Liver Trauma

The liver is the most frequently injured abdominal organ. Abdominal injuries occur in 31% of patients of polytrauma with 13 and 16% spleen and liver injuries respectively, and pelvic injuries in 28% of cases, making differential diagnosis between pelvic or intractable abdominal injury difficult.[1] Liver trauma is the most common cause of death after abdominal injury. The most common cause of liver injury is blunt abdominal trauma. Identification of serious intra-abdominal trauma is often challenging; many injuries may not manifest during the initial assessment and treatment period. Liver frequently injured following abdominal trauma and associated injuries contribute significantly to mortality and morbidity, and may mask the liver injury and causes delay in diagnosis. Management of hepatic injuries has evolved over the past 30 years. Prior to that time, a diagnostic peritoneal lavage (DPL) positive for blood, was an indication for exploratory celiotomy because of concern about ongoing hemorrhage and/or missed intra-abdominal injuries needing repair. The recognition that between 50 and 80 per cent of liver injuries stop bleeding spontaneously, coupled with better imaging of the injured liver by computed tomography (CT) and efficient ICU management, has led progressively to the acceptance of nonoperative management (NOM) with a resultant decrease in mortality rates

Real-time pursuit-evasion with humanoid robots

We consider a pursuit-evasion problem between humanoids. In our scenario, the pursuer enters the safety area of the evader headed for collision, while the latter executes a fast evasive motion. Control schemes are designed for both the pursuer and the evader. They are structurally identical, although the objectives are different: the pursuer tries to align its direction of motion with the line-of-sight to the evader, whereas the evader tries to move in a direction orthogonal to the line-of-sight to the pursuer. At the core of the control scheme is a maneuver planning module which makes use of closed- form expressions exclusively. This allows its use in a replanning framework, where each robot updates its motion plan upon completion of a step to account for the perceived motion of the other. Simulation and experimental results on NAO humanoids reveal an interesting asymptotic behavior which was predicted using unicycle as template models for trajectory generation

Real-time pursuit-evasion with humanoid robots

We consider a pursuit-evasion problem between humanoids. In our scenario, the pursuer enters the safety area of the evader headed for collision, while the latter executes a fast evasive motion. Control schemes are designed for both the pursuer and the evader. They are structurally identical, although the objectives are different: the pursuer tries to align its direction of motion with the line-of-sight to the evader, whereas the evader tries to move in a direction orthogonal to the line-of-sight to the pursuer. At the core of the control scheme is a maneuver planning module which makes use of closed-form expressions exclusively. This allows its use in a replanning framework, where each robot updates its motion plan upon completion of a step to account for the perceived motion of the other. Simulation and experimental results on NAO humanoids reveal an interesting asymptotic behavior which was predicted using unicycle as template models for trajectory generation

A model predictive control approach for the Partner Ballroom Dance Robot

A model predictive controller is developed for following the position of a human dancer in robot ballroom dancing. The control design uses a dynamic model of a dancer, based on a variant of the so-called 3D Linear Inverted Pendulum Mode that includes also the swing foot. This model serves as a basis for a Kalman predictor of the human motion during the single-support phase, while a simpler kinematic technique is used during the double-support phase. The output of the prediction filter enables to design a Model Predictive Control (MPC) law, by recursively solving on line and within a preview window a convex linear-quadratic optimization problem, constrained by differential kinematic bounds on robot commands. Two different control strategies, either at the velocity or at the acceleration level, are proposed and compared in simulations and in actual experiments. Accurate and reactive behaviors are obtained by the ballroom robot follower, confirming the benefit of the predictive/filtering nature of a MPC approach to handle uncertainty of human intentions and noisy signals

DAFNES: A distributed algorithm for network energy saving based on stress-centrality

We focus on the problem of reducing power consumption in backbone networks by putting in sleep mode IP links in order to save energy. We propose a new algorithm, called DAFNES, which relies on the stress centrality index in order to take the switch off decision. Differently from previous work in the literature, our algorithm requires neither the complete knowledge of the traffic matrix nor a careful tuning of the input parameters. Results, obtained over two realistic case studies, prove the efficiency and efficacy of our solution, with more than 50% of power saving while preserving Quality of Service constraints in terms of network connectivity, link congestion avoidance and increase of path lengths. Moreover, we show that the extra overhead required for running the distributed solution is limited compared to the amount of traffic exchanged in the network by the users. Finally, we face different implementation issues, including: (i) the reduction of the number of times our solution is applied, (ii) the evaluation of the algorithm performance on an emulated testbed