Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography

Neural Computing and Applications - In this paper, we present the novel Deep-MEG approach in which image-based representations of magnetoencephalography (MEG) data are combined with ensemble...     

A fuzzy queue-aware routing approach for wireless mesh networks

Recent advances in Wireless Mesh Networks (WMNs) have overcome the drawbacks of traditional wired and ad-hoc networks and now they are seen as a means of allowing last mile communications with quality level assurance in Future Multimedia Systems. However, new routing schemes are needed to provide end-to-end Quality of Service (QoS) and Quality of Experience (QoE) support for delay/loss/jitter-sensitive multimedia applications. The well-known OLSR (Optimized Link State Routing) protocol with ETX (Expected Transmission Count) metric brings many benefits to the path selection process, but has a drawback with regard to queue availability management, which reduces the system performance. This problem is caused when OLSR-EXT control messages are exchanged and the queues of mesh routers along the end-to-end communication path are overloaded. As a result, multimedia-related packets will suffer from loss/delay/jitter and the overall system performance will decrease. This paper proposes the Optimized Link State Routing-Fuzzy ETX Queue (OLSR-FEQ) protocol to overcome the limitations of OLSR-ETX regarding queue availability, QoS and QoE assurance. OLSR-FEQ optimizes network and user-based parameters by coordinating queue availability, QoS and fuzzy issues in the routing decision process as a way of allocating the best paths for multimedia applications. Performance evaluations were carried out with the Network Simulator (NS-2.34) to show the benefits of the proposed solution when compared with existing routing schemes, namely OLSR-ETX, OLSR-FLC, OLSR-MD and HWMP (IEEE 802.11s standard), regarding QoS (unsuccessful packet delivery and throughput) and QoE (PSNR, SSIM, VQM and MOS) parameters.     

An infrastructure for smart hospitals

In healthcare facilities most of the daily activities require strict coordination between clinicians, who often operate under heavy workloads and minimal workforce conditions in environments filled with increasingly complex technology. Ubiquitous Computing applications constitute a suitable solution for both reducing medical costs and improving patient safety by better supporting clinical processes. In this study we introduce an intelligent infrastructure for smart hospitals which implements basic services to optimize medical staff/patient interactions and grants ubiquitous and transparent access to clinical data stored in standard clinical databases. This infrastructure relies on the integration of Radio Frequency IDentification (RFID) and photosensor technologies to identify, locate and track clinicians and patients equipped with mobile devices and wearable RFID tags.     

Passive internet-based crane teleoperation with haptic aids

Crane operation is a challenging task, due to the combined problem of obstacle avoidance and load swing suppression in underactuated conditions. This paper presents a human-machine interface that increases the operator’s perception of a gantry crane’s workspace. With this aim, a virtual environment resembling the workspace is connected with a haptic device. This allows the user to receive not only visual but also tactile feedback, thus increasing maneuvering safety. Additionally, this capability is integrated in a teleoperation setup, adopting a passivity-based control approach that guarantees overall stability. This includes also the design of controllers by means of the IDA-PBC method. Experimental results carried out with a laboratory crane show its feasibility for internet-based teleoperation and demonstrate the improvements on the system performance.     

Comparative analysis of methods for determining the metabolic rate in order to provide a balance between man and the environment

The incorrect determination of metabolic rate can be linked to discrepancies between the model of the PMV (Predicted Mean Vote) and real thermal sensation collected in field studies. Aiming to improve the correlation of the PMV model and the real thermal sensation, this work established new values for the metabolic rate: one way being called “calculated” using Newton's Method and the other called "measured" using a metabolic analyzer. Welder's activities were evaluated, through the measurements of environmental and personal variables. New values of metabolic rate were determined for this activity. The values found for the calculated form and the measured one were, respectively, 178.63 and 145.46 W/m², different from the range provided by the table of ISO 8996 (2004) for this activity (75–125 W/m²). In order to verify which of the values of the metabolic rate was closer to the real thermal sensation of PMV, a linear regression was made between the PMV and the real thermal sensation in three ways: S × PMV_tabulated (R² = 0.1749), S × PMV_calculated (R ² = 0.7481) and S × PMV_measured (R² = 0.7854). It was found that the values measured by the instrument gave a higher coefficient of determination which was chosen for the correction of the table. The correction of the table provides a value of M_predicted, that is a value of metabolic rate that corrects the values provided by the tables of ISO 8996 (2004), by means of a correction coefficient. For the welder's activities in a metal-mechanics industry, tabulated values can be multiplied by the correction coefficient 1.4648 in order to minimize inaccuracies. The PMV_predicted, obtained through the M_predicted, when related to the actual thermal sensation, provides a coefficient of determination of 0.7511, thereby improving the model of the PMV.     

Interactional Order and Constructed Ways of Seeing with Touchless Imaging Systems in Surgery

While surgical practices are increasingly reliant on a range of digital imaging technologies, the ability for clinicians to interact and manipulate these digital representations in the operating theatre using traditional touch based interaction devices is constrained by the need to maintain sterility. To overcome these concerns with sterility, a number of researchers are have been developing ways of enabling interaction in the operating theatre using touchless interaction techniques such as gesture and voice to allow clinicians control of the systems. While there have been important technical strides in the area, there has been little in the way of understanding the use of these touchless systems in practice. With this in mind we present a touchless system developed for use during vascular surgery. We deployed the system in the endovascular suite of a large hospital for use in the context of real procedures. We present findings from a study of the system in use focusing on how, with touchless interaction, the visual resources were embedded and made meaningful in the collaborative practices of surgery. In particular we discuss the importance of direct and dynamic control of the images by the clinicians in the context of talk and in the context of other artefact use as well as the work performed by members of the clinical team to make themselves sensable by the system. We discuss the broader implications of these findings for how we think about the design, evaluation and use of these systems.     

Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.     

Straightforward modeling of dynamic I–V characteristics for microwave FETs

This work presents a straightforward approach aimed at modeling the dynamic I–V characteristics of microwave active solid‐state devices. The drain‐source current generator represents the most significant source of nonlinearity in a transistor and, therefore, its correct modeling is fundamental to predict accurately the current and voltage waveforms under large‐signal operation. The proposed approach relies on using a small set of low‐frequency time‐domain waveform measurements combined with numerical optimization‐based estimation of the nonlinear model parameters. The procedure is applied to a gallium nitride HEMT and silicon FinFET. The effectiveness of the modeling procedure in terms of prediction accuracy and generalization capability is demonstrated by validation of the extracted models under operating conditions different than the ones used for the parameters estimation. Good agreement between measurements and model simulations is achieved for both technologies and in both low‐ and high‐frequency range. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:109–116, 2014.     

Smoothing: A natural way to detect contour features

This work presents a dominant point detector. The angles of the contour are characterized through local entropy produced by a rotationally symmetric smoothing. The proposed scheme uses a punctual multi-scale approach in which only the candidates are analyzed in higher scales. To preserve the angle-entropy relationship in higher scales, we propose a smoothing kernel which presents special features that ensure its steepness in every scale. It is built from the sum of two Gaussians with different openings resembling center-surround receptive fields. The outputs of the proposed method are confronted to a ground-truth found in the literature, and to popular boundary based corner detectors that used the same set of images. Results reveal that the proposed detector performs extremely well.     

Binary and m-ary encoding in applications of tree-based genetic algorithms for QoS routing

Ubiquitous and Pervasive Computing (UPC) applications often have Quality of Service (QoS) requirements. These become constraints for the UPC network infrastructure. In this paper, we refer to Mobile ad Hoc Networks, one of the most important technologies supporting UPC, and investigate on Genetic Algorithms (GAs) for QoS routing. GAs are part of the soft computing paradigm and can solve the NP search of QoS routes with multiple constraints. We elaborate on tree-based GAs, which represent the set of paths from source to destination as a tree and encode them through the crossed junctions. While their most well-known applications use m-ary encoding representing single paths in the chromosomes, in this paper we discuss a binary encoding with the objective of improving the convergence speed. The binary encoding represents classes of paths in the chromosomes and allows local search on classes of paths. These classes are both collectively exhaustive and mutually exclusive. Simulation results compare convergence speed and scalability of GA applications with binary and m-ary encoding in networks with an increasing number of nodes and links per node. As the per-class processing is reason of additional computational cost, an hybrid GA application that uses both binary and m-ary encoding is introduced.