Elastic Translation Invariant Matching of Trajectories

We investigate techniques for analysis and retrieval of object trajectories. We assume that a trajectory is a sequence of two or three dimensional points. Trajectory datasets are very common in environmental applications, mobility experiments, video surveillance and are especially important for the discovery of certain biological patterns. Such kind of data usually contain a great amount of noise, that makes all previously used metrics fail. Therefore, here we formalize non-metric similarity functions based on the Longest Common Subsequence (LCSS), which are very robust to noise and furthermore provide an intuitive notion of similarity between trajectories by giving more weight to the similar portions of the sequences. Stretching of sequences in time is allowed, as well as global translating of the sequences in space. Efficient approximate algorithms that compute these similarity measures are also provided. We compare these new methods to the widely used Euclidean and Dynamic Time Warping distance functions (for real and synthetic data) and show the superiority of our approach, especially under the strong presence of noise. We prove a weaker version of the triangle inequality and employ it in an indexing structure to answer nearest neighbor queries. Finally, we present experimental results that validate the accuracy and efficiency of our approach.     

An electronic post market surveillance system for medical devices

An important issue in the health care sector is the collection of information about adverse incidents relative to medical devices and the exchange of this information among Health Care Institutions, Manufacturers and Competent Authorities. We present an Electronic Post Market Surveillance System, which solves in an efficient and secure way the above problem and it is compliant to the International Standards. The system consists of the PMS Server Application installed in the manufacturers/suppliers premises and the PMS Client Application installed in the Health Care Institutions. The PMS applications are used for the management of the PMS Reports and Responses with important features such as the user-friendly interfaces, interoperability and different implementations depending on the performance and cost requirements. The messages are in XML format and the security is based on public-private key cryptography. The system was evaluated in a systematic way by a variety of users, who were satisfied by the system functionality and efficiency.     

Design and Wind Tunnel Performance Testing of a New Omnidirectional Roof Vent

Low-slope roofs are subjected to potentially high levels of suction pressure as reported by Baskaran and Savage in 2003 in “Wind pressure measurements on full scale flat roofs.” Traditional roof assemblies are prone to failure when the low pressure on the roof surface instigates a transfer of forces to the roof membrane. Existing pressure-equalized roof systems use the power of the wind to transmit low pressure to the space immediately beneath the roof membrane, pulling the membrane down to the roof surface. The object of this study is the design of a wind vent which, when coupled with a single-ply roof membrane in a complete roof assembly, will successfully equalize low pressure throughout the entire field of the roof. The proposed wind vent differs from existing equalizer valves in its use of the Bernoulli effect to create low pressure. The vent is omnidirectional and contains no moving parts. Future study will be required to determine the tributary area of each vent and other roof system parameters.     

Detection of blocking artifacts in compressed video

A novel algorithm for the detection of artifacts in compressed video is described. The algorithm does not require access to the original video and therefore can be very useful in situations where quality assessment needs to be carried out at the receiver end. The proposed method is insensitive to other common video artifacts such as blurring for similar levels of objective distortion. The use of fast transformations in the frequency domain makes the method attractive for real-time applications     

Ultrafast semiconductor-based fiber laser sources

In this paper, a novel ring laser platform is presented that uses a single active element, a semiconductor optical amplifier (SOA), to provide both gain and gain modulation in the optical cavity. Gain modulation is achieved by an externally introduced optical pulsed signal. This signal periodically saturates the amplifier gain and forces the ring laser to mode lock. Using this laser platform, we demonstrate picosecond pulsetrain generation at repetition rates up to 40 GHz, either in single or multiwavelength operation mode. In particular, using rational harmonic mode locking, 2.5-ps pulses were obtained up to a 40-GHz repetition rate, while output pulses and output power were constant over a 20-nm tuning range. In addition, a multiwavelength optical signal was obtained using the same laser platform with the addition of a Fabry-Pe/spl acute/rot filter for comb generation. Multiwavelength oscillation is possible due to the broad gain spectrum of the SOA used and its inhomogeneous line broadening. To this end, 48 oscillating wavelengths were obtained at the laser output, with 50-GHz line spacing. Combining both modes of operation, it was possible to mode lock the oscillating multiwavelength signal and to obtain at the output ten wavelength channels, simultaneously mode locked at a 30-GHz repetition rate. The mode-locked channels are temporarily synchronized and exhibit almost identical spectral and time characteristics.     

Structural Periodic Measures for Time-Series Data

This work motivates the need for more flexible structural similarity measures between time-series sequences, which are based on the extraction of important periodic features. Specifically, we present non-parametric methods for accurate periodicity detection and we introduce new periodic distance measures for time-series sequences. We combine these new measures with an effective metric tree index structure for efficiently answering k-Nearest-Neighbor queries. The goal of these tools and techniques are to assist in detecting, monitoring and visualizing structural periodic changes. It is our belief that these methods can be directly applicable in the manufacturing industry for preventive maintenance and in the medical sciences for accurate classification and anomaly detection.

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Portable power production from methanol in an integrated thermoeletric/microreactor system

Catalytic self-ignition of methanol over platinum supported on anodized alumina in a microburner is demonstrated. The effects of air flow rate and air/methanol ratio on the system start-up time and steady state temperature have been studied. The air flow rate strongly affects the system start-up time. However, at the same flow rate, the start-up time is not affected by the air/methanol ratio over the range studied. Computational fluid dynamics simulations confirm these experimental findings. It is proposed that high flow rates and relatively lower fuel content can lead to attaining steady state faster with minimal fuel utilization. Transient axial temperature profiles showed that the hot spot of the reaction started at the inlet of the burner and did not shift downstream with time under most reaction conditions. The burner effective thermal conductivity was increased using copper thermal spreaders on the burner outer walls, allowing for thermally uniform walls. The uniform temperature profile allowed for optimal integration of the microburner with a thermoelectric device. The integrated microburner/thermoelectric device was shown to self-start from room temperature. The maximum power generated with the thermoelectric was 0.65 W and the maximum thermal efficiency was 1.1%.     

Transparency maximization methodology for haptic devices

In this paper, a design methodology is presented aimed at maximizing haptic device transparency, as seen from the user side. The methodology developed focuses on endpoint side fidelity, and optimizes not only mechanism dimensions, but also all relevant design parameters including relative position of endpoint desired path to device location, motor transmission ratios, and rotor inertias or motor sizes. The methodology is applied to a 5-degree-of-freedom (5-DOF) haptic device, part of a training medical urological simulator, and is applicable to any haptic mechanism. The transparency maximization is achieved using a multivariable optimization approach and an objective function including mechanism-induced parasitic torques/forces and motor and transmission parameters, as seen from the user side, under several constraints. The objective function and the kinematical and operational constraints are described and discussed. A new 5-DOF haptic mechanism is constructed according to the developed procedure, resulting in a substantially improved device with respect to an existing one, developed with a standard optimization method.     

10×30 GHz pulse train generation from semiconductor amplifierfiber ring laser

A multiwavelength, fiber ring laser source, is demonstrated. It generates 10 wavelength channels, simultaneously mode-locked and synchronized at 30 GHz, each producing 7-ps pulses. The mode-locking technique relies on the gain saturation of the semiconductor amplifier from an external optical pulse train to impose the simultaneous mode-locking of the 10 wavelengths     

Optimal search in Hough parameter hyperspace for estimation of complex motion in image sequences

The paper is a contribution to the theory of multiparameter motion estimation using the Hough transform technique and its main feature is the analytic development of closed-form solutions for the optimal estimation strategy. Motion estimation in image sequences using the Hough transform is reviewed. Various motion models are considered offering a more realistic portrayal of camera and scene motion compared with the purely translational models adopted by standardised video coding algorithms. Since the computational complexity arising from the use of such sophisticated models is prohibitive, standard optimisation techniques are used for the search of minima of the motion estimation error function in the Hough parameter hyperspace. In contrast to previously published work, second-order Taylor expansions of the error function are considered. By taking into account such second-order terms the optimal iterative step for a gradient search in the Hough parameter hyperspace is determined for all the motion models of interest. For a purely translational model it is demonstrated that the analysis provides a similar estimate to that of the well-known Netravali and Robbins algorithm. For more complex motion models it is shown that the computation of the optimal solution involves modest complexity.