is a need for carefully designed problems. Cellular Automata programming lends itself as a very suitable candidate among problems designed for programming practice. In this paper, we describe how various types of problems can be designed using concepts from Cellular Automata and discuss the features which make them good practice problems with regard to instructional pedagogy. We also present a case study on a Cellular Automata programming exercise used in a MOOC on Test Driven Development using JUnit, and discuss the automated evaluation of code submissions and the feedback about the reception of this exercise by participants in this course. Finally, we suggest two ideas to facilitate an easier approach of creating such programming exercises.

Download Full-text

Evolving One Dimensional Cellular Automata to Perform a Non-Trivial Collective Behavior Task: One Case Study

Lecture Notes in Computer Science - Computational Science — ICCS 2002 ◽

10.1007/3-540-46043-8_80 ◽

2002 ◽

pp. 793-802 ◽

Cited By ~ 3

Author(s):

F. Jiménez-Morales ◽

M. Mitchell ◽

J. P. Crutchfield

Keyword(s):

Cellular Automata ◽

Collective Behavior ◽

One Dimensional

Download Full-text

Using the Econometric Models for Identification of Risk Factors for Albanian Smes (Case Study: Smes of Gjirokastra Region)

WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS ◽

10.37394/23207.2021.18.17 ◽

2021 ◽

Vol 18 ◽

pp. 163-170

Author(s):

Lorenc Koçiu ◽

Kledian Kodra

Keyword(s):

Logistic Regression ◽

Statistical Models ◽

Logistic Regression Model ◽

Qualitative Data ◽

Linear Models ◽

Binary Logistic Regression ◽

Random Variable ◽

Econometric Models ◽

Binary Logistic Regression Model

Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sizedEnterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in theGjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likertscale was used to measure it. Finally, the data was processed through statistical software SPSS version 21,using the binary logistic regression model, which reveals the probability of occurrence of an event when allindependent variables are included. Logistic regression is an integral part of a category of statistical models,which are called General Linear Models. Logistic regression is used to analyze problems in which one or moreindependent variables interfere, which influences the dichotomous dependent variable. In such cases, the latteris seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identifyrisks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of thepaper, we conclude that Albanian SMEs can identify risk

Download Full-text