Operation "Brother Sam" and the role of the United States in the 1964 coup d'etat in Brazil

openThe thesis describes the 1964 coup d’etat in Brazil analyzing its causes and consequences. It focuses than, on the role and the influence that the United States had in this event as well as on the strategies which they adopted to influence the course of events, particularly it focusses on the so-called “Operation Brother Sam”.The thesis describes the 1964 coup d’etat in Brazil analyzing its causes and consequences. It focuses than, on the role and the influence that the United States had in this event as well as on the strategies which they adopted to influence the course of events, particularly it focusses on the so-called “Operation Brother Sam”

N-gram GP: Early results and half-baked ideas

In this talk I present N-gram GP, a system for evolving linear GP programs using an EDA style system to update the probabilities of different 3-grams (triplets) of instructions. I then pick apart some of the evolved programs in an effort to better understand the properties of this approach and identify ways that it might be extended. Doing so reveals that there are frequently cases where the system needs two triples of the form ABC and ABD to solve the problem, but can only choose between them probabilistically in the EDA phase. I present the entirely untested idea of creating a new pseudo-instruction that is a duplicate of a key instruction. This could potentially allow the system to learn, for example, that AB is always followed by C, while AB\u27 is always followed by D

Brain-Computer Interfaces for Detection and Localization of Targets in Aerial Images

Objective. The N2pc event-related potential (ERP) appears on the opposite side of the scalp with respect to the visual hemisphere where an object of interest is located. We explored the feasibility of using it to extract information on the spatial location of targets in aerial images shown by means of a rapid serial visual presentation (RSVP) protocol using single-Trial classification. Methods. Images were shown to 11 participants at a presentation rate of 5 Hz while recording electroencephalographic signals. With the resulting ERPs, we trained linear classifiers for single-Trial detection of target presence and location. We analyzed the classifiers' decisions and their raw output scores on independent test sets as well as the averages and voltage distributions of the ERPs. Results. The N2pc is elicited in RSVP presentation of complex images and can be recognized in single trials (the median area under the receiver operating characteristic curve was 0.76 for left versus right classification). Moreover, the peak amplitude of this ERP correlates with the horizontal position of the target within an image. The N2pc varies significantly depending on handedness, and these differences can be used for discriminating participants in terms of their preferred hand. Conclusion and Significance. The N2pc is elicited during RSVP presentation of real complex images and contains analogue information that can be used to roughly infer the horizontal position of targets. Furthermore, differences in the N2pc due to handedness should be taken into account when creating collaborative brain-computer interfaces

Group Augmentation in Realistic Visual-Search Decisions via a Hybrid Brain-Computer Interface.

Groups have increased sensing and cognition capabilities that typically allow them to make better decisions. However, factors such as communication biases and time constraints can lead to less-than-optimal group decisions. In this study, we use a hybrid Brain-Computer Interface (hBCI) to improve the performance of groups undertaking a realistic visual-search task. Our hBCI extracts neural information from EEG signals and combines it with response times to build an estimate of the decision confidence. This is used to weigh individual responses, resulting in improved group decisions. We compare the performance of hBCI-assisted groups with the performance of non-BCI groups using standard majority voting, and non-BCI groups using weighted voting based on reported decision confidence. We also investigate the impact on group performance of a computer-mediated form of communication between members. Results across three experiments suggest that the hBCI provides significant advantages over non-BCI decision methods in all cases. We also found that our form of communication increases individual error rates by almost 50% compared to non-communicating observers, which also results in worse group performance. Communication also makes reported confidence uncorrelated with the decision correctness, thereby nullifying its value in weighing votes. In summary, best decisions are achieved by hBCI-assisted, non-communicating groups

Enhancement of group perception via a collaborative brain-computer interface

Objective: We aimed at improving group performance in a challenging visual search task via a hybrid collaborative brain-computer interface (cBCI). Methods: Ten participants individually undertook a visual search task where a display was presented for 250 ms, and they had to decide whether a target was present or not. Local temporal correlation common spatial pattern (LTCCSP) was used to extract neural features from response-and stimulus-locked EEG epochs. The resulting feature vectorswere extended by including response times and features extracted from eye movements. A classifier was trained to estimate the confidence of each group member. cBCI-assisted group decisions were then obtained using a confidence-weighted majority vote. Results: Participants were combined in groups of different sizes to assess the performance of the cBCI. Results show that LTCCSP neural features, response times, and eye movement features significantly improve the accuracy of the cBCI over what we achieved with previous systems. For most group sizes, our hybrid cBCI yields group decisions that are significantly better than majority-based group decisions. Conclusion: The visual task considered here was much harder than a task we used in previous research. However, thanks to a range of technological enhancements, our cBCI has delivered a significant improvement over group decisions made by a standard majority vote. Significance: With previous cBCIs, groups may perform better than single non-BCI users. Here, cBCI-assisted groups are more accurate than identically sized non-BCI groups. This paves the way to a variety of real-world applications of cBCIs where reducing decision errors is vital

Free Lunch and Ride Sharing: A New Business Model for Winter Sport Resorts

This paper proposes a new business model for winter sport resorts, by adopting a cluster approach. By following the guidelines for design research, we propose a new online service, which combines the notions of ridesharing and rebate. Ridesharing is often seen as a solution to reduce the number of cars in winter sport resorts, whereas the delivery of discount coupon has been used to increase the amount of customers. Hence, we propose to reward skiers that share a ride with coupons of complementary activities in the winter sport resorts. We describe our proposed service by describing its customer journey. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Brain–Computer Interfaces for Human Augmentation

Editorial for the Special Issue Brain-Computer Interfaces for Human Augmentatio