User testing and trustworthy electronic voting system design

In this contribution the user interface design for trustworthy system is presented. The principle of the Electronic Voting is discussed. The research aim was to discuss a users trust and its issues, which are connected to the design process of the prototype electronic voting system

Categorical variable segmentation model for software development effort estimation

This paper proposes a new software development effort estimation model. The new model's design is based on the function point analysis, categorical variable segmentation (CVS), and stepwise regression. The stepwise regression method is used for the creation of the unique estimation model of each segment. The estimation accuracy of the proposed model is compared to clustering-based models and the international function point user group model. It is shown that the proposed model increases estimation accuracy when compared to baseline methods: non-clustered functional point analysis and clustering-based models. The new CVS model achieves a significantly higher accuracy than the baseline methods. © 2013 IEEE.Faculty of Applied Informatics, Tomas Bata University in Zlin [RO30186021025/2102

Evaluating subset selection methods for use case points estimation

When the Use Case Points method is used for software effort estimation, users are faced with low model accuracy which impacts on its practical application. This study investigates the significance of using subset selection methods for the prediction accuracy of Multiple Linear Regression models, obtained by the stepwise approach. K-means, Spectral Clustering, the Gaussian Mixture Model and Moving Window are evaluated as appropriate subset selection techniques. The methods were evaluated according to several evaluation criteria and then statistically tested. Evaluation was performing on two independent datasets-which differ in project types and size. Both were cut by the hold-out method. If clustering were used, the training sets were clustered into 3 classes; and, for each of class, an independent regression model was created. These were later used for the prediction of testing sets. If Moving Window was used, then window of sizes 5, 10 and 15 were tested. The results show that clustering techniques decrease prediction errors significantly when compared to Use Case Points or moving windows methods. Spectral Clustering was selected as the best-performing solution, because it achieves a Sum of Squared Errors reduction of 32% for the first dataset, and 98% for the second dataset. The Mean Absolute Percentage Error is less than 1% for the second dataset for Spectral Clustering; 9% for moving window; and 27% for Use Case Points. When the first dataset is used, then prediction errors are significantly higher -53% for Spectral Clustering, but Use Case Points produces a 165% result. It can be concluded that this study proves subset selection techniques as a significant method for improving the prediction ability of linear regression models - which are used for software development effort prediction. It can also be concluded that the clustering method performs better than the moving window method

Internet Voting

This contribution focuses on the opportunity of using Internet voting as part of e-government services. Many countries have been researching the benefits of e-votingsolutions. Every country uses individual ideas to solve e-voting problems. Only few are thinking about Internet voting. This contribution describes the basic proposalsof Internet voting solution research and the web-based application advantages for the Internet voting

Key Factors Influencing Electronic Voting Design

This contribution focuses on the opportunity of the setting accurate level of the security and privacy in the electronic voting.

Using actors and use cases for software size estimation

Software size estimation represents a complex task, which is based on data analysis or on an algorithmic estimation approach. Software size estimation is a nontrivial task, which is important for software project planning and management. In this paper, a new method called Actors and Use Cases Size Estimation is proposed. The new method is based on the number of actors and use cases only. The method is based on stepwise regression and led to a very significant reduction in errors when estimating the size of software systems compared to Use Case Points-based meth-ods. The proposed method is independent of Use Case Points, which allows the elimination of the effect of the inaccurate determination of Use Case Points components, because such components are not used in the proposed method. © 2021 by the author. Licensee MDPI, Basel, Switzerland.Faculty of Applied Informatics, Tomas Bata University in Zli

Analysis and selection of a regression model for the Use Case Points method using a stepwise approach

This study investigates the significance of use case points (UCP) variables and the influence of the complexity of multiple linear regression models on software size estimation and accuracy. Stepwise multiple linear regression models and residual analysis were used to analyse the impact of model complexity. The impact of each variable was studied using correlation analysis. The estimated size of software depends mainly on the values of the weights of unadjusted UCP, which represent a number of use cases. Moreover, all other variables (unadjusted actors' weights, technical complexity factors, and environmental complexity factors) from the UCP method also have an impact on software size and therefore cannot be omitted from the regression model. The best performing model (Model D) contains an intercept, linear terms, and squared terms. The results of several evaluation measures show that this model's estimation ability is better than that of the other models tested. Model D also performs better when compared to the UCP model, whose Sum of Squared Error was 268,620 points on Dataset 1 and 87,055 on Dataset 2. Model D achieved a greater than 90% reduction in the Sum of Squared Errors compared to the Use Case Points method on Dataset 1 and a greater than 91% reduction on Dataset 2. The medians of the Sum of Squared Errors for both methods are significantly different at the 95% confidence level (p < 0.01), while the medians for Model D (312 and 37.26) are lower than Use Case Points (3134 and 3712) on Datasets 1 and 2, respectively. © 2016 The Author

Patients' perspective of the design of provider-patients electronic communication services

Information Delivery is one the most important tasks in healthcare practice. This article discusses patient's tasks and perspectives, which are then used to design a new Effective Electronic Methodology. The system design methods applicable to electronic communication in the healthcare sector are also described. The architecture and the methodology for the healthcare service portal are set out in the proposed system design. © 2014 by the authors; licensee MDPI, Basel, Switzerland

Requirements based estimation approach for system engineering projects

In this paper the requirements are used for the purpose of the estimation. Requirements are cluster according to their complexity. The new approach in the papers is based on requirements analysis. The complexity of the requirements is set and Total Requirements Points Value (TRP) is calculated. The Total Requirements Points are modified by the technical and environmental factors, which described the problem domain and the development team experiences. The Total Requirements point can be used as a coefficient for the system size. According this approach system-engineering project can be compared and priced

Process of transformation, Storage and data analysis for data mart enlargement

Creation of the information system is the complex and long process but it is only the first step in its existence. Most of information systems go through a certain development during its life cycle. Very often the users have defined the requests for the enlargement of the functionality and the volume of the displayed data. The process of the transformation, storage and analysis for data mart enlargement based on the users’ requests; concretely the data mart of the personal transport is presented in the paper. The expressions from the field of the Business Intelligence and the systems used for gaining data, data analysis or creation of forms and reports are explained