Migrating from target-controlled infusion to closed-loop control in general anaesthesia

The target-controlled infusion (TCI) technique has been successfully and commercially used in clinical general anaesthesia with the intravenous anaesthetic agent propofol. The technique is based on a population pharmacokinetic model and is an open-loop control system. Closed-loop control requires a reliable and consistent signal for feedback utilisation. With all anaesthetic agents the somatosensory evoked potentials (SEP) have been shown to give increased latency as anaesthetic depth is increased. Using infusion rate and SEP response data from rats anaesthetised with propofol a mathematical model was derived to describe the anaesthetic process. This model was used as a design reference to develop a proportional integral (PI) closed-loop control system using SEP as the feedback measure. A serials of 10 trials were conducted to investigate the difference between continuous bolus injection and infusion, all under closed-loop control. The trials showed that the use of SEPs in closed-loop control of anaesthesia is feasible.     

Robotic execution of everyday tasks by means of external vision/force control

In this article, we present an integrated manipulation framework for a service robot, that allows to interact with articulated objects at home environments through the coupling of vision and force modalities. We consider a robot which is observing simultaneously his hand and the object to manipulate, by using an external camera (i.e. robot head). Task-oriented grasping algorithms (Proc of IEEE Int Conf on robotics and automation, pp 1794–1799, 2007) are used in order to plan a suitable grasp on the object according to the task to perform. A new vision/force coupling approach (Int Conf on advanced robotics, 2007), based on external control, is used in order to, first, guide the robot hand towards the grasp position and, second, perform the task taking into account external forces. The coupling between these two complementary sensor modalities provides the robot with robustness against uncertainties in models and positioning. A position-based visual servoing control law has been designed in order to continuously align the robot hand with respect to the object that is being manipulated, independently of camera position. This allows to freely move the camera while the task is being executed and makes this approach amenable to be integrated in current humanoid robots without the need of hand-eye calibration. Experimental results on a real robot interacting with different kind of doors are presented.     

Empirical studies to assess the understandability of data warehouse schemas using structural metrics

Data warehouses are powerful tools for making better and faster decisions in organizations where information is an asset of primary importance. Due to the complexity of data warehouses, metrics and procedures are required to continuously assure their quality. This article describes an empirical study and a replication aimed at investigating the use of structural metrics as indicators of the understandability, and by extension, the cognitive complexity of data warehouse schemas. More specifically, a four-step analysis is conducted: (1) check if individually and collectively, the considered metrics can be correlated with schema understandability using classical statistical techniques, (2) evaluate whether understandability can be predicted by case similarity using the case-based reasoning technique, (3) determine, for each level of understandability, the subsets of metrics that are important by means of a classification technique, and assess, by means of a probabilistic technique, the degree of participation of each metric in the understandability prediction. The results obtained show that although a linear model is a good approximation of the relation between structure and understandability, the associated coefficients are not significant enough. Additionally, classification analyses reveal respectively that prediction can be achieved by considering structure similarity, that extracted classification rules can be used to estimate the magnitude of understandability, and that some metrics such as the number of fact tables have more impact than others.

Knowledge representation for diagnosis of care problems through an expert system: Model of the auto-care deficit situations

The caregiver role strain is today an increasing problem because of the population aging; moreover, its diagnosis is highly difficult. In this article, we summarize the design of an Expert System for the diagnosis of this health problem. The Expert System Knowledge Base is composed by a set of production rules written in classic bi-valued logic and by a set of potential facts. In order to build this Knowledge Base it has been necessary to design previously a Model of the problem treatment. The Expert System Inference Engine uses Gröbner Bases and Normal Form to obtain the diagnosis from the information stored in the Knowledge Base. Furthermore, a Graphic User’s Interface has been implemented to make easier the access to the System by all kinds of users.     

Cluster validation in clustering‐based one‐class classification

Reconstruction‐based one‐class classification has shown to be very effective in a number of domains. This approach works by attempting to capture the underlying structure of the normal class, typically, by means of clusters of objects. It has the main disadvantage, however, that one has to indicate the number of clusters in advance, for this yields an efficient way of computing a clustering. In this paper, we introduce a new algorithm, OCKRA++, which achieves a better performance, by enhancing a clustering‐based one‐class ensemble classifier (OCKRA) with a cluster validity index that is used to set the best number of clusters during the classifier's training process. We have thoroughly tested OCKRA++ in a particular domain, namely masquerade detection. For this purpose, we have used the Windows‐Users and ‐Intruder simulation Logs data set repository, which contains 70 different masquerade data sets. We have found that OCKRA++ is currently the algorithm that achieves the best area under the curve, with a significant difference, in masquerade detection using the file system navigation approach.     

Using iterated local search for solving the flow‐shop problem: Parallelization,parametrization, and randomization issues

Iterated local search (ILS) is a powerful framework for developing efficient algorithms for the permutation flow‐shop problem (PFSP). These algorithms are relatively simple to implement and use very few parameters, which facilitates the associated fine‐tuning process. Therefore, they constitute an attractive solution for real‐life applications. In this paper, we discuss some parallelization, parametrization, and randomization issues related to ILS‐based algorithms for solving the PFSP. In particular, the following research questions are analyzed: (a) Is it possible to simplify even more the parameter setting in an ILS framework without affecting performance? (b) How do parallelized versions of these algorithms behave as we simultaneously vary the number of different runs and the computation time? (c) For a parallelized version of these algorithms, is it worthwhile to randomize the initial solution so that different starting points are considered? (d) Are these algorithms affected by the use of a “good‐quality” pseudorandom number generator? In this paper, we introduce the new ILS‐ESP (where ESP is efficient, simple, and parallelizable) algorithm that is specifically designed to take advantage of parallel computing, allowing us to obtain competitive results in “real time” for all tested instances. The ILS‐ESP also uses “natural” parameters, which simplifies the calibration process. An extensive set of computational experiments has been carried out in order to answer the aforementioned research questions.     

A Hierarchical Gravity Model with Spatial Correlation: Mathematical Formulation and Parameter Estimation

This study presents a hierarchical trip distribution gravity model that can accommodate various spatial correlation structures. It is formulated on the basis of the solution to an equivalent optimization problem, and its parameters are estimated using a sequential maximum likelihood procedure. We conclude that accounting for spatial correlation through a hierarchical structure incorporated into gravity-type trip distribution models significantly increases their explanatory and predictive powers and improves the results they generate for use in transportation system planning processes.     

A nanoscale parametric feedback oscillator

We describe and demonstrate a new oscillator topology, the parametric feedback oscillator (PFO). The PFO paradigm is applicable to a wide variety of nanoscale devices and opens the possibility of new classes of oscillators employing innovative frequency-determining elements, such as nanoelectromechanical systems (NEMS), facilitating integration with circuitry and system-size reduction. We show that the PFO topology can also improve nanoscale oscillator performance by circumventing detrimental effects that are otherwise imposed by the strong device nonlinearity in this size regime.     

Effects of various handling and storage conditions on stability of Treponema pallidum DNA in cerebrospinal fluid

Treponema pallidum DNA from even small numbers of organisms was detectable in cerebrospinal fluid (CSF) stored at room temperature or at 4 degrees C for several hours and in CSF subjected to three freeze-thaw cycles. These results suggest that negative PCR results for T. pallidum from patients diagnosed with T. pallidum invasion of the central nervous system are probably not due to the loss of target DNA prior to testing.