Reconfigurable Battery Techniques and Systems: A Survey

Battery packs with a large number of battery cells are becoming more and more widely adopted in electronic systems, such as robotics, renewable energy systems, energy storage in smart grids, and electronic vehicles. Therefore, a well-designed battery pack is essential for battery applications. In the literature, the majority of research in battery pack design focuses on battery management system, safety circuit, and cell-balancing strategies. Recently, the reconfigurable battery pack design has gained increasing attentions as a promising solution to solve the problems existing in the conventional battery packs and associated battery management systems, such as low energy efficiency, short pack lifespan, safety issues, and low reliability. One of the most prominent features of reconfigurable battery packs is that the battery cell topology can be dynamically reconfigured in the real-time fashion based on the current condition (in terms of the state of charge and the state of health) of battery cells. So far, there are several reconfigurable battery schemes having been proposed and validated in the literature, all sharing the advantage of cell topology reconfiguration that ensures balanced cell states during charging and discharging, meanwhile providing strong fault tolerance ability. This survey is undertaken with the intent of identifying the state-of-the-art technologies of reconfigurable battery as well as providing review on related technologies and insight on future research in this emerging area

Discriminative preprocessing of speech : towards improving biometric authentication

Im Rahmen des "SecurePhone-Projektes" wurde ein multimodales System zur Benutzerauthentifizierung entwickelt, das auf ein PDA implementiert wurde. Bei der vollzogenen Erweiterung dieses Systems wurde der Möglichkeit nachgegangen, die Benutzerauthentifizierung durch eine auf biometrischen Parametern (E.: "feature enhancement") basierende Unterscheidung zwischen Sprechern sowie durch eine Kombination mehrerer Parameter zu verbessern. In der vorliegenden Dissertation wird ein allgemeines Bezugssystem zur Verbesserung der Parameter präsentiert, das ein mehrschichtiges neuronales Netz (E.: "MLP: multilayer perceptron") benutzt, um zu einer optimalen Sprecherdiskrimination zu gelangen. In einem ersten Schritt wird beim Trainieren des MLPs eine Teilmenge der Sprecher (Sprecherbasis) berücksichtigt, um die zugrundeliegenden Charakteristika des vorhandenen akustischen Parameterraums darzustellen. Am Ende eines zweiten Schrittes steht die Erkenntnis, dass die Größe der verwendeten Sprecherbasis die Leistungsfähigkeit eines Sprechererkennungssystems entscheidend beeinflussen kann. Ein dritter Schritt führt zur Feststellung, dass sich die Selektion der Sprecherbasis ebenfalls auf die Leistungsfähigkeit des Systems auswirken kann. Aufgrund dieser Beobachtung wird eine automatische Selektionsmethode für die Sprecher auf der Basis des maximalen Durchschnittswertes der Zwischenklassenvariation (between-class variance) vorgeschlagen. Unter Rückgriff auf verschiedene sprachliche Produktionssituationen (Sprachproduktion mit und ohne Hintergrundgeräusche; Sprachproduktion beim Telefonieren) wird gezeigt, dass diese Methode die Leistungsfähigkeit des Erkennungssystems verbessern kann. Auf der Grundlage dieser Ergebnisse wird erwartet, dass sich die hier für die Sprechererkennung verwendete Methode auch für andere biometrische Modalitäten als sinnvoll erweist. Zusätzlich wird in der vorliegenden Dissertation eine alternative Parameterrepräsentation vorgeschlagen, die aus der sog. "Sprecher-Stimme-Signatur" (E.: "SVS: speaker voice signature") abgeleitet wird. Die SVS besteht aus Trajektorien in einem Kohonennetz (E.: "SOM: self-organising map"), das den akustischen Raum repräsentiert. Als weiteres Ergebnis der Arbeit erweist sich diese Parameterrepräsentation als Ergänzung zu dem zugrundeliegenden Parameterset. Deshalb liegt eine Kombination beider Parametersets im Sinne einer Verbesserung der Leistungsfähigkeit des Erkennungssystems nahe. Am Ende der Arbeit sind schließlich einige potentielle Erweiterungsmöglichkeiten zu den vorgestellten Methoden zu finden. Schlüsselwörter: Feature Enhancement, MLP, SOM, Sprecher-Basis-Selektion, SprechererkennungIn the context of the SecurePhone project, a multimodal user authentication system was developed for implementation on a PDA. Extending this system, we investigate biometric feature enhancement and multi-feature fusion with the aim of improving user authentication accuracy. In this dissertation, a general framework for feature enhancement is proposed which uses a multilayer perceptron (MLP) to achieve optimal speaker discrimination. First, to train this MLP a subset of speakers (speaker basis) is used to represent the underlying characteristics of the given acoustic feature space. Second, the size of the speaker basis is found to be among the crucial factors affecting the performance of a speaker recognition system. Third, it is found that the selection of the speaker basis can also influence system performance. Based on this observation, an automatic speaker selection approach is proposed on the basis of the maximal average between-class variance. Tests in a variety of conditions, including clean and noisy as well as telephone speech, show that this approach can improve the performance of speaker recognition systems. This approach, which is applied here to feature enhancement for speaker recognition, can be expected to also be effective with other biometric modalities besides speech. Further, an alternative feature representation is proposed in this dissertation, which is derived from what we call speaker voice signatures (SVS). These are trajectories in a Kohonen self organising map (SOM) which has been trained to represent the acoustic space. This feature representation is found to be somewhat complementary to the baseline feature set, suggesting that they can be fused to achieve improved performance in speaker recognition. Finally, this dissertation finishes with a number of potential extensions of the proposed approaches. Keywords: feature enhancement, MLP, SOM, speaker basis selection, speaker recognition, biometric, authentication, verificatio

Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems

Wearable healthcare monitoring systems (WHMSs) have received significant interest from both academia and industry with the advantage of non-intrusive and ambulatory monitoring. The aim of this paper is to investigate the use of an adaptive filter to reduce motion artefact (MA) in physiological signals acquired by WHMSs. In our study, a WHMS is used to acquire ECG, respiration and triaxial accelerometer (ACC) signals during incremental treadmill and cycle ergometry exercises. With these signals, performances of adaptive MA cancellation are evaluated in both respiration and ECG signals. To achieve effective and robust MA cancellation, three axial outputs of the ACC are employed to estimate the MA by a bank of gradient adaptive Laguerre lattice (GALL) filter, and the outputs of the GALL filters are further combined with time-varying weights determined by a Kalman filter. The results show that for the respiratory signals, MA component can be reduced and signal quality can be improved effectively (the power ratio between the MA-corrupted respiratory signal and the adaptive filtered signal was 1.31 in running condition, and the corresponding signal quality was improved from 0.77 to 0.96). Combination of the GALL and Kalman filters can achieve robust MA cancellation without supervised selection of the reference axis from the ACC. For ECG, the MA component can also be reduced by adaptive filtering. The signal quality, however, could not be improved substantially just by the adaptive filter with the ACC outputs as the reference signals.Municipal Science & Technology Commission. Beijing Natural Science Foundation (Grants 3102028 and 3122034)General Logistics Science Foundation (Grant CWS11C108)National Institutes of Health (U.S.) (National Institute of General Medical Sciences (U.S.). Grant R01- EB001659)National Institutes of Health (U.S.) (National Institute for Biomedical Imaging and Bioengineering (U.S.) Cooperative Agreement U01- EB-008577

Video Surveillance Over Wireless Sensor and Actuator Networks Using Active Cameras

Although there has been much work focused on the camera control issue on keeping tracking a target of interest, few has been done on jointly considering the video coding, video transmission, and camera control for effective and efficient video surveillance over wireless sensor and actuator networks (WSAN). In this work, we propose a framework for real-time video surveillance with pan-tilt cameras where the video coding and transmission as well as the automated camera control are jointly optimized by taking into account the surveillance video quality requirement and the resource constraint of WSANs. The main contributions of this work are: i) an automated camera control method is developed for moving target tracking based on the received surveillance video clip in consideration of the impact of video transmission delay on camera control decision making; ii) a content-aware video coding and transmission scheme is investigated to save network node resource and maximize the received video quality under the delay constraint of moving target monitoring. Both theoretical and experimental results demonstrate the superior performance of the proposed optimization framework over existing systems

A Remote Markerless Human Gait Tracking for E-Healthcare Based on Content-Aware Wireless Multimedia Communications

Remote human motion tracking and gait analysis over wireless networks can be used for various e-healthcare systems for fast medical prognosis and diagnosis. However, most existing gait tracking systems rely on expensive equipment and take lengthy processes to collect gait data in a dedicated biomechanical environment, limiting their accessibility to small clinics located in remote areas. In this work we propose a new accurate and cost-effective e­ healthcare system for fast human gait tracking over wireless networks, where gait data can be collected by using advanced video content analysis techniques with low-cost cameras in a general clinic environment. Furthermore, based on video content analysis, the extracted human motion region is coded, transmitted, and protected in video encoding with a higher priority against the insignificant background area to cope with limited communication bandwidth. In this way the encoder behavior and the modulation and coding scheme are jointly optimized in a holistic way to achieve the best user-perceived video quality over wireless networks. Experimental results using H.264/AVC demonstrate the validity and efficacy of the proposed system

Extended ammonia observations towards the 'Integral-Shaped Filament'

Recent observations suggest a scenario in which filamentary structures in the ISM represent the first step towards clumps/cores and eventually star formation. The densest filaments would then fragment into prestellar cores owing to gravitational instability. We seek to understand the roles filamentary structures play in high-mass star formation. We mapped the integral-shaped filament (ISF) in NH3 (1, 1) and (2, 2). The whole filamentary structure is uniformly and fully sampled. We find that the morphology revealed by the map of velocity-integrated intensity of the NH3 (1, 1) line is closely associated with the dust ridge. We identify 6 "clumps" related to the well known OMC-1 to 5 and 11 "sub-clumps" within the map and they are separated not randomly but in roughly equal intervals along the ISF. The average spacing of clumps is 11.30'$\pm$1.31' (1.36$\pm$0.16 pc ) and the average spacing of sub-clumps is 7.18'$\pm$1.19' (0.86$\pm$0.14 pc). These spacings agree well with the predicted values of the thermal (0.86 pc) and turbulent sausage instability (1.43 pc) by adopting a cylindric geometry of the ISF with an inclination of $60^{\circ}$ with respect to the line of sight. We also find a velocity gradient of about 0.6 km s-1 pc-1 that runs along the ISF which likely arises from an overall rotation of the Orion A molecular cloud. The inferred ratio between rotational and gravitational energy is well below unity. Furthermore, fluctuations are seen in the centroid velocity diagram along the ISF. The OMC-1 to 5 clouds are located close to the local extrema of the fluctuations, which suggests that there exist gas flows associated with these clumps in the ISF. The derived NH3 (1, 1) and (2, 2) rotation temperatures in the OMC-1 are about 30-40 K. In OMC-2, OMC-3, and the northern part of OMC-4, we find higher and lower temperatures at the boundaries and in the interior, respectively.Comment: Accepted by A&A. 14 pages, 14 figure