Doing what you love makes service official

When a person performs service, he or she gains much more than money. Service is in no way selfless. While performing service, a person can connect with all kinds of people and create lasting friendships and memories. Service gives people an opportunity to do things they love

Visually guided control of movement in the context of multimodal stimulation

Flight simulation has been almost exclusively concerned with simulating the motions of the aircraft. Physically distinct subsystems are often combined to simulate the varieties of aircraft motion. Visual display systems simulate the motion of the aircraft relative to remote objects and surfaces (e.g., other aircraft and the terrain). 'Motion platform' simulators recreate aircraft motion relative to the gravitoinertial vector (i.e., correlated rotation and tilt as opposed to the 'coordinated turn' in flight). 'Control loaders' attempt to simulate the resistance of the aerodynamic medium to aircraft motion. However, there are few operational systems that attempt to simulate the motion of the pilot relative to the aircraft and the gravitoinertial vector. The design and use of all simulators is limited by poor understanding of postural control in the aircraft and its effect on the perception and control of flight. Analysis of the perception and control of flight (real or simulated) must consider that: (1) the pilot is not rigidly attached to the aircraft; and (2) the pilot actively monitors and adjusts body orientation and configuration in the aircraft. It is argued that this more complete approach to flight simulation requires that multimodal perception be considered as the rule rather than the exception. Moreover, the necessity of multimodal perception is revealed by emphasizing the complementarity rather than the redundancy among perceptual systems. Finally, an outline is presented for an experiment to be conducted at NASA ARC. The experiment explicitly considers possible consequences of coordination between postural and vehicular control

DOP: Deep Optimistic Planning with Approximate Value Function Evaluation

Research on reinforcement learning has demonstrated promising results in manifold applications and domains. Still, efficiently learning effective robot behaviors is very difficult, due to unstructured scenarios, high uncertainties, and large state dimensionality (e.g. multi-agent systems or hyper-redundant robots). To alleviate this problem, we present DOP, a deep model-based reinforcement learning algorithm, which exploits action values to both (1) guide the exploration of the state space and (2) plan effective policies. Specifically, we exploit deep neural networks to learn Q-functions that are used to attack the curse of dimensionality during a Monte-Carlo tree search. Our algorithm, in fact, constructs upper confidence bounds on the learned value function to select actions optimistically. We implement and evaluate DOP on different scenarios: (1) a cooperative navigation problem, (2) a fetching task for a 7-DOF KUKA robot, and (3) a human-robot handover with a humanoid robot (both in simulation and real). The obtained results show the effectiveness of DOP in the chosen applications, where action values drive the exploration and reduce the computational demand of the planning process while achieving good performance

Q-CP: Learning Action Values for Cooperative Planning

Research on multi-robot systems has demonstrated promising results in manifold applications and domains. Still, efficiently learning an effective robot behaviors is very difficult, due to unstructured scenarios, high uncertainties, and large state dimensionality (e.g. hyper-redundant and groups of robot). To alleviate this problem, we present Q-CP a cooperative model-based reinforcement learning algorithm, which exploits action values to both (1) guide the exploration of the state space and (2) generate effective policies. Specifically, we exploit Q-learning to attack the curse-of-dimensionality in the iterations of a Monte-Carlo Tree Search. We implement and evaluate Q-CP on different stochastic cooperative (general-sum) games: (1) a simple cooperative navigation problem among 3 robots, (2) a cooperation scenario between a pair of KUKA YouBots performing hand-overs, and (3) a coordination task between two mobile robots entering a door. The obtained results show the effectiveness of Q-CP in the chosen applications, where action values drive the exploration and reduce the computational demand of the planning process while achieving good performance

Statistical analysis of the trigger algorithm for the NEMO project

We discuss the performances of a trigger implemented for the planned neutrino telescope NEMO. This trigger seems capable to discriminate between the signal and the strong background introduced by atmospheric muons and by the beta decay of the K-40 nuclei present in the water. The performances of the trigger, as evaluated on simulated data are analyzed in detail.Comment: Published in the Proceedings of the "I Workshop of Astronomy and Astrophysics for Students", Eds. N.R. Napolitano & M. Paolillo, Naples, 19-20 April 2006 (astro-ph/0701577

The effect of placebo and neurophysiological involvements

Placebo and placebo effect are important issues related to the drug therapy for clinical and scientific meanings. The rates of placebo may get as many as 50% for analgesic drugs in headache. The high answer to placebo brings questions on pathophysiology of headache. Answers may offer a new strategy in the implementation of trials and new insight in neurophysiology of headache. Current knowledge on placebo and placebo effect will be analysed and dicussed looking for new direction in headache field

A Preliminary Look at Early Educational Results of the Opportunity NYC - Family Rewards Program: A Research Note for Funders

Targeted toward very low-income families in six high-poverty New York City communities, Family Rewards offers cash payments tied to efforts and achievements in children's education, family preventive health care practices, and parents' employment. This paper reviews data on participants' receipt of rewards and offers preliminary estimates of the program's impacts on selected educational outcomes during the first year

Implementation of the trigger algorithm for the NEMO project

We describe the implementation of trigger algorithm specifically tailored on the characteristics of the neutrino telescope NEMO. Extensive testing against realistic simulations shows that, by making use of the uncorrelated nature of the noise produced mainly by the decay of K-40 beta-decay, this trigger is capable to discriminate among different types of muonic events.Comment: Published in the Proceedings of the "I Workshop of Astronomy and Astrophysics for Students", Eds. N.R. Napolitano & M. Paolillo, Naples, 19-20 April 2006 (astro-ph/0701577

The effects of environmental temperature changes on the EKG of the squirrel monkey /Saimiri sciureus/

Environmental temperature effects on EKG of squirrel monkey - animal study of heart rate and T-wave amplitud