An Evidential Approach to Query Interface Matching on the Deep Web

Matching query interfaces is a crucial step in data integration across multiple Web databases. The problem is closely related to schema matching that typically exploits different features of schemas. Relying on a particular feature of schemas is not suffcient. We propose an evidential approach to combining multiple matchers using Dempster-Shafer theory of evidence. First, our approach views the match results of an individual matcher as a source of evidence that provides a level of confidence on the validity of each candidate attribute correspondence. Second, it combines multiple sources of evidence to get a combined mass function that represents the overall level of confidence, taking into account the match results of different matchers. Our combination mechanism does not require use of weighing parameters, hence no setting and tuning of them is needed. Third, it selects the top k attribute correspondences of each source attribute from the target schema based on the combined mass function. Finally it uses some heuristics to resolve any conflicts between the attribute correspondences of different source attributes. Our experimental results show that our approach is highly accurate and effective.

A Corpus-Based Approach to Speech Enhancement from Nonstationary Noise

Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.

Design of a wideband conformal array antenna system with beamforming and null steering, for application in a DVB-T based passive radar

The use of radars in detecting low flying, small targets is being explored for several decades now. However radar with counter-stealth abilities namely the passive, multistatic, low frequency radars are in the focus recently. Passive radar that uses Digital Video Broadcast Terrestrial (DVB-T) signals as illuminator of opportunity is a major contender in this area. A DVB-T based passive radar requires the development of an antenna array that performs satisfactorily over the entire DVB-T band. At Fraunhofer FHR, there is currently a need for an array antenna to be designed for operation over the 450-900 MHz range with wideband beamforming and null steering capabilities. This would add to the ability of the passive radar in detecting covert targets and would improve the performance of the system. The array should require no mechanical adjustments to inter-element spacing to correspond to the DVB-T carrier frequency used for any particular measurement. Such an array would have an increased flexibility of operation in different environment or locations.

The design of such an array antenna and the applied techniques for wideband beamforming and null steering are presented in the thesis. The interaction between the inter-element spacing, the grating lobes and the mutual couplings had to be carefully studied and an optimal solution was to be reached at that meets all the specifications of the antenna array for wideband applications. Directional beams, nulls along interference directions, low sidelobe levels, polarization aspects and operation along a wide bandwidth of 450-900 MHz were some of the key considerations.

Transmit and receive filter design for OFDM based WLAN systems

We analyze the effect of different pulse shaping filters on the orthogonal frequency division multiplexing (OFDM) based wireless local area network (LAN) systems in this paper. In particular, the performances of the square root raised cosine (RRC) pulses with different rolloff factors are evaluated and compared. This work provides some guidances on how to choose RRC pulses in practical WLAN systems, e.g., the selection of rolloff factor, truncation length, oversampling rate, quantization levels, etc.

A laboratory based model study. Experimental observations of footings supported on soft clay reinforced with granular columns.

The inclusion of granular columns in soft clay deposits leads to improvements in bearing capacity and overall stiffness along with a reduction in consolidation settlement. Many laboratory investigations have focused on aspects of bearing capacity, but published data on settlement performance is limited. This paper reports on some interesting findings obtained from a laboratory model study in respect of these issues. In this investigation, 300 mm diameter by 400 mm long samples of soft kaolin clay were reinforced with single or multiple granular columns of various lengths using the displacement and replacement installation methods. The experimental findings revealed that, for the same area replacement ratio, limited settlement reduction was achieved for single long floating columns and end-bearing column groups. Marginal improvements in settlement performance were also achieved for columns installed by the displacement method. No settlement reduction was achieved for short single floating columns while short floating granular column groups produced increased settlements. These observations were verified using contact pressure measurements between the footing and column/surrounding clay.

Measurement-based Estimation of Wind Farm Inertia

The inertia of fixed-speed wind turbine generators (WTGs) helps to mitigate under-frequency transients, promotes fault ride-through and damps inter-area oscillations. It is therefore important to quantify this inertia. The authors use measured wind farm responses during under-frequency transients to provide this information. They discuss the extent of the data and the criteria used to select certain events for further analysis. The estimation of WTG inertia is based on a induction generator model. The basis of the model will be described. The manner in which the model is applied to estimate the inertia from the measured data is then explained. Finally, the implications of the results for power system operation are assessed.

Probable z'-band Ground-based Detection of the Secondary Eclipse of WASP-19b

We present the probable ground-based detection of the secondary eclipse of the transiting exoplanet WASP-19b. The observations were made in the Sloan z'-band using the ULTRACAM triple-beam CCD camera mounted on the NTT. The measurement shows a 1±0.2mmag eclipse depth, consistent with a dayside temperature of 2900K, matching previous predictions based on H- and K-band measurements. However, since this is based on a single observation, the eclipse depth - at the moment - is not particularly well constrained, and would benefit from additional observations at similar wavelengths. Our technique for the data reduction and analysis is described, along with our approach to dealing with systematic errors associated with ground-based secondary eclipse observations.

Context-Aware Body Area Networks (CABAN) for interactive smart environments:Interference characterization

Body Area Networks are unique in that the large-scale mobility of users allows the network itself to travel across a diverse range of operating domains or even to enter new and unknown environments. This network mobility is unlike node mobility in that sensed changes in inter-network interference level may be used to identify opportunities for intelligent inter-networking, for example, by merging or splitting from other networks, thus providing an extra degree of freedom. This paper introduces the concept of context-aware bodynets for interactive environments using inter-network interference sensing. New ideas are explored at both the physical and link layers with an investigation based on a 'smart' office environment. A series of carefully controlled measurements of the mesh interconnectivity both within and between an ambulatory body area network and a stationary desk-based network were performed using 2.45 GHz nodes. Received signal strength and carrier to interference ratio time series for selected node to node links are presented. The results provide an insight into the potential interference between the mobile and static networks and highlight the possibility for automatic identification of network merging and splitting opportunities. © 2010 ACM.

A sparse representation based fast detection method for surface defect detection of bottle caps

A practical machine-vision-based system is developed for fast detection of defects occurring on the surface of bottle caps. This system can be used to extract the circular region as the region of interests (ROI) from the surface of a bottle cap, and then use the circular region projection histogram (CRPH) as the matching features. We establish two dictionaries for the template and possible defect, respectively. Due to the requirements of high-speed production as well as detecting quality, a fast algorithm based on a sparse representation is proposed to speed up the searching. In the sparse representation, non-zero elements in the sparse factors indicate the defect's size and position. Experimental results in industrial trials show that the proposed method outperforms the orientation code method (OCM) and is able to produce promising results for detecting defects on the surface of bottle caps.

Solvent induced phase inversion-based in situ forming controlled release drug delivery implants

In situ forming (ISF) drug delivery implants have gained tremendous levels of interest over the last few decades. This is due to their wide range of biomedical applications such as in tissue engineering, cell encapsulation, microfluidics, bioengineering and drug delivery. Drug delivery implants forming upon injection has shown a range of advantages which include localized drug delivery, easy and less invasive application, sustained drug action, ability to tailor drug delivery, reduction in side effects associated with systemic delivery and also improved patient compliance and comfort. Different factors such as temperature, pH, ions, and exchange of solvents are involved in in situ implant formation. This review especially focuses on ISF implants that are formed through solvent induced phase inversion (SPI) technique. The article critically reviews and compares a wide range of polymers, solvents, and co-solvents that have been used in SPI implant preparation for control release of a range of drug molecules. Major drawback of SPI systems has been their high burst release. In this regard, the article exhaustively discusses factors that affect the burst release and different modification strategies that has been utilised to reduce the burst effect from these implants. Performance and controversial issues associated with the use of different biocompatible solvents in SPI systems is also discussed. Biodegradation, formulation stability, methods of characterisation and sterilisation techniques of SPI systems is comprehensively reviewed. Furthermore, the review also examines current SPI-based marketed products, their therapeutic application and associated clinical data. It also exemplifies the interest of multi-billion dollar pharma companies worldwide for further developments of SPI systems to a range of therapeutic applications. The authors believe that this will be the first review article that extensively investigate and discusses studies done to date on SPI systems. In so doing, this article will undoubtedly serve as an enlightening tool for the scientists working in the concerned area.

Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations

This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

Tuneable magneto-optical metamaterials based on photonic resonances in nickel nanorod arrays

We investigate the magneto-optical properties of a nanostructured metamaterial comprised of arrays of nickel nanorods embedded in an anodized aluminum oxide template. The rods are grown using a self-assembly bottom-up technique that provides a uniform, quasi-hexagonal array over a large area, quickly and at low cost. The tuneability of the magneto-optic response of the material is investigated by varying the nanorod dimensions: diameter, length and inter-rod spacing as well as the overall thickness of the template. It is demonstrated that the system acts as a sub-wavelength light trap with enhanced magneto-optical properties occurring at reflectivity minima corresponding to photonic resonances of the metamaterial. Changes in dimensions of the nickel rods on the order of tens of nanometers cause a spectral blue-shift in the peak magneto-optical response of 270 nm in the visible range. A plasmonic enhancement is also observed at lower wavelengths, which becomes increasingly damped with larger diameters and increased volume fraction of nickel inclusions. This type of structure has potential applications in high density magneto-optical data storage (up to 1011–12 rods per square inch), ultrafast magneto-plasmonic switching and optical components for telecommunications.

A bridge-monitoring tool based on bridge and vehicle accelerations

Previous research on damage detection based on the response of a structure to a moving load has reported decay in accuracy with increasing load speed. Using a 3D vehicle – bridge interaction model, this paper shows that the area under the filtered acceleration response of the bridge increases with increasing damage, even at highway load speeds. Once a datum reading is established, the area under subsequent readings can be monitored and compared with the baseline reading, if an increase is observed it may indicate the presence of damage. The sensitivity of the proposed approach to road roughness and noise is tested in several damage scenarios. The possibility of identifying damage in the bridge by analysing the acceleration response of the vehicle traversing it is also investigated. While vehicle acceleration is shown to be more sensitive to road roughness and noise and therefore less reliable than direct bridge measurements, damage is successfully identified in favourable scenarios.

Using entropy based mean shift filter and modified watershed transform for grain segmentation

Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper,we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice.However,due to the over-segmentation issue,this technique has experienced poor performance in various applications,such as inhomogeneous background and connected targets. To solve this problem,we present a combination of two classical techniques to handle this issue.In the first step,a mean shift filter is used to eliminate the inhomogeneous background, where entropy is used to be a converging criterion. Secondly,a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.

Partial least squares model for dynamic rating of overhead line in wind intensive areas based on field measurements

This paper presents a statistical model for the thermal behaviour of the line model based on lab tests and field measurements. This model is based on Partial Least Squares (PLS) multi regression and is used for the Dynamic Line Rating (DLR) in a wind intensive area. DLR provides extra capacity to the line, over the traditional seasonal static rating, which makes it possible to defer the need for reinforcement the existing network or building new lines. The proposed PLS model has a number of appealing features; the model is linear, so it is straightforward to use for predicting the line rating for future periods using the available weather forecast. Unlike the available physical models, the proposed model does not require any physical parameters of the line, which avoids the inaccuracies resulting from the errors and/or variations in these parameters. The developed model is compared with physical model, the Cigre model, and has shown very good accuracy in predicting the conductor temperature as well as in determining the line rating for future time periods.