We propose new features called the forward and backward variances of signature for on-line signature verification. In the proposed method, stable features of signature can be characterized by the forward and backward variances of signature. It is shown that signature can be verified by evaluating the difference of K-L coefficients of the forward and backward variances between the reference and signature to be verified. Experiments are performed on public signature database MCYT-100, consists of 5000 signatures from 100 people. The Equal Error Rate is 4.49%.

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Most of the research on social media is conducted to comprehend and to exploit the presence of public opinion in it. Meanwhile, there has been limited research that explores the engagement process and interaction results from social media accounts. Therefore, this study aims to map the interaction between government and society in social media in principal-agent context. Exploration made from tweets posted by @KemenDesa and citizens' tweets which are mentioning @KemenDesa dated from 1 October 2014 to 31 September 2017. The results give an idea of the engagement process and the content of the interaction so that the relationship between them in the principal-agent context can be mapped. In addition, the results of the analysis can also be used to evaluate the use of social media by public organizations and communities as an alternative medium to communicate.

In this research, the basic pattern of seasonal performances of soccer teams is investigated. We propose a clustering method to reveal the seasonal performance. In the proposed method, a new performance indicator called situational score line is used as a feature describing the seasonal performance. It consists of score line, opponent rating, and away rating. Using k-means, the features are clustered into four clusters. Cluster 1, which has a pattern of decreasing performance, is the basic pattern of Italian Serie A and German Bundesliga. Cluster 2 has a stable performance, which is mostly shown in English Premier League, Italian Serie A, and Spanish La Liga. Cluster 3 has the highest competitiveness and is one of the most common patterns in French Ligue 1 and Spanish La Liga. Finally, Cluster 4, which has a rising performance, is the basic pattern of the English Premier League.