An empirical biometric-based study for user identification from different roles in the online game League of Legends

© 2017 CEUR-WS. All rights reserved. The popularity of computer games has grown exponentially in the last few years. In some games, players can choose to play with different characters from a pre-defined list, exercising distinct roles in each match. Although such games were created to promote competition and promote self-improvement, there are several recurrent issues. One that has received the least amount of attention is the problem of "account sharing" so far is when a player pays more experienced players to progressing in the game. The companies running those games tend to punish this behaviour, but this specific case is hard to identify. The aim of this study is to use a database of mouse and keystroke dynamics biometric data of League of Legends players as a case study to understand the specific characteristics a player will keep (or not) when playing different roles and distinct characters

The productive role of public infrastructure: A critical review of recent literature

The publication of two empirical articles by Aschauer in 1989 brought a renewed interest in the study of the productive role of public infrastructure. Since then, many empirical studies as well as a few surveys have been published not only in regional science journals but also in main stream economics journals. The interest in the subject and the controversy are both high, which constitute two major ingredients for our critical review of recent literature. Our purpose in this paper is to evaluate the recent contributions identifying approaches followed, results obtained, major shortcomings of the empirical evidence produced, areas of strong controversy and promising methodologies for future research.

An empirical analysis of Brazilian courts law documents using learning techniques

This paper describes a survey on investigating judicial data to find patterns and relations between crime attributes and corresponding decisions made by courts, aiming to find import directions that interpretation of the law might be taking. We have developed an initial methodology and experimentation to look for behaviour patterns to build judicial sentences in the scope of Brazilian criminal courts and achieved results related to important trends in decision making. Neural networks-based techniques were applied for classification and pattern recognition, based on Multi-Layer Perceptron and Radial-basis Functions, associated with data organisation techniques and behavioral modalities extractio

Are Voters Rationally Ignorant? An Empirical Study for Portuguese Local Elections

The application of the rational choice postulate to a political context invariably leads to the conclusion that most voters are ill informed when making the decision for whom to vote. In this paper, the authors do an empirical evaluation of the rational ignorance theory, based on the results of the 1997 Portuguese Local Elections. The results only partially sustain the hypothesis of rational ignorance, although it is also possible to identify several limitations that prevent the establishment of definite conclusions in this specific field.JEL Classification: H7 Key words: Voter’s Behaviour; Local Elections; Local Governments; Portugal.

Smart Rescue Drones to Find Snowslide Victims

In the approach of using autonomous robots to find victims on risk zones, there are specific ones that can reach the victims faster, the Unmanned Autonomous Vehicles (UAVs), better known as Drones. For this to happen, artificial intelligence algorithms were designed to teach them to search for the victims faster. On this paper, a simulation of three drones flying on different environments was made based on a Hidden Markov Models with KNN classifier as an artificial intelligence approach for the learning. The results revealed that for some environments, based on memory to store the paths and the classification of the objects, different hardware settings for the drones can be needed

Overconfidence and excess entry: a comparison between students and managers

Overconfidence can lead to excessive business entry. Here we replicate the pioneer experiment finding this nexus (Camerer and Lovallo 1999) and extend it in two major directions: (1) to consider managers as well as student subjects and (2) to explicitly take into account selected characteristics of the manager subjects. We find that managers are more prone to the nexus overconfidence-excess entry than students are. In particular, we find that left-handed, married, and emotionally aroused managers are more prone to excess entry.excess business entry, overconfidence, unrealistic optimism

Stock selection based on cluster analysis

We put forward a technique based on cluster analysis to group stocks in spot markets according to a risk-return criterion. We show how an informed investor will make money using the cluster analysis to select stocks of major companies from North and South America.