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This paper presents an overview on available tools and methods for the simulation of electromagnetic transients in power systems. Both off-line and real-time simulation tools are presented and discussed. The first objective is to give the reader an overview on the modeling and simulation capabilities in currently available state-of-the-art tools. The second objective is to provide perspectives on research topics and needed enhancements. Index Terms--Electromagnetic transients, EMTP, power system models, real-time digital simulation.

This paper introduces an architecture for computer communications applied to the operation and maintenance of power systems, the distributed real-time computer network architecture (DRNA). The architecture consists of four functional entities, namely, application programs associated with information models, an adaptation function, a transport function, and network-and security-management functions to achieve seamless, real-time, adaptive, and secure information exchange between distributed power system control devices. DRNA uses off-the-shelf and standardized technologies along with dedicated ones. Through careful application of the technology, an experimental setup of a distributed cooperative voltage-control network was constructed in a power system simulator to verify the architectural concept. The implemented technologies include mobile agents, middle-ware for prioritized and redundant communication schemes, label-switched and Ethernet-based transport networks, and a secure virtual private network. The experiment demonstrated the effectiveness of DRNA. Index Terms--Architecture, computer network security, cooperative systems, Internet, object-oriented programming, power system communication, protocols, supervisory control and data-acquisition (SCADA) systems.

This paper presents a nonlinear least squares method for measuring the power system frequency, wherein the voltage at the measurement point is modeled by using the Fourier series. The estimation of the fundamental frequency is a nonlinear problem in this formulation and is solved by performing a 1-D search over the range of allowed frequency variation. The voltage signal is used for frequency estimation because it is typically less distorted than the line current, resulting in computational efficiency. The robustness of this algorithm with respect to change in various parameters is studied through simulation and the results are validated by hardware implementation using a Virtex IV field-programmable gate array. An application of this algorithm to a shunt active power filter is also presented. Index Terms--Nonlinear least squares, real-time frequency estimation.

This paper describes the hardware and software modules of a remote Internet-based laboratory for experimentation with a 120-kVA multilevel power converter. The key feature of this laboratory is the utilization of a multilevel converter that can be controlled and supervised remotely in a secured way. A wide variety of laboratory experiments are supported, from grid connection to ac motor control. Users can choose the control structure, the control parameters, and the kind of load and get the graphical results of the measurements, all in real time. Index Terms--Multilevel power converters, real-time control, remote laboratory.

This paper presents a new neural network (NN) algorithm for real-time retrievals of low amounts of precipitable water vapor (PWV) and integrated liquid water from millimeter-wave ground-based observations. Measurements are collected by the 183.3-GHz G-band vapor radiometer (GVR) operating at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility, Barrow, AK. The NN provides the means to explore the nonlinear regime of the measurements and investigate the physical boundaries of the operability of the instrument. A methodology to compute individual error bars associated with the NN output is developed, and a detailed error analysis of the network output is provided. Through the error analysis, it is possible to isolate several components contributing to the overall retrieval errors and to analyze the dependence of the errors on the inputs. The network outputs and associated errors are then compared with results from a physical retrieval and with the ARM two-channel microwave radiometer (MWR) statistical retrieval. When the NN is trained with a seasonal training data set, the retrievals of water vapor yield results that are comparable to those obtained from a traditional physical retrieval, with a retrieval error percentage of ~5% when the PWV is between 2 and 10 mm, but with the advantages that the NN algorithm does not require vertical profiles of temperature and humidity as input and is significantly faster computationally. Liquid water path (LWP) retrievals from the NN have a significantly improved clear-sky bias (mean of ~2.4 g/[m.sup.2]) and a retrieval error varying from 1 to about 10 g/[m.sup.2] when the PWV amount is between 1 and 10 mm. As an independent validation of the LWP retrieval, the longwave downwelling surface flux was computed and compared with observations. The comparison shows a significant improvement with respect to the MWR statistical retrievals, particularly for LWP amounts of less than 60 g/[m.sup.2]. This paper shows that the GVR alone can provide overall improved PWV and LWP retrievals when the PWV amount is less than 10 mm, and, when combined with the MWR, can provide improved retrievals over the whole water-vapor range.

Modeling dynamic systems incurring stochastic disturbances for deriving a control policy is a ubiquitous task in engineering. However, in some instances obtaining a model of a system may be impractical or impossible. Alternative approaches have been developed using a simulation-based stochastic framework, in which the system interacts with its environment in real time and obtains information that can be processed to produce an optimal control policy. In this context, the problem of developing a policy for controlling the system's behavior is formulated as a sequential decision-making problem under uncertainty. This paper considers the problem of deriving a control policy for a dynamic system with unknown dynamics in real time, formulated as a sequential decision-making under uncertainty. The evolution of the system is modeled as a controlled Markov chain. A new state-space representation model and a learning mechanism are proposed that can be used to improve system performance over time. The major difference between the existing methods and the proposed learning model is that the latter utilizes an evaluation function, which considers the expected cost that can be achieved by state transitions forward in time. The model allows decision-making based on gradually enhanced knowledge of system response as it transitions from one state to another, in conjunction with actions taken at each state. The proposed model is demonstrated on the single cart-pole balancing problem and a vehicle cruise-control problem. [DOI: 10.1115/1.3117200]

In recent years, time-triggered communication protocols have been developed to support time-critical applications for in-vehicle communication. In this respect, the FlexRay protocol is likely to become the de facto standard. In this paper, we investigate the scheduling problem of periodic signals in the static segment of FlexRay. We identify and solve two subproblems and introduce associated performance metrics: 1) The signals have to be packed into equal-size messages to obey the restrictions of the FlexRay protocol, while using as little bandwidth as possible. To this end, we formulate a nonlinear integer programming (NIP) problem to maximize bandwidth utilization. Furthermore, we employ the restrictions of the FlexRay protocol to decompose the NIP and compute the optimal message set efficiently. 2) A message schedule has to be determined such that the periodic messages are transmitted with minimum jitter. For this purpose, we propose an appropriate software architecture and derive an integer linear programming (ILP) problem that both minimizes the jitter and the bandwidth allocation. A case study based on a benchmark signal set illustrates our results. Index Terms--FlexRay, integer programming, real time, scheduling, vehicular communication networks.

The FlexRay communication protocol is expected to be the de facto standard for high-speed, in-vehicle communication. In this paper, we formally investigate the scheduling problem for the dynamic segment (DS) of FlexRay. We take the bounds on the generation times and the timing requirements of the signals into consideration to propose a reservation-based scheduling approach that preserves the flexible medium access of the DS. To obtain efficient schedules, we formulate a nonlinear integer programming problem (NIP) that minimizes the required duration of the DS. This NIP is then decomposed into two linear binary integer programming problems to facilitate the computation of feasible message schedules. An experimental study illustrates our message scheduling approach for the DS of FlexRay. Index Terms--FlexRay, integer programming, real time, scheduling, vehicular communication networks.

This paper introduces a new adaptive notch filtering approach to extract the harmonic and reactive current components for power quality purposes in grid-connected converters. The main function of this method is to provide synchronized harmonic and reactive current components for control purposes. The theoretical analysis is presented, and the performance of the method is experimentally evaluated. The methodology is applicable for a wide range of equipment such as uninterrupted power supplies, regenerative converters, active power filters, etc., as a basis for generating the reference signals. Index Terms--Active power filters, adaptive filters, harmonics and reactive power compensation.

Lane departure warning systems (LDWS) are an important element in improving driving safety. In this paper, we propose an embedded Advanced RISC Machines (ARM)-based real-time LDWS. As for software development, an improved lane detection algorithm based on peak finding for feature extraction is used to successfully detect lane boundaries. Then, a spatiotemporal mechanism using the detected lane boundaries is designed to generate appropriate warning signals. As for hardware implementation, a 1-D Gaussian smoother and a global edge detector are adopted to reduce noise effects in the images. By using the developed data transfer channel (DTC) in the reconfigurable field-programmable gate array (FPGA) module, the data transfer rate among the complementary metal-oxide-semiconductor (CMOS) imager module, liquid-crystal display (LCD) display module, and central processing unit (CPU) bus is about 25 frame/s for an image size of 256 x 256. In addition, the proposed departure warning algorithm based on spatial and temporal mechanisms is successfully executed on the presented ARM-based platform. The effectiveness of our system concludes that the lane detection rate is 99.57% during the day and 98.88% at night in a highway environment. The proposed departure mechanisms effectively generate effective warning signals and avoid most false warnings. Index Terms--Computer vision, embedded real-time system, lane departure warning system (LDWS), lane detection, smart vehicle, vanishing point.

Ultrawideband (UWB) is an emerging technology that is expected to achieve high data rate with low-power transmission and to enable quality-of-service (QoS)-based multimedia services over wireless personal area networks (WPANs). Currently, WiMedia alliance proposes the physical layer and medium access control (MAC) layer standards for WPANs. Although WiMedia MAC defines the QoS signaling mechanism, it does not specify the resource-allocation algorithm that will eventually provide the QoS guarantee. To address this issue, we first propose a novel traffic predictor for real-time variable bit rate (VBR) videos. Based on the proposed predictor, we then present a dynamic resource-allocation (DRA) algorithm to support real-time VBR video transmission over WiMedia-based WPANs. Simulation results indicate that the proposed traffic predictor and DRA algorithm significantly outperform other existing schemes. Index Terms--Medium access control (MAC), quality of service (QoS), ultrawideband (UWB), variable bit rate (VBR) video.

Emphasis of the present work is on an elegant real-time solution for GPS/INS integration. Micro-electro mechanical system (MEMS) based inertial sensors are light but not accurate enough for inertial navigation system (INS) applications. An integrated INS/GPS system provides better accuracy compared with either INS or GPS, used individually. This paper describes an improved design and fabrication of a loosely coupled INS-GPS integrated system. The systems currently available use commercial off-the-shelf (COTS) hardware and are, therefore, not optimized for compact, single supply, and low power requirements. In the proposed system, a digital signal processor (DSP) is used for inertial navigation solution and Kalman filter computations. A field programmable gate array (FPGA) is used for creating an efficient interface of the GPS with the DSP. Direct serial interface of the GPS involve tedious processing overhead on the navigation processor. Therefore, a universal asynchronous receiver transmitter (UART) and dual port random axis memory (DPRAM) are created on the FPGA itself. This also reduces the total chip count, resulting in a compact system. The system is designed to give real time processed navigation solutions with an update rate of 100 Hz. All the details of this work are presented.

In endoscopic surgery, the use of long surgical instruments through access ports diminishes tactile feedback and degrades the surgeon's ability to identify hidden tissue abnormalities. To overcome this constraint, we developed a real-time compliance mapping system that is composed of: 1) a standard surgical instrument with a high-precision sensor configuration design; 2) real-time objective interpretation of the output signals for tissue identification; and 3) a novel human-computer interaction technique using interactive voice and handle force monitoring techniques to suit operating theater working environment. The system was calibrated and used in clinical practice in four routine endoscopic human procedures. In a laboratory-based experiment to compare the tissue discriminatory power of the system with that of surgeons' hands, the system's tissue discriminatory power was three times more sensitive and 10% less specific. The data acquisition precision was tested using principal component analysis ([R.sup.2]X : 0.975, Q2 [cumulative (cum)] = 0.808) and partial least square discriminate analysis ([R.sup.2]X = 0.903, [R.sup.2]Y = 0.729, Q2 (cum) = 0.572). Index Terms--Bending beam force transducer, compliance mapping system, endoscopic surgery, surgical devices.

Engineering design is evolving into a global activity. Globally distributed design requires efficient global distribution of models of dynamic physical systems through computer networks. These models must describe the external input-output behavior of the electrical, mechanical, fluid, and thermal dynamics of engineering systems. An efficient system model assembly method is then required to assemble these component system models into a model of a yet higher-level dynamic system. Done recursively, these higher-level system models become possible components for yet higher-level analytical models composed of external model equations in the same standardized format as that of the lowest level components. Real-time, automated exchange, and assembly of engineering dynamic models over a global network requires four characteristics. The models exchanged must have a unique standard format so that they can be exchanged and assembled by an automated process. The exchange of model information must be executed in a single-query transmission to minimize network load. The models must describe only external behavior to protect internal model details. Finally, the assembly process must be recursive so that the transfer and assembly processes do not change with the level of the model exchanged or assembled. This paper will introduce the modular modeling method (MMM), a modeling strategy that satisfies these requirements. The MMM distributes and assembles linear dynamic physical system models with a dynamic matrix representation. Using the MMM method, dynamic models of complex assemblies can be built and distributed while hiding the topology and characteristics of their dynamic subassemblies. [DOI: 10.1115/1.3072119]

A method for real-time mosaic of video flow acquired by a small low-cost unmanned aerial vehicle (UAV) has been presented in this paper. The basic procedures of real-time mosaic are as follows: 1) Each video frame is resampled and orthorectified using a developed mathematical model, which can simultaneously solve the video camera's interior orientation parameters and the exterior orientation parameters of each video frame; 2) each orthorectified video frame is mosaicked at real time. A test field located in Picayune, Mississippi, has been established for testing our method. Sixty-minute video data were collected using the UAV and were processed using the proposed method. The results demonstrated that each video frame can be geo-orthorectified and mosaicked together to produce a 2-D planimetric mapping at near real time. Accuracy of the mosaicked video images (2-D planimetric map) is approximately 1-2 pixels, when compared to 55 checkpoints, which were measured by differential GPS surveying. Index Terms--Image flow, image processing, image registration, unmanned aerial vehicle (UAV).

Fuzzy neural networks (FNNs) have been successfully applied to generate predictive rules for medical or diagnostic data. This brief presents an approach to detect premature ventricular contractions (PVCs) using the neural network with weighted fuzzy membership functions (NEWFMs). The NEWFM classifies normal and PVC beats by the trained bounded sum of weighted fuzzy membership functions (BSWFMs) using wavelet transformed coefficients from the MIT-BIH PVC database. The eight generalized coefficients, locally related to the time signal, are extracted by the nonoverlap area distribution measurement method. The eight generalized coefficients are used for the three PVC data sets with reliable accuracy rates of 99.80%, 99.21%, and 98.78%, respectively, which means that the selected features are less dependent on the data sets. It is shown that the locations of the eight features are not only around the QRS complex that represents ventricular depolarization in the electrocardiogram (ECG) containing a Q wave, an R wave, and an S wave, but also the QR segment from the Q wave to the R wave has more discriminate information than the RS segment from the R wave to the S wave. The BSWFMs of the eight features trained by NEWFM are shown visually, which makes the features explicitly interpretable. Since each BSWFM combines multiple weighted fuzzy membership functions into one using the bounded sum, the eight small-sized BSWFMs can realize real-time PVC detection in a mobile environment. Index Terms--Feature selection, fuzzy neural networks (FNNs), premature ventricular contraction (PVC) classification, wavelet transform (WT), weighted fuzzy membership function.

Unsymmetrical loading on a car like [mu]-split braking, side wind forces, or unilateral loss of fire pressure results in unexpected yaw disturbances that require yaw stabilization either by the driver or by an automatic driver-assist system. The use of two-degrees-of-freedom control architecture known as the model regulator is investigated here as a robust steering controller for such yaw stabilization tasks in a driver-assist system. The yaw stability-enhancing steering controller is designed in the parameter space to satisfy a frequency-domain mixed sensitivity constraint. To evaluate the resulting controller design, a real-time hardware-in-the-loop simulator is developed. Steering tests with and without the controller in this hardware-in-the-loop setup allow the driver to see the effect of the proposed controller to improve vehicle-handling quality. The hardware-in-the-loop simulation setup can also be used for real-time driver-in-the-loop simulation of other vehicle control systems. Index Terms--Hardware-in-the-loop simulation, model regulator, robust control, yaw stability control.

We propose a frame dependency management strategy for error robust transmission of conversational video in mobile networks. We consider an end-to-end video transmission scenario that involves both a wireless uplink as well as a wireless downlink plus some intermediate wireline network transmission. We also investigate the special cases of an end-to-end scenario where only a wireless uplink or a wireless downlink is present. We cope with packet loss on the downlink by retransmitting lost packets from the base station to the receiver for error recovery. Retransmissions are enabled by using fixed-distance reference picture selection during encoding with a prediction distance that corresponds to the round-trip time of the downlink combined with accelerated decoding. We deal with transmission errors on the uplink by sending acknowledgments and predicting the next frame to encode from those slices that have been correctly received by the base station. We show that these two separate approaches for uplink and downlink efficiently complement one another and the resulting end-to-end scheme is characterized by very low computational complexity. We compare our scheme to several state-of-the-art error resiliency approaches and report significant improvements. Index Terms--Adaptive reference picture selection, error resilience, proxy, real-time video transmission.

The MPEG transport stream is an extremely complex structure using interlinked tables and coded identifiers to separate the programs and the elementary streams. Quality management is therefore a complicated issue and the need to identify the degree of coding degradations in terms of coding and/or transmission errors or system failures is becoming an important criterion for the evaluation of the quality of the MPEG streams. A theoretical decoder (T-STD) defines the verification process based on the proper fill level of an MPEG decoder buffers whose size is defined by the standards in order to obtain an evaluation of the MPEG stream quality. This paper describes a new embedded and programmable solution capable of analysing MPEG streams in real time. The proposed hardware architecture provides a real time continuous buffer analysis of the MPEG stream components and is composed of several modules allowing for simultaneous modeling of the various buffers of the T-STD components (video, audio or system). Real time errors flags are generated when the buffers filling level becomes illegal (overflow, empty buffer, transfer delay, etc.). The architecture has been modeled, validated and simulated using the SystemC and VHDL languages in combination with real MPEG DVB-T streams. A VHDL synthesisable model of our architecture allows an implementation on an field-programmable gate array circuit based on Altera APEX20K1000. The hardware implementation of this configurable T-STD allows a data rate of 232 Mbps and requires only 9738 logical cells and 4,7 kB memory. Index Terms--Buffer analysis, digital TV, field-programmable gate arrays (FPGAs), MPEG streams monitoring, real-time embedded systems.

This paper presents the implementation of a video segmentation unit used for embedded automated video surveillance systems. Various aspects of the underlying segmentation algorithm are explored and modifications are made with potential improvements of segmentation results and hardware efficiency. In addition, to achieve real-time performance with high resolution video streams, a dedicated hardware architecture with streamlined dataflow and memory access reduction schemes are developed. The whole system is implemented on a Xilinx field-programmable gate array platform, capable of real-time segmentation with VGA resolution at 25 frames per second. Substantial memory bandwidth reduction of more than 70% is achieved by utilizing pixel locality as well as wordlength reduction. The hardware platform is intended as a real-time testbench, especially for observations of long term effects with different parameter settings. Index Terms--Field-programmable gate array (FPGA), mixture of Gaussian (MoG), video segmentation.

We present single-molecule, real-time sequencing data obtained from a DNA polymerase performing uninterrupted template-directed synthesis using four distinguishable fluorescently labeled deoxyribonucleoside triphosphates (dNTPs). We detected the temporal order of their enzymatic incorporation into a growing DNA strand with zero-mode waveguide nanostructure arrays, which provide optical observation volume confinement and enable parallel, simultaneous detection of thousands of single-molecule sequencing reactions. Conjugation of fluorophores to the terminal phosphate moiety of the dNTPs allows continuous observation of DNA synthesis over thousands of bases without steric hindrance. The data report directly on polymerase dynamics, revealing distinct polymerization states and pause sites corresponding to DNA secondary structure. Sequence data were aligned with the known reference sequence to assay biophysical parameters of polymerization for each template position. Consensus sequences were generated from the single-molecule reads at 15-fold coverage, showing a median accuracy of 99.3%, with no systematic error beyond fluorophore-dependent error rates.

A novel prediction scheme is proposed for real-time MPEG video to predict the burst and long-range dependent traffic. The trend and periodic characteristics of MPEG video traffic are fully captured by a proposed stochastic state-space dynamic model. Then a recursive [H.sub.[infinity]] filtering algorithm is proposed to estimate traffic for long-range prediction. Simulation results based on real MPEG traffic data show that the proposed scheme has superior performance and lower complexity than some adaptive neural network methods, such as TDNN, NARX, and Elman neural networks. Index Terms--[H.sub.[infinity]] filter, long-range dependence, MPEG video, state-space method.

Quarter-pixel accuracy and variable block-size significantly enhance compression performances of the MPEG-4 AVC/H.264 video compression standard over its predecessors, but also significantly increase computation requirements. Firstly, a digital signal processor (DSP)-based solution that achieves real-time integer motion estimation is proposed. Fractional-pixel refinement is too computationally intensive to be efficiently processed on a software-based processor. To address this restriction, a flexible and low complexity VLSI subpixel refinement coprocessor is designed. Thanks to an improved datapath, a high throughput is achieved with low logic resources. Finally, an heterogeneous (DSP-field-programmable gate array) solution to handle real-time motion estimation with variable block-size and fractional-pixel accuracy for high-definition video is studied. This solution, combining programmability and efficiency, achieves motion estimation of 720 p sequences at up to 60 fps. Index Terms--Digital signal processors, field-programmable gate arrays, H.264, motion estimation, parallel processing, real-time.

Recent trends in the telecommunication industry have been moving toward the development of ubiquitous information systems, where the provision of a plethora of advanced multimedia services should be possible, regardless of time and space limitations. An efficient and seamless delivery of multimedia services over various types of wireless networks is still a challenging task. The underlying difficulty consists of the disparity in the bandwidth availability over each network type. Indeed, the fundamental chailenge upon a handoff phenomenon in a heterogeneous wireless network consists of an efficient probing of the bandwidth availability of the new network, followed by a prompt adjustment of the data delivery rate. This paper presents a cross-layer approach that involves five layers, namely, physical, data link, application, network, and transport layers. The three former layers are used to anticipate the handoff occurrence and to locate the new point of attachment to the network. Based on their feedback, the transport layer is used then to probe the resources of the new network using low-priority dummy packets. Being the most widely used protocol for multimedia delivery, this paper addresses multimedia applications based on the Transmission Control Protocol (TCP) and the Real-time Transport Protocol (RTP). The design of the whole cross-layer architecture is discussed, and enhancements to the two protocols are proposed. The performance of the enhanced TCP and the RTP are evaluated and compared against existing schemes through extensive simulations. The obtained results are encouraging and promising for the delivery of multimedia services in heterogeneous wireless networks. Index Terms--Cross layer, heterogeneous wireless networks, next-generation wireless Internet, Real-time Transport Protocol (RTP), Transmission Control Protocol (TCP).

In this paper, a novel method for continuous human movement recognition based on fuzzy vector quantization (FVQ) and linear discriminant analysis (LDA) is proposed. We regard a movement as a unique combination of basic movement patterns, the so-called dynemes. The proposed algorithm combines FVQ and LDA to discover the most discriminative dynemes as well as represent and discriminate the different human movements in terms of these dynemes. This method allows for simple Mahalanobis or cosine distance comparison of not aligned human movements, taking into account implicitly time shifts and internal speed variations, and, thus, aiding the design of a real-time continuous human movement recognition algorithm. The effectiveness and robustness of this method is shown by experimental results on a standard dataset with videos captured under real conditions, and on a new video dataset created using motion capture data. Index Terms--Fuzzy vector quantization, linear discriminant analysis, real-time continuous human movement recognition.

Automatic detection of a falling person in video sequences has interesting applications in video-surveillance and is an important part of future pervasive home monitoring systems. In this paper, we propose a multiview approach to achieve this goal, where motion is modeled using a layered hidden Markov model (LHMM). The posture classification is performed by a fusion unit, merging the decision provided by the independently processing cameras in a fuzzy logic context. In each view, the fall detection is optimized in a given plane by performing a metric image rectification, making it possible to extract simple and robust features, and being convenient for real-time purpose. A theoretical analysis of the chosen descriptor enables us to define the optimal camera placement for detecting people falling in unspecified situations, and we prove that two cameras are sufficient in practice. Regarding event detection, the LHMM offers a principle way for solving the inference problem. Moreover, the hierarchical architecture decouples the motion analysis into different temporal granularity levels, making the algorithm able to detect very sudden changes, and robust to low-level steps errors. Index Terms--Fall detection, layered hidden Markov model (LHMM), metric rectification, multiview pose classification.

This paper introduces a new methodology for compressing ECG signals in an automatic way guaranteeing signal interpretation quality. The approach is based on noise estimation in the ECG signal that is used as a compression threshold in the coding stage. The Set Partitioning in Hierarchical Trees algorithm is used to code the signal in the wavelet domain. Forty different ECG records from two different ECG databases commonly used in ECG compression have been considered to validate the approach. Three cardiologists have participated in the clinical trial using mean opinion score tests in order to rate the signals quality. Results showed that the approach not only achieves very good ECG reconstruction quality but also enhances the visual quality of the ECG signal. Index Terms--Clinical evaluation, ECG coding, Set Partitioning in Hierarchical Trees (SPIHT).

We investigate a class of finite-dimensional time decoding algorithms that: 1) is insensitive with respect to the time-encoding parameters; 2) is highly efficient and stable; and 3) can be implemented in real time. These algorithms are based on the observation that the recovery of time encoded signals given a finite number of observations has the property that the quality of signal recovery is very high in a reduced time range. We show how to obtain a local representation of the time encoded signal in an efficient and stable manner using a Vandermonde formulation of the recovery algorithm. Once the signal values are obtained from a finite number of possibly overlapping observations, the reduced-range segments are stitched together. The signal obtained by segment stitching is subsequently filtered for improved performance in recovery. Finally, we evaluate the complexity of the algorithms and their computational requirements for real-time implementation. Index Terms--Asynchronous communications, frames, irregular sampling, real-time stitching algorithms, time decoding machines (TDMs), time encoding machines (TEMs).

An electric machine submitted to dissipations and a too high temperature can generate irreversible damage. A reduced thermal model allows us to monitor the critical points of the machine. The thermal modeling of the machine adopted here results from the association of two methods: a nodal approach which models the diffusion in the structure and a computational fluid dynamics (CFD) approach which characterizes the convective heat exchanges which operate in the end cavities. A methodology of reduction is proposed and applied to the thermal model of a 5.5-kW two-pole induction machine to obtain a reduced four-node model for real-time thermal monitoring. Index Terms--Electric machines, identification, model reduction, thermal modeling.

A real-time hardware software 2-D vector Doppler system has been realized by means of the FEMMINA platform. The system operates by performing two independent 1-D Doppler estimations on the scan plane of a linear array probe along different directions; the probe is connected to a commercial scanner. The reconstructed velocity is presented in real-time as superposition on the conventional B-mode images. Two different scanning techniques have been implemented, in order to carry out the 2-D Doppler investigation in the area of interest. These techniques allow to use the system both in vivo and in vivo. An extensive set of simulations has been performed in order to establish a gold standard regarding vector Doppler 2-D techniques, and to be able to assess the performance of the 2-D Doppler system by comparing simulated and experimental results. The whole real-time 2-D vector Doppler system is fully certified as hospital equipment, and thus it can be employed to carry out an experimental characterization of the 2-D Doppler technique in the clinical environment. Index Terms--Clinical environment, Doppler measurements, real-time systems, two-dimensional (2-D), vector Doppler.

This paper introduces a 2-D strain imaging technique based on minimizing a cost function using dynamic programming (DP). The cost function incorporates similarity of echo amplitudes and displacement continuity. Since tissue deformations are smooth, the incorporation of the smoothness into the cost function results in reduced decorrelation noise. As a result, the method generates high-quality strain images of freehand palpation elastography with up to 10% compression, showing that the method is more robust to signal decorrelation (caused by scatterer motion in high axial compression and nonaxial motions of the probe) in comparison to the standard correlation techniques. The method operates in less than 1 s and is thus also potentially suitable for real time elastography. Index Terms--Dynamic programming, freehand ultrasound (US), real time strain imaging, regularization, ultrasound elastography.

This paper introduces a novel and general real-time adaptive motion planning (RAMP) approach suitable for planning trajectories of high-DOF or redundant robots, such as mobile manipulators, in dynamic environments with moving obstacles of unknown trajectories. The RAMP approach enables simultaneous path and trajectory planning and simultaneous planning and execution of motion in real time. It facilitates real-time optimization of trajectories under various optimization criteria, such as minimizing energy and time and maximizing manipulability. It also accommodates partially specified task goals of robots easily. The approach exploits redundancy in redundant robots (such as locomotion versus manipulation in a mobile manipulator) through loose coupling of robot configuration variables to best achieve obstacle avoidance and optimization objectives. The RAMP approach has been implemented and tested in simulation over a diverse set of task environments, including environments with multiple mobile manipulators. The results (and also the accompanying video) show that the RAMP planner, with its high efficiency and flexibility, not only handles a single mobile manipulator well in dynamic environments with various obstacles of unknown motions in addition to static obstacles, but can also readily and effectively plan motions for each mobile manipulator in an environment shared by multiple mobile manipulators and other moving obstacles. Index Terms--Adaptive, dynamic obstacles of unknown motion, loose coupling, mobile manipulators, partially specified goal, real time, redundant robots, trajectory optimization.

A method using reduced-order Kalman filters is developed to estimate the thin gas film axial force and moments in real time for mechanical gas face seal systems in a flexibly mounted stator configuration. First-order Gauss--Markov stochastic models, combined with the stator motion equations, form the basis for the reduced-order Kalman filter estimators. Two schemes are presented to estimate axial force and moments based on stator motion measurements. In one scheme, the force and moments are directly estimated and, in another scheme, a set of proper orthogonal decomposition weighting Junctions is estimated, from which the gas film force and moments are computed. Both estimators are shown to approximate the gas film axial force and moments successfully for different forcing functions over a wide range of compressibility numbers. [DOI: 10.1115/1.2936383] Keywords: mechanical gas face seal, state estimation, POD, reduced-order Kalman filter

The paper presents a multiple-input single-output fuzzy logic governor algorithm that can be used to improve the transient response of a diesel generating set, when supplying an islanded load. The proposed governor uses the traditional speed input in addition to voltage and power factor to modify the fueling requirements during various load disturbances. The use of fuzzy logic control allows the use of proportional-integral-derivative (PID) type structures that can provide variable gain strategies to account for nonlinearities in the system. Fuzzy logic also provides a means of processing other input information by linguistic reasoning and a logical control output to aid the governor action during transient disturbance. The test results were obtained using a 50 kVA naturally aspirated diesel generator testing facility. Both real and reactive load tests were conducted. The complex load test results demonstrate that, by using additional inputs to the governor algorithm, enhanced generator transient speed recovery response can be obtained. Index Terms--Diesel engine, digital governors, distributed generation, fuzzy control, real-time control.

This paper discusses the control and implementation of a real-time spotting system. It is intended for high-density high-yield microarray fabrication to facilitate diagnostic and research effort in genomics and proteomics. The method is based on a self-sensing fully automated aspiring/dispensing pin. System performance is evaluated by several batch runs with deionized water solutions of 0.3% fluorescent Cy-3 dye, which has similar physical properties to the deoxyribonucleic acid (DNA) probe materials. Experimental results show that this system is capable of fast and robust DNA/protein microarray fabrication in high volume while keeping spot size as small as 60 [micro]m consistently. Based on the laser scanned images and experimental data of the spotted microarrays, it is also verified that this system can recognize and prevent the formation of abnormal spots. Index Terms--Control, microarray, protein, real time, spotting.

This paper proposes a new voltage instability risk indicator based on local phasor measurements at fast sampling rate. The effectiveness of the indicator is analyzed at EHV load and 'transit' buses. The risk criterion is based on the real-time computation of the Thevenin equivalent impedance of the classic electrical circuit given by an equivalent generator connected to an equivalent load impedance through an equivalent connecting impedance. The main contribution of the paper is the innovating algorithm utilized on the real-time adaptive identification of the Thevenin voltage and impedance equivalents. The algorithm performance is shown through a detailed sensitivity analysis. The paper presents important numerical results from the actual Italian EHV network. Index Terms--Dynamic simulation, long-term voltage stability, online VSA, phasor measurement unit (PMU), Thevenin equivalent, voltage stability.

With the appearance of electricity markets, the variation of the price of electricity will influence usage custom of electric energy. This will complicate short-term load forecasting and challenge the existing forecasting methods that are applied to a fixed-price environment. In regard to the influence of real-time electricity prices on short-term load, a model to forecast short. term load is established by combining the radial basis function (RBF) neural network with the adaptive neural fuzzy inference system (ANFIS). The model first makes use of the nonlinear approaching capacity of the RBF network to forecast the load on the prediction day with no account of the factor of electricity price, and then, based on the recent changes of the real-time price, it uses the ANFIS system to adjust the results of load forecasting obtained by RBF network. This system integration will improve forecasting accuracy and overcome the defects of the RBF network. As shown in this paper by the results of an example of factual forecasting, the model presented can work effectively. Index Terms--Adaptive neural fuzzy inference system, power system, radial basis function neural network, real-time price, short-term load forecasting.

A platform for high spatial and temporal resolution electrophysiological recordings of in vitro electrogenic cell cultures handling 4096 electrodes at a full frame rate of 8 kHz is presented and validated by means of cardiomyocyte cultures. Based on an active pixel sensor device implementing an array of metallic electrodes, the system provides acquisitions at spatial resolutions of 42 [micro]m on an active area of 2.67 mm x 2.67 mm, and in the zooming mode, temporal resolutions down to 8 [micro]s on 64 randomly selected electrodes. The low-noise performances of the integrated amplifier (11 [micro][V.sub.rms]) combined with a hardware implementation inspired by image/video processing concepts enable high-resolution acquisitions with real-time preprocessing capabilities adapted to the handling of the large amount of acquired data. Index Terms--Active pixel sensor (APS), cardiomyocytes culture, electrophysioiogy, extracellular recording, high density, high spatiotemporal resolution, microelectrode array, real-time processing.

This paper describes a method for robust real-time pattern matching. We first introduce a family of image distance measures, the Image Hamming Distance Family. Members of this family are robust to occlusion, small geometrical transforms, light changes, and nonrigid deformations. We then present a novel Bayesian framework for sequential hypothesis testing on finite populations. Based on this framework, we design an optimal rejection/acceptance sampling algorithm. This algorithm quickly determines whether two images are similar with respect to a member of the Image Hamming Distance Family. We also present a fast framework that designs a nearoptimal sampling algorithm. Extensive experimental results show that the sequential sampling algorithm's performance is excellent. Implemented on a Pentium IV 3 GHz processor, the detection of a pattern with 2,197 pixels in 610 x 480 pixel frames, where in each frame the pattern rotated and was highly occluded, proceeds at only 0.022 seconds per frame. Index Terms--Pattern matching, template matching, pattern detection, image similarity measures, Hamming distance, real time, sequential hypothesis testing, composite hypothesis, image statistics, Bayesian statistics, finite populations.

Model-based fitting has proven to be a successful approach to interpreting the large amount of information contained in images. Fitting algorithms search for the global optimum of an objective function, which should correspond to the best model fit in a given image. Although fitting algorithms have been the subject of intensive research and evaluation, the objective function is usually designed ad hoc, based on implicit and domain-dependent knowledge. This often leads to functions with many local minima and a global minimum that does not correspond to the best model fit. We address the root of this problem by learning more robust objective functions. First, we formulate a set of desirable properties for objective functions and give a concrete example of an ideal function that has these properties. Then, we propose a novel approach that learns an objective function from training data generated by this function and manually annotated images. In this approach, critical decisions such as the feature selection are automated and the remaining manual steps hardly require domain-dependent knowledge. An extensive empirical evaluation demonstrates that learned objective functions enable fitting algorithms to determine the best model fit more accurately and efficiently than designed objective functions. Index Terms--Computer vision, vision and scene understanding, face and gesture recognition, real-time systems.

Within 2 months of its launch in April 2006 as part of the Earth Observing System A-Train satellite constellation, the National Aeronautics and Space Administration Earth System Science Pathfinder (ESSP) CloudSat mission began making significant contributions toward broadening the understanding of detailed cloud vertical structures around the earth. Realizing the potential benefit of CloudSat to both the research objectives and operational requirements of the U.S. Navy, the Naval Research Laboratory coordinated early on with the CloudSat Data Processing Center to receive and process first-look 94-GHz Cloud Profiling Radar datasets in near--real time (4-8 h latency), thereby making the observations more relevant to the operational community. Applications leveraging these unique data, described herein, include 1) analysis/ validation of cloud structure and properties derived from conventional passive radiometers, 2) tropical cyclone vertical structure analysis, 3) support of research field programs, 4) validation of numerical weather prediction model cloud fields, and 5) quantitative precipitation estimation in light rainfall regimes.

This paper presents the real-time simulation and control of the 'Sen' Transformer (ST) for transmission power-flow regulation. A detailed electromagnetic transient model was developed for the ST embedded in the network, and a comprehensive control technique was proposed for the operation of the ST. To implement the models in real time, a state-of-the-art high performance PC-cluster-based real-time simulator was used. The ST model and the controller are implemented using a custom C program in MATLAB/SIMULINK environment. The execution time of the entire system is only 75 [micro]s on a simulation time-step of 100 [micro]s. Real-time oscilloscope results are provided to show the validity of the model under steady-state and transient conditions. Index Terms--Electromagnetic transient analysis, power system modeling, real-time systems, 'Sen' transformer.

The recently launched LabPET[TM], a small animal Avalanche PhotoDiode (APD)-based PET scanner with quasi-individual readout and massively parallel processing, makes it possible to acquire real-time information necessary for Positron Emission Tomography (PET) image reconstruction. Since each APD is coupled to an LYSO/LGSO phoswich scintillator pair, an efficient crystal identification algorithm must be developed to sustain real-time crystal feature extraction in high PET count rate. Furthermore, a less application specific algorithm is needed to easily expand its use to a large range of crystal materials. For these reasons, a new ultra-fast crystal identification algorithm based on a Wiener filter is proposed. This optimum filter instantly recovers crystal parameters by minimizing a linear cost function. A one-dimension projection based discrimination is used to identify the scintillating crystal. The algorithm achieves a discrimination rate of ~88% for low-energy X-ray photons (~60 keV) and up to ~100% for high energy 511 keV photopeak photons, with a maximum throughput of 10 Mevents/sec when implemented in a field programmable gate array. Index Terms--Crystal identification, positron emission tomography, Wiener filter.

Fast independent component analysis (FastICA) algorithm separates the independent sources from their mixtures by measuring non-Gaussian. FastICA is a common offline method to identify artifact and interference from their mixtures such as electroencephalogram (EEG), magnetoencephalography (MEG), and electrocardiogram (ECG). Therefore, it is valuable to implement FastICA for real-time signal processing. In this paper, the FastICA algorithm is implemented in a field-programmable gate array (FPGA), with the ability of real-time sequential mixed signals processing by the proposed pipelined FastICA architecture. Moreover, in order to increase the numbers precision, the hardware floating-point (FP) arithmetic units had been carried out in the hardware FastICA. In addition, the proposed pipeline FastICA provides the high sampling rate (192 kHz) capability by hand coding the hardware FastICA in hardware description language (HDL). To verify the features of the proposed hardware FastICA, simulations are first performed, then real-time signal processing experimental results are presented using the fabricated platform. Experimental results demonstrate the effectiveness of the presented hardware FastICA as expected. Index Terms--Blind source separation (BSS), fast independent component analysis (FastICA), field-programmable gate array (FPGA), floating point (FP).