Design of robust model-based controllers via parametric programming

In this paper a method is presented for deriving the explicit robust model-based optimal control law for constrained linear dynamic systems. The controller is derived off-line via parametric programming before any actual process implementation takes place. The proposed control scheme guarantees feasible operation in the presence of bounded input uncertainties by (i) explicitly incorporating in the controller design stage a set of feasibility constraints and (ii) minimizing the nominal performance, or the expectation of the performance over the uncertainty space. An extension of the method to problems involving target point tracking in the presence of persistent disturbances is also discussed. The general concept is illustrated with two examples.     

Adaptive Head-to-Tail: Active Queue Management based on implicit congestion signals

Active Queue Management is a convenient way to administer the network load without increasing the complexity of end-user protocols. Current AQM techniques work in two ways; the router either drops some of its packets with a given probability or creates different queues with corresponding priorities. Head-to-Tail introduces a novel AQM approach: the packet rearrange scheme. Instead of dropping, HtT rearranges packets, moving them from the head of the queue to its tail. The additional queuing delay triggers a sending rate decrease and congestion events can be avoided. The HtT scheme avoids explicit packet drops and extensive retransmission delays. In this work, we detail the HtT algorithm and demonstrate when and how it outperforms current AQM implementations. We also approach analytically its impact on packet delay and conduct extensive simulations. Our experiments show that HtT achieves better results than Droptail and RED methods in terms of retransmitted packets and Goodput.     

An empirical investigation of Technology Readiness among medical staff based in Greek hospitals

Technology readiness (TR) represents an individual’s mental readiness to accept new technologies. Although the TR scale has been used in many studies, its application in the healthcare context is limited. This paper focuses on identifying the TR profiles of medical staff and to model preference TR variations with respect to computer use, computer knowledge and computer feature demands. The study reports results from a nationwide study conducted in Greece, during a three-year period, which sampled responses from 604 physicians and nurses working in 14 Greek hospitals. Exploratory Structural Equation Modelling analysis is used in order to confirm the structure of the Technology Readiness Index. The results confirm the five groups of the TR taxonomy. Statistical differences were found between classes in information and communication technology (ICT) knowledge, ICT feature demands, hours of use per week as well as ICT use performance, but not in the general use of ICT. The results facilitate comprehension of the factors, which influence the use of ICT by medical staff and, in addition, they convey important policy and managerial implications. In conclusion, medical staff should be treated according to its TR taxonomy classes in order to expedite the acceptance and use of an ICT system.     

The Wave & Probe Communication Mechanisms

This paper is motivated by the modifications recently suggested to enhance TCP performance over wireless channels. We argue that TCP end-to-end error-control mechanism lacks the functionality to respond appropriately in situations where errors vary in nature, frequency, or duration. As a result, this mechanism could, under some circumstances, yield zero throughput achievements at high energy-cost, or degrade throughput performance without conserving energy. This incompetent behavior with respect to the energy/throughput tradeoff puts in question TCP's suitability as a universal, reliable transport protocol of choice, especially for battery-powered mobile devices for which energy is a critical resource and congestion is not the exclusive cause of errors.We propose Wave and Probing communication and control mechanisms that permit end-to-end protocols to detect congestion without necessarily experiencing packet drops, to distinguish random and burst errors from congestion, and, as conditions vary, to rapidly adjust the transmission window upwards or downwards depending on the nature of the error. We report extensively on the performance of these new mechanisms to demonstrate their energy-conserving and high-throughput capabilities.     

Semantic content of motorcycle riders’ eye fixations during lane-splitting

A naturalistic field observation study is presented, exploring the experienced riders’ eye fixations on specific traffic objects and their relative s     

The ChaLearn gesture dataset (CGD 2011)

This paper describes the data used in the ChaLearn gesture challenges that took place in 2011/2012, whose results were discussed at the CVPR 2012 and ICPR 2012 conferences. The task can be described as: user-dependent, small vocabulary, fixed camera, one-shot-learning. The data include 54,000 hand and arm gestures recorded with an RGB-D \(\hbox {Kinect}^\mathrm{TM}\) camera. The data are organized into batches of 100 gestures pertaining to a small gesture vocabulary of 8–12 gestures, recorded by the same user. Short continuous sequences of 1–5 randomly selected gestures are recorded. We provide man-made annotations (temporal segmentation into individual gestures, alignment of RGB and depth images, and body part location) and a library of function to preprocess and automatically annotate data. We also provide a subset of batches in which the user’s horizontal position is randomly shifted or scaled. We report on the results of the challenge and distribute sample code to facilitate developing new solutions. The data, datacollection software and the gesture vocabularies are downloadable from http://gesture.chalearn.org. We set up a forum for researchers working on these data http://groups.google.com/group/gesturechallenge.     

A load-balanced parallel sorting algorithm for shared-nothing architectures

With the popularity of parallel database machines based on the shared-nothing architecture, it has become important to find external sorting algorithms which lead to a load-balanced computation, i.e., balanced execution, communication and output. If during the course of the sorting algorithm each processor is equally loaded, parallelism is fully exploited. Similarly, balanced communication will not congest the network traffic. Since sorting can be used to support a number of other relational operations (joins, duplicate elimination, building indexes etc.) data skew produced by sorting can further lead to execution skew at later stages of these operations. In this paper we present a load-balanced parallel sorting algorithm for shared-nothing architectures. It is a multiple-input multiple-output algorithm with four stages, based on a generalization of Batcher's odd-even merge. At each stage then keys are evenly distributed among thep processors (i.e., there is no final sequential merge phase) and the distribution of keys between stages ensures against network congestion. There is no assumption made on the key distribution and the algorithm performs equally well in the presence of duplicate keys. Hence our approach always guarantees its performance, as long asn is greater thanp ³, which is the case of interest for sorting large relations. In addition, processors can be added incrementally. Recommended by: Patrick Valduriez