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This paper focuses on the development of an online method for diagnosing high-resistance connection (HRC) in delta-connected permanent magnet synchronous machine (PMSM) using zero-sequence current component (ZSCC). The development of this method begins with the establishment of the mathematic model of the PMSM with the HRC. Based on the model, a ZSCC-based method is proposed to diagnose the HRC. The fault indicator and angle differences are defined for fault diagnosis. To implement online diagnosis, an effective frequency tracking algorithm is applied. Finally, the fault diagnosis steps are presented. This method is capable of detecting the fault, evaluating the fault severity, and identifying the faulty phases. The simulation and experiment are carried out to verify the proposed method. Both the results show the validity of the proposed method, leading to the effective diagnosis of the HRC in the delta-connected PMSM. [ABSTRACT FROM AUTHOR]

IC3 is one of the most successful algorithms for hardware model checking. Since its invention in 2010, several variants of the original algorithm have been published, proposing optimizations and/or alternative procedures for many different steps of the algorithm. In this paper, we present a thorough empirical comparison of a large set of optimizations and procedures for the steps of IC3, considering “high-level” variants/extensions to the basic algorithm, as well as “low-level” optimizations/configuration settings. We implemented each of them in the same tool, optimizing the implementations to the best of our knowledge. This enabled for a flexible experimentation in a controlled environment, and to gain new insights about their most important differences and commonalities, as well as about their performance characteristics. We conducted the experiments using as benchmarks the problems used in the last four editions of the hardware model checking competition. The analysis helped us to identify several settings leading to significant improvements with respect to a basic implementation of IC3. [ABSTRACT FROM AUTHOR]

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By considering the original pairwise distance in the contextual space, we develop a feature vector called sparse contextual activation (SCA) that encodes the local distribution of an image. Hence, re-ranking task can be simply accomplished by vector comparison under the generalized Jaccard metric, which has its theoretical meaning in the fuzzy set theory. In order to improve the time efficiency of re-ranking procedure, inverted index is successfully introduced to speed up the computation of generalized Jaccard metric. As a result, the average time cost of re-ranking for a certain query can be controlled within 1 ms. Furthermore, inspired by query expansion, we also develop an additional method called local consistency enhancement on the proposed SCA to improve the retrieval performance in an unsupervised manner. On the other hand, the retrieval performance using a single feature may not be satisfactory enough, which inspires us to fuse multiple complementary features for accurate retrieval. Based on SCA, a robust feature fusion algorithm is exploited that also preserves the characteristic of high time efficiency. We assess our proposed method in various visual re-ranking tasks. Experimental results on Princeton shape benchmark (3D object), WM-SRHEC07 (3D competition), YAEL data set B (face), MPEG-7 data set (shape), and Ukbench data set (image) manifest the effectiveness and efficiency of SCA. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient blind image quality assessment (BIQA) algorithm, which is characterized by a new feature fusion scheme and a k -nearest-neighbor (KNN)-based quality prediction model. Our goal is to predict the perceptual quality of an image without any prior information of its reference image and distortion type. Since the reference image is inaccessible in many applications, the BIQA is quite desirable in this context. In our method, a new feature fusion scheme is first introduced by combining an image’s statistical information from multiple domains (i.e., discrete cosine transform, wavelet, and spatial domains) and multiple color channels (i.e., Y, Cb, and Cr). Then, the predicted image quality is generated from a nonparametric model, which is referred to as the label transfer (LT). Based on the assumption that similar images share similar perceptual qualities, we implement the LT with an image retrieval procedure, where a query image’s KNNs are searched for from some annotated images. The weighted average of the KNN labels (e.g., difference mean opinion score or mean opinion score) is used as the predicted quality score. The proposed method is straightforward and computationally appealing. Experimental results on three publicly available databases (i.e., LIVE II, TID2008, and CSIQ) show that the proposed method is highly consistent with human perception and outperforms many representative BIQA metrics. [ABSTRACT FROM AUTHOR]

This paper describes a new vision-based control method to drive a set of robots moving on the ground plane to a desired formation. As the main contribution, we propose to use multiple camera-equipped unmanned aerial vehicles (UAVs) as control units. Each camera views, and is used to control, a subset of the ground team. Thus, the method is partially distributed, combining the simplicity of centralized schemes with the scalability and robustness of distributed strategies. Relying on a homography computed for each UAV-mounted camera, our approach is purely image-based and has low computational cost. In the control strategy we propose, if a robot is seen by multiple cameras, it computes its motion by combining the commands it receives. Then, if the intersections between the sets of robots viewed by the different cameras satisfy certain conditions, we formally guarantee the stabilization of the formation, considering unicycle robots. We also propose a distributed algorithm to control the camera motions that preserves these required overlaps, using communications. The effectiveness of the presented control scheme is illustrated via simulations and experiments with real robots. [ABSTRACT FROM PUBLISHER]

This paper presents algorithms to compute the generalized distance between two separated or penetrating compact convex sets, which is defined as the minimum or maximum scale factor of a given gauge set such that the scaled gauge set intersects or is contained in the Minkowski difference of the two sets. The traditional Euclidean distance is a special case where the origin-centered unit ball is used as the gauge set. While the generalized distance was proposed almost a decade ago, the only practical method for its computation has been general-purpose numerical optimization, which is computationally expensive. In contrast, our geometry-based algorithms are efficient and guarantee globally optimal solutions. Important applications of the algorithms in robotics include collision detection and grasp planning. The algorithm for computing the penetration distance also provides an accurate and efficient approach to flatness error evaluation, which is a fundamental problem in manufacturing. We demonstrate that our algorithms possess superior efficiency and accuracy in these applications. [ABSTRACT FROM PUBLISHER]

In this paper, we address the theoretical aspects of coherence region modeling and its inversion methods for polarimetric interferometric synthetic aperture radar (PolInSAR). Instead of only considering the geometrical shape of the coherence region, we focus on directly modeling the whitened interferometric cross-correlation matrix of the PolInSAR data. In particular, we consider three classes of generic scattering models that respectively contain single, double, and triple phase centers within one resolution cell. We then demonstrate, for each class, that the modeled whitened interferometric cross-correlation matrix is normal. Based on this property, we propose, for each case, efficient algorithms to obtain the best normal matrix approximation solution for model inversion from the observed whitened interferometric cross-correlation matrix. In addition, we show how a simple and effective criterion can be designed from the derived solutions for model validation. Finally, we verify the solutions with both simulated and real data. The results prove the proposed method to be a very promising tool for PolInSAR applications. [ABSTRACT FROM PUBLISHER]

In this paper, a new method for novel X-ray pulsar navigation is proposed to overcome the Doppler effects from the motion of a deep space explorer. An analysis was undertaken of the dynamic orbit model of the interplanetary trajectory cruise phase. During a pulsar signal observation period, the deep space explorer can be considered to be at a constant acceleration motion. A Doppler compensation method is proposed based on this analysis. The method demonstrates great advantages in terms of low computational cost. However, there is an evident bias due to the Doppler compensation in the pulse time-of-arrival (TOA). Moreover, the pulse TOA bias and the velocity estimation error of the deep space explorer are correlated, resulting in a decline in Kalman filter performance. To deal with this problem, we constructed a TOA measurement bias model with respect to the state estimation error, and we developed an extended Kalman filter (EKF) with correlated measurement bias and state estimation error. Results from simulations suggest that the proposed navigation method is feasible, accurate, and effective. The proposed navigation method based on EKF with correlated measurement bias and state estimation error proves to be more accurate than a traditional EKF-based method. [ABSTRACT FROM AUTHOR]

Topic modeling has become a widely used tool for document management. However, there are few topic models distinguishing the importance of documents on different topics. In this paper, we propose a framework LIMTopic to incorporate link based importance into topic modeling. To instantiate the framework, RankTopic and HITSTopic are proposed by incorporating topical pagerank and topical HITS into topic modeling respectively. Specifically, ranking methods are first used to compute the topical importance of documents. Then, a generalized relation is built between link importance and topic modeling. We empirically show that LIMTopic converges after a small number of iterations in most experimental settings. The necessity of incorporating link importance into topic modeling is justified based on KL-Divergences between topic distributions converted from topical link importance and those computed by basic topic models. To investigate the document network summarization performance of topic models, we propose a novel measure called log-likelihood of ranking-integrated document-word matrix. Extensive experimental results show that LIMTopic performs better than baseline models in generalization performance, document clustering and classification, topic interpretability and document network summarization performance. Moreover, RankTopic has comparable performance with relational topic model (RTM) and HITSTopic performs much better than baseline models in document clustering and classification. [ABSTRACT FROM AUTHOR]

Magnetic tracking technology is emerging to provide an occlusion-free tracking scheme for the estimation of full pose (position and orientation) of various instruments. This brings substantial benefits for intracorporeal applications, such as for tracking of flexible or wireless endoscopic devices, and thus is significant for further computer-assisted diagnosis, interventions, and surgeries. Toward efficient magnetic tracking, a 6-D magnetic localization and orientation method is proposed in this paper. An annular permanent magnet is mounted on the exterior surface of a capsule. With a magnetic sensor array, the magnetic field can be measured and the capsule’s 3-D location and 3-D orientation information can be estimated based on proposed closed-form analytical model of annular magnet and particle swarm optimization algorithm. Magnetic dipole model and Levenberg–Marquardt algorithm are used to improve the speed and accuracy of estimation. Extensive simulation experiments show that the localization and orientation method works well with good position and orientation accuracy. [ABSTRACT FROM AUTHOR]

The Warp code (and its framework of associated tools) was initially developed for particle-in-cell simulations of space-charge-dominated ion beams in accelerators, for heavy-ion-driven inertial fusion energy, and related experiments. It has found a broad range of applications, including nonneutral plasmas in traps, stray electron clouds in accelerators, laser-based acceleration, and the focusing of ion beams produced when short-pulse lasers irradiate foil targets. We summarize novel methods used in Warp, including: time-stepping conducive to diagnosis and particle injection; an interactive Python-Fortran-C structure that enables scripted and interactive user steering of runs; a variety of geometries (3-D $x$ , $y$ , $z$ ; 2-D $r$ , $z$ ; 2-D $x$ , $y$ ); electrostatic and electromagnetic field solvers; a cut-cell representation for internal boundaries; the use of warped coordinates for bent beam lines; adaptive mesh refinement, including a capability for time-dependent space-charge-limited flow from curved surfaces; models for accelerator lattice elements (magnetic or electrostatic quadrupole lenses, accelerating gaps, etc.) at user-selectable levels of detail; models for particle interactions with gas and walls; moment/envelope models that support sophisticated particle loading; a drift-Lorentz mover for rapid tracking through regions of strong and weak magnetic field; a Lorentz-boosted frame formulation with a Lorentz-invariant modification of the Boris mover; an electromagnetic solver with tunable dispersion and stride-based digital filtering; and a pseudospectral electromagnetic solver. Warp has proven useful for a wide range of applications, described very briefly herein. It is available as an open-source code under a BSD license. This paper describes material presented during the Prof. Charles K. (Ned) Birdsall Memorial Session of the 2013 IEEE Pulsed Power and Plasma Science Conference. In addition to our overview of the computational methods used in Warp, we summarize a few aspects of Ned's contributions to plasma simulation and to the careers of those he mentored. [ABSTRACT FROM PUBLISHER]

In this paper, we formulate realistic beamforming (BF) training (or beam steering) in the emerging 60-GHz millimeter-wave communications as a numerical optimization problem. To maximize the receiving SNR, it aims to identify the optimal beam pair from a prescribed codebook using as little overhead as possible. Being a promising numerical method that excludes a functional derivative, the Rosenbrock numerical search may be of great significance to such applications. Nevertheless, for the encountered nonsmooth objective function, a search failure is inevitable due to the local optimum. To meet this challenge, we further present an appealing global numerical algorithm inspired by simulated annealing (SA) mechanics. In sharp contrast to classical schemes, numerical probes that lead to reward improvement are always accepted, and search moves toward worse solutions are also permitted, with a probability associated with an external temperature parameter. By relying on a newly designed two-level annealing schedule, the temperature decreases; thereby, permitting movements to worse solutions is progressively restricted. Consequently, it can basically escape from the local optimum. We then apply this new numerical search to beam switching of 60-GHz communications. Experimental simulations have demonstrated that the developed beam-switching scheme can efficiently discover the optimal beam pair by considerably reducing protocol overhead and energy consumption. [ABSTRACT FROM PUBLISHER]

This paper presents a multi-objective robust optimization strategy assisted by the surrogate model. In order to guarantee the accurate response prediction, the performances of three different Kriging surrogate models, ordinary Kriging, first-order universal Kriging (UK), and second-order UK, are investigated through analytical benchmark functions. Once the accurate model is constructed, the performance analysis can be efficiently approximated during optimization process. Furthermore, the robustness against uncertainty is evaluated by the worst-case scenario through applying optimization technique to the approximated model in the uncertainty set. The proposed algorithm is validated through one electromagnetic application, a robust version of the TEAM 22. [ABSTRACT FROM AUTHOR]

Petri nets are suitable for modeling and analysis of business processes. However, the lack of data concepts often makes Petri-net-based models excessively large and difficult to analyze especially when process logic is sensitive to changes of process attribute values. Emergency treatment processes are a typical example of this situation. To solve the aforementioned problems, this paper proposes a new hierarchical Petri net model for modeling and verification of emergency treatment processes. The hierarchical Petri net model includes three separate but closely related models, i.e., a business process logic net, a business process semantic net, and a set of case models. Business process logic nets are used to model the task dependencies disregarding semantic information. Business process semantic nets introduce data concepts to business process logic nets to model semantic information such as process attributes or conditions of sequence flows. Case models are used to model the practical routes of specific business instances. Based on the three models, a formal verification algorithm of an emergency treatment process is presented. Finally, the hierarchical modeling and verification methods are validated by an emergency treatment process of highways under snow/ice weather conditions. [ABSTRACT FROM AUTHOR]

Capacitive and inductive coupling between bus lines results in crosstalk induced delays. Many bus encoding techniques have been proposed to improve the performance. Existing implementation techniques and mapping algorithms in the literature only apply the specific encoding. This paper presents the first generalized framework for a stall-free on-chip codeword generation strategy that is scalable and easy to automate. It is applicable to the coupling aware encoding techniques that allow recursive codeword generation. The proposed implementation strategy iteratively generates codewords without explicitly enumerating them. Codeword mapping relies on graph-based representation that is unique to the given encoding technique. The codewords are calculated on-chip using basic function blocks, such as adders and multiplexers. Three encoding techniques were implemented using the proposed strategy. Experimental results show significant reduction in the area overhead and power dissipation over the existing method that uses random logic to implement the codec. [ABSTRACT FROM PUBLISHER]

Analytical models have been demonstrated to be effective tools in the analysis of electromagnetic devices by providing fast, yet accurate solutions. In this paper, a comprehensive analytical framework for double-rotor radial-flux air-cored permanent-magnet (PM) machines is developed whereby the average as well as the torque ripples, back-electromotive force (EMF) waveforms, air-gap flux density distribution, and a number of other characteristics regarding the design of the machine are predicted. Also, closed-form expressions for inductances of the stator coils are analytically derived. All machine parameters and material properties including iron saturation are considered in the model. Moreover, an algorithm in order to optimally design the thicknesses of the rotor yokes based on the utilized steel is presented. Finally, genetic optimizations regarding the enhancement of the produced torque and back-EMF are performed. It is also shown that the results obtained from the proposed model match well with those issued from finite element method. [ABSTRACT FROM PUBLISHER]

Inductors are a significant contributor to mass in many power applications including the dc link in high-power drives and in dc–dc power conversion equipment. Permanent magnet inductors (PMIs) may be used in place of traditional inductors in dc biased applications with significant (40%) mass savings. This paper sets forth a rigorous, systematic, and multifaceted design paradigm for a PMI, using a buck converter application as an example. The algorithm includes electrical, magnetic, and thermal analysis and minimizes overall converter mass and loss. The algorithm is demonstrated in the design and testing of a 4 kW laboratory scale dc–dc converter. [ABSTRACT FROM PUBLISHER]

Intercell interference coordination (ICIC) techniques not only help improve cellular data coverage but allow more efficient use of a valuable wireless spectrum as well. This paper investigates soft frequency reuse (SFR), which is a form of ICIC, for long-term evolution (LTE) systems. By analyzing the throughput of the SFR scheme, we find that classifying cell-edge users and cell-center users is critical. Thus, we develop low-complexity decentralized SFR scheduling algorithms that include optimal user classification and balance throughput and fairness among multiusers. We also propose suboptimal methods to reduce computational complexity. Computer simulation demonstrates that gains of the proposed SFR algorithm can improve the fifth percentile user throughput by 26% while maintaining the same cell average throughput, compared with a non-ICIC system. [ABSTRACT FROM PUBLISHER]

Synthetic aperture radar (SAR) images are often blurred by phase perturbations induced by uncompensated sensor motion and/or unknown propagation effects caused by turbulent media. To get refocused images, autofocus proves to be a useful postprocessing technique applied to estimate and compensate the unknown phase errors. However, a severe drawback of the conventional autofocus algorithms is that they are only capable of removing one-dimensional azimuth phase errors (APEs). As the resolution becomes finer, residual range cell migration (RCM), which makes the defocus inherently two dimensional (2-D), becomes a new challenge. In this paper, correction of APE and residual RCM are presented in the framework of polar format algorithm (PFA). First, an insight into the underlying mathematical mechanism of polar reformatting is presented. Then, based on this new formulation, the effect of polar reformatting on the uncompensated APE and residual RCM is investigated in detail. By using the derived analytical relationship between APE and residual RCM, an efficient 2-D autofocus method is proposed. Experimental results indicate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a distributed recharging rate control algorithm which combines the objectives of regulating frequency and improving the utilization of electric generators. An incentive policy \kappa is created that encourages electric vehicles (EVs) to demand energy when non-EV demand is low and electric generators are underutilized. EVs also act as frequency regulators which can control their participation role by modifying their respective payment rate wi. The proposed distributed recharging rate control algorithm can realize a Demand Management solution for EVs and does not require explicit real time communication from the electric generators or between the recharging sockets. A mechanism is presented that can trade off an ideal incentive policy with its approximation and enable the integration of the proposed controller with legacy protection system. Simulation is used to assess the algorithm and to highlight its embedded characteristics. [ABSTRACT FROM PUBLISHER]

In competitive environments, most equipment are operated closer to or at their limits and as a result, equipment's maintenance schedules may be affected by system conditions. In this paper, we propose a Markov decision process (MDP) that allows better flexibility in conducting maintenance. The proposed MDP model is based on a state transition diagram where inspection and maintenance (I&M) delay times are explicitly incorporated. The model can be solved efficiently to determine adaptive maintenance policies. This formulation successfully combines the long term aging process with more frequently observed short term changes in equipment's condition. We demonstrate the applicability of the proposed model using I&M data of local transformers. [ABSTRACT FROM PUBLISHER]

We present, in this paper, the FAIR algorithm: a fast algorithm for document image restoration. This algorithm has been submitted to different contests where it showed good performance in comparison to the state of the art. In addition, this method is scale invariant and fast enough to be used in real-time applications. The method is based on a double-threshold edge detection approach that makes it possible to detect small details while remaining robust against noise. The performance of the proposition is evaluated on several types of degraded document images where considerable background noise or variation in contrast and illumination exist. [ABSTRACT FROM PUBLISHER]

Grid-connected induction generators (IGs) suffer from voltage and frequency fluctuations when stator circuits are disconnected from the power grid. A typical strategy to prevent this problem is to remove the shunt capacitor to cease self-excitation. However, when paralleling the IG with the power grid, another problem of severe voltage drop caused by excitation current inrush occurs. This paper presents an active voltage and frequency regulator (AVFR) to alleviate the undesired transients for the IG in grid-connection and grid-disconnection cases. The proposed AVFR is realized using a voltage-source inverter (VSI) with a controllable resistor at the dc link. The active power at the ac side is rectified to maintain a constant dc-link voltage using a VSI that also supplies excitation current to the machine. To achieve quick ac current response for the VSI, a stationary \alpha–\beta-axis-based direct current controller is proposed. A new algorithm based on the normalized voltage vector, which features a linear relation between the \alpha-axis voltage and phase angle, leads directly to a rule that will detect the frequency deviation and provide effective frequency control. The experimental results from a 2.5-kVA digital-signal-processor-based laboratory prototype verify the effectiveness of the proposed AVFR. [ABSTRACT FROM PUBLISHER]

Three-phase inverters are currently utilized in an enormous variety of industrial applications, including variable-speed ac drives. However, due to their complexity and exposure to several stresses, they are prone to suffer critical failures. Accordingly, this paper presents a novel diagnostic algorithm that allows the real-time detection and localization of multiple power switch open-circuit faults in inverter-fed ac motor drives. The proposed method is quite simple and just requires the measured motor phase currents and their corresponding reference signals, already available from the main control system, therefore avoiding the use of additional sensors and hardware. Several experimental results using a vector-controlled permanent-magnet synchronous motor drive are presented, showing the diagnostic algorithm effectiveness, its relatively fast detection time, and its robustness against false alarms. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a cascaded sparse/DCT (S/DCT) two-layer representation of prediction residuals, and implement this idea on top of the state-of-the-art high efficiency video coding (HEVC) standard. First, a dictionary is adaptively trained to contain featured patterns of residual signals so that a high portion of energy in a structured residual can be efficiently coded via sparse coding. It is observed that the sparse representation alone is less effective in the R-D performance due to the side information overhead at higher bit rates. To overcome this problem, the DCT representation is cascaded at the second stage. It is applied to the remaining signal to improve coding efficiency. The two representations successfully complement each other. It is demonstrated by experimental results that the proposed algorithm outperforms the HEVC reference codec HM5.0 in the Common Test Condition. [ABSTRACT FROM PUBLISHER]

In this paper, a new iterative algorithm for the analysis of properties of magnetic shielding systems is proposed. Since such shielding systems for low frequency applications are composed of thin-walled shells with magnetic materials of high permeability, the thin shell approximation is adopted and a numerical integral formulation of the ensuing magnetostatic problem is obtained in the form of a convolution equation. This algebraic system is eventually solved iteratively by exploiting the convolution properties of the discrete Fourier transform. The convergence properties of the procedure are analyzed and tested on two case studies where isotropic and anisotropic magnetic shields are used. [ABSTRACT FROM AUTHOR]

Synthesis of operational behavior models from scenario-based specifications has been extensively studied. The focus has been mainly on either existential or universal interpretations. One noteworthy exception is Live Sequence Charts (LSCs), which provides expressive constructs for conditional universal scenarios and some limited support for nonconditional existential scenarios. In this paper, we propose a scenario-based language that supports both existential and universal interpretations for conditional scenarios. Existing model synthesis techniques use traditional two-valued behavior models, such as Labeled Transition Systems. These are not sufficiently expressive to accommodate specification languages with both existential and universal scenarios. We therefore shift the target of synthesis to Modal Transition Systems (MTS), an extension of labeled Transition Systems that can distinguish between required, unknown, and proscribed behavior to capture the semantics of existential and universal scenarios. Modal Transition Systems support elaboration of behavior models through refinement, which complements an incremental elicitation process suitable for specifying behavior with scenario-based notations. The synthesis algorithm that we define constructs a Modal Transition System that uses refinement to characterize all the Labeled Transition Systems models that satisfy a mixed, conditional existential and universal scenario-based specification. We show how this combination of scenario language, synthesis, and Modal Transition Systems supports behavior model elaboration. [ABSTRACT FROM PUBLISHER]

Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However, most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure evaluation that may differ in various patient populations, rendering the technique unreliable. A promising complementary technique for automatic estimation of BP, based on the dependence of pulse transit time (PTT) on cuff pressure (CP) (PTT–CP mapping), has been proposed in the literature. However, a theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In this paper, we propose a novel coefficient-free BP estimation method based on PTT–CP dependence. PTT is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically shown that PTT–CP mappings computed from various points on the arterial pulses can be used to directly estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and 4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our work thus shows promise toward providing robust and objective BP estimation in a variety of patients and monitoring situations. [ABSTRACT FROM PUBLISHER]

Write errors in bit-patterned-media-recording are a unique problem that may require nonconventional coding and signal processing techniques. Development of such advanced algorithms requires a simple yet accurate channel model to start with. In this paper, we analyze the various sources of write error in BPMR based hard drives and conduct write error characterization. The system parameters are either measured from current hard drives or set with realistic assumptions. A position dependent write error model is proposed based on these analyses which lead to a modified binary symmetric channel model for BPMR. [ABSTRACT FROM PUBLISHER]

Channel estimation error results in severe performance deterioration in wireless networks. In this paper, we study the impact of imperfect channel estimation (ICE) on the outage performance of bidirectional relaying where the two sources have asymmetric traffic requirements (ATRs). In particular, we focus on the amplify-and-forward (AF) relay-assisted multiple-access broadcast (MABC) protocol, i.e., MABC-AF, which has received much attention due to its high spectrum efficiency and low complexity. In the single-relay scenario, we derive exact and generalized closed-form expressions for system outage probability, which indicate that the system outage is determined by the unidirectional outage in the case of highly asymmetric traffic patterns. For more insights into our approach, the closed-form asymptotic expressions are also evaluated, manifesting the interesting error floor (EF) phenomenon due to ICE. Using these analytical results, we further develop a robust and practical optimum power-allocation (OPA) algorithm that minimizes the system outage probability under aggregate and individual node power constraints. In the multirelay scenario, by taking into account the traffic knowledge, a novel relay selection criterion is proposed for asymmetric MABC-AF, followed by its impact on the system outage probability in the presence of ICE. Numerical results validate the accuracy of our analytical results and highlight the effect of the proposed OPA algorithm under various traffic requirements and channel estimation errors. Furthermore, the results also show that the proposed relay selection criterion is superior to the classical max–min criterion with ATRs, and the performance improvement becomes remarkable as channel estimation error increases. [ABSTRACT FROM PUBLISHER]

In this paper, a new method for the consistent analysis of periodic metasurfaces with bianisotropic particles is introduced. The proposed technique combines a microscopic modeling approach at the level of the constituting meta-atoms with a macroscopic equivalent surface characterization, to unambiguously determine a set of surface susceptibilities that properly predict the reflection and transmission properties of the metasurface. Comparisons with alternative schemes and full-wave simulation results for bianisotropic scatterers, frequently utilized as building blocks of realistic metasurfaces, are provided in order to validate the featured algorithm. [ABSTRACT FROM PUBLISHER]

The modeling of High Temperature Superconductor (HTS) devices has presented considerable challenges over the years. One of the main difficulties arises due to the high degree of non-linearity associated with the HTS materials. Iterative techniques are applied to deal with such nonlinearities, and construct computational prototypes and solvers. The conventional approaches such as the Newton-Raphson (NR) method, and the Successive Substitution (SS) method have been applied in the past but they have shortcomings of being unstable in certain scenarios, and at times, are very slow to converge. This paper presents a new algorithm which attempts to address these issues based on the ideas of the Aitken technique. [ABSTRACT FROM AUTHOR]

We present a comprehensive, self-contained, and mechanically verified proof of correctness of a maximally redundant SRT design for floating-point division and square root extraction, supported by verified procedures that 1) test the admissibility of a proposed digit selection table, 2) determine the minimal dimensions of an admissible table for a given arbitrary radix, and 3) generate these tables. For square root extraction, we also provide a verified procedure for generating an initial approximation that meets the accuracy requirement of the algorithm and ensures that the digit selection index derived from successive partial roots remains static throughout the computation. A radix-8 instantiation of these algorithms has been implemented in the floating-point unit of the AMD processor code-named Steamroller. To ensure their correctness, all of our results and procedures have been formalized and mechanically checked by the ACL2 prover. We present evidence of the value of this approach by comparing it to that of a more conventional published paper that reports similar results, which are shown to be fatally flawed. [ABSTRACT FROM AUTHOR]

From the perspective of the Bayesian approach, the denoising problem is essentially a prior probability modeling and estimation task. In this paper, we propose an approach that exploits a hidden Bayesian network, constructed from wavelet coefficients, to model the prior probability of the original image. Then, we use the belief propagation (BP) algorithm, which estimates a coefficient based on all the coefficients of an image, as the maximum-a-posterior (MAP) estimator to derive the denoised wavelet coefficients. We show that if the network is a spanning tree, the standard BP algorithm can perform MAP estimation efficiently. Our experiment results demonstrate that, in terms of the peak-signal-to-noise-ratio and perceptual quality, the proposed approach outperforms state-of-the-art algorithms on several images, particularly in the textured regions, with various amounts of white Gaussian noise. [ABSTRACT FROM PUBLISHER]

We address the problem of unconstrained face recognition from remotely acquired images. The main factors that make this problem challenging are image degradation due to blur, and appearance variations due to illumination and pose. In this paper, we address the problems of blur and illumination. We show that the set of all images obtained by blurring a given image forms a convex set. Based on this set-theoretic characterization, we propose a blur-robust algorithm whose main step involves solving simple convex optimization problems. We do not assume any parametric form for the blur kernels, however, if this information is available it can be easily incorporated into our algorithm. Furthermore, using the low-dimensional model for illumination variations, we show that the set of all images obtained from a face image by blurring it and by changing the illumination conditions forms a bi-convex set. Based on this characterization, we propose a blur and illumination-robust algorithm. Our experiments on a challenging real dataset obtained in uncontrolled settings illustrate the importance of jointly modeling blur and illumination. [ABSTRACT FROM PUBLISHER]

Needle insertion procedures are commonly used for diagnostic and therapeutic purposes. In this paper, an image-guided control system is developed to robotically steer flexible needles with an asymmetric tip. Knowledge about needle deflection is required for accurate steering. Two different models to predict needle deflection are presented. The first is a kinematics-based model, and the second model predicts needle deflection that is based on the mechanics of needle–tissue interaction. Both models predict deflection of needles that undergo multiple bends. The maximum targeting errors of the kinematics-based and the mechanics-based models for 110-mm insertion distance using a \phi 0.5-mm needle are 0.8 and 1.7 mm, respectively. The kinematics-based model is used in the proposed image-guided control system. The control system accounts for target motion during the insertion procedure by detecting the target position in each image frame. Five experimental cases are presented to validate the real-time control system using both camera and ultrasound images as feedback. The experimental results show that the targeting errors of camera and ultrasound image-guided steering toward a moving target are 0.35 and 0.42 mm, respectively. The targeting accuracy of the algorithm is sufficient to reach the smallest lesions (\phi 2 mm) that can be detected using the state-of-the-art ultrasound imaging systems. [ABSTRACT FROM PUBLISHER]

Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ± 3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects. [ABSTRACT FROM PUBLISHER]

Permanent magnet linear motors are a type of linear motors that are generally used in precision motion control applications. However, the position of motor is easily disturbed by external force, disturbance, and variation in parameters of plant. Therefore, the construction of the high-precision linear motion system is a difficult task. This paper implements a modified disturbance observer and compensator, which includes a novel variable gain, to overcome the effects of unknown parameters of the motor, to minimize the effect of the disturbance, and to reduce the response time of the disturbance. This compensated linear motor is further controlled by the internal model reference control algorithm so that the position of the motor can be tracked with expected response precisely. The authors conducted the experiments and verified the feasibility of the high-precision positioning control. Compared with the case of normal disturbance compensator, the experimental results also illustrate the improvements of the novel variable gain, which reduces the response time toward the command signal and the external disturbance. [ABSTRACT FROM PUBLISHER]

In a target tracking situation, with clutter measurements and uncertain detections, true tracks often get lost due to temporal occlusions or unfavourable detection sequences, as well as the effects of measurement noise, clutter measurements, or any combination thereof. After a detection delay a new track is then initialized and subsequently confirmed for the same target, and the track becomes segmented. The Markov chain two (MC2) model for target existence propagation includes this temporal loss of detectability and often allows the track to continue through adverse conditions. This paper integrates the MC2 model with the integrated track splitting (ITS) algorithm resulting in a significant reduction of track segmentation. [ABSTRACT FROM PUBLISHER]

This paper concerns the correction of refracted propagation effects for airborne radar tracking. An algorithm based on the Kalman filter (KF) is developed that compensates for range and elevation refraction errors, which were analytically derived using a simplified tropospheric model. In particular, the refraction error model applies to a spherically stratified troposphere and does not include the effects of azimuthal refraction errors, small-scale fluctuations, or ducting. The effectiveness of the proposed tracking algorithm is assessed in the presence of tropospheric parameter mismatch and measurement noise. Both theoretical and numerical results are described for a medium range scenario, and a quasi-ellipsoidal racetrack is chosen for the air platform that carries the radar. [ABSTRACT FROM PUBLISHER]

In this paper, a two-time-scale coordination control method to mitigate wind power fluctuations using a battery energy storage system (BESS) is proposed. Two-time-scale maximal power fluctuation restrictions (MPFRs) are set for the combined output of the wind farm and the BESS: the maximal fluctuation of the combined power in any 1- and 30-min time window must be kept within \gamma 1\min\\% and \gamma 30\min \\% , respectively, of the rated power of the wind farm. A flexible first-order low-pass filter (FLF) with an optimization of time constant T_f is developed to limit the power fluctuation under restriction with smaller BESS capacity. Then, a coordination control method is developed on base of the FLF, which contains: 1) PSO-based time constant real-time optimizing algorithm; 2) remaining energy level feedback control; 3) two-time-scale coordination control strategy. Finally, an estimation of BESS capacity and power rating for a wind farm to achieve the MPFRs is presented, and the whole method is tested in a time-domain simulation system. [ABSTRACT FROM AUTHOR]

This paper presents a time-domain macromodel for lossy multiconductor transmission lines exposed to electromagnetic interference. The proposed algorithm is based on the recently developed passive method of characteristics, which provides an efficient mechanism to ensure the passivity of the macromodel for different line lengths. Numerical examples illustrate that when compared to other passive incident field coupling algorithms, the proposed method is efficient in modeling electrically long interconnects since delay extraction without segmentation is used to capture the frequency response. [ABSTRACT FROM AUTHOR]

This paper analyzes the thrust characteristics of the investigated permanent magnet linear synchronous motor (PMLSM) and discusses their differences with those of rotary motors. It shows that the main components of the thrust ripple are second, fourth, and sixth harmonics, which is produced by end-effect, not the 12th harmonic caused by cogging. The ripple suppression abilities of magnet step-skew method are analyzed through skew factors of thrust harmonics and effective electromagnetic thrust. The optimal step number and skew angle for PMLSM are studied with comparison to those of rotary motor. A 2-D FEM algorithm for the asymmetric PMLSM model analysis is investigated, with which the aforesaid skew step number selection and optimal skew angle are validated. [ABSTRACT FROM PUBLISHER]

This paper proposes a fuzzy control method combining with particle swarm optimization (PSO) algorithm for the flux weakening control of hybrid excitation synchronous motor (HESM). A total copper loss minimization model is established to determine the optimal field current, d-axis and q-axis currents in low speed region. In order to improve the dynamic characteristic and decrease the harmful influence of parameters variation on HESM's operation, a fuzzy control method is employed in high speed rang. Meanwhile, to improve the efficiency, the PSO algorithm is applied to current optimization during steady state operation. Simulation results show that higher efficiency HESM system can be implemented by adopting the proposed control method. [ABSTRACT FROM PUBLISHER]

This paper proposes an approach for the optimal design of fault-tolerant Petri net controllers using arc weights minimization. Given a system controller that is modeled as a Petri net, a fault-tolerant Petri net controller is obtained by embedding the given Petri net controller into a larger (redundant) Petri net controller that retains the properties of the original controller and allows the detection and identification of faults that may occur in the controller places. An algorithm is developed to systematically design this fault-tolerant Petri net controller in an optimal sense. The optimality is in terms of minimizing the sum of the entries in the input and output incident matrices of the fault-tolerant controller. Examples of the optimal design of fault-tolerant Petri net controllers for a manufacturing system are also provided to illustrate our approach. [ABSTRACT FROM PUBLISHER]

In this paper, an error surface-considered modeling algorithm for quarter-pixel motion estimation during video encoding is presented. We previously proposed two algorithms: a model-based quarter-pixel motion estimation (MBQME) algorithm and a hierarchical modelbased quarter-pixel motion estimation (HMBQME) algorithm. MBQME is an interpolation-free algorithm that has a minimum motion estimation time, while HMBQME has selective interpolation according to the decision process. Consequently, the peak signal-to-noise ratio (PSNR) for HMBQME is better than that of MBQME, but the motion estimation time is also increased. As an alternative method, we propose an error surface-considered modeling algorithm. In this scheme, the tendency of the error surface is first assessed. Using the strength of the edge at the error surface, we can classify the error surface region as plain or textured. For plain regions, interpolation-free and simplestructured modeling is appropriate for the quarter-pixel motion estimation method. In this case, we modified conventional mathematical modeling algorithm suitable for plain region. For textured regions, additional interpolation is needed for more accurate modeling. We calculate the half-pixel SAD values and perform more accurate modeling so as to find the best motion vector (MV). The experimental results show that the proposed scheme has better PSNR performance than any previous algorithms with minimum motion estimation time. [ABSTRACT FROM PUBLISHER]

When a catadioptric imaging system suffers from limited depth of field, a single image cannot capture all the objects with clear focus. To solve this problem, a set of multifocal images can be used to extend the depth of the field by fusing the best-focused image regions to an overall well-focused composite image. In this paper, we propose a novel model-based method that avoids the computational cost problem of previous extended-depth-of-field algorithms. On the basis of the special optical geometry properties of catadioptric systems, the proposed model describes the shapes of the best-focused image regions in multifocal images by a series of neighboring concentric annuluses. Then we propose a method to estimate the model parameters. On the basis of this model, an overall well-focused image is obtained by combining the best-focused regions with a fast and reliable online operation. Experiments on catadioptric images of a variety of different scenes and camera settings verify the validity of the model and the robust performance of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to automatic face modeling for realistic synthesis from an unknown face image, using a probabilistic face diffuse model and a generic face specular map. We construct a probabilistic face diffuse model for estimating the albedo and normals of the input face. Then, we develop a generic face specular map for estimating the specularity of face. Using the estimated albedo, normal, and specular information, we can synthesize the face under arbitrary lighting and viewing directions realistically. Unlike many existing techniques, our approach can extract both the diffuse and specular information of face without involving an intensive 3-D matching procedure. We conduct three different experiments to show our improvement over the prior art. First, we compare the proposed algorithm with previous techniques, including the state of the art, to demonstrate our achievement in realistic face synthesis. Moreover, we evaluate the proposed algorithm over nonautomatic face modeling techniques through a subjective user study. This evaluation is meaningful in that it tells us how far our results as well as others are from the real photograph in terms of the perceptual quality. Finally, we apply our face model for improving the face recognition performance under varying illumination conditions and show that the proposed algorithm is effective in enhancing the face recognition rate. Thanks to the compact representation and the effective inference scheme, our technique is applicable for many practical applications, such as avatar creation, digital face cloning, face normalization, de-identification and many others. [ABSTRACT FROM AUTHOR]

Dummy fill has been demonstrated to be an effective technique to reduce process variation and improve manufacturability for advanced integrated circuit (IC) designs. However, the computation load, often several days for a realistic IC design, is a significant portion of the cycle time for delivering first silicon on new or modified designs. In this paper, we propose a novel design flow and dummy-fill algorithm based on Boolean operations, which greatly improves computational efficiency and pattern density uniformity, and enables dummy generation to be combined with the mask-preparation Boolean operations performed by the mask-fabrication facility. Mask data preparation can be performed in parallel with dummy generation and post-dummy simulation checks at the design house, resulting in improved first-silicon cycle time. Experimental results demonstrate these benefits in the context of an advanced foundry process technology. [ABSTRACT FROM PUBLISHER]

Factors limiting and degrading the performance of a multiport-based receiver system for wideband signals are modeled and a suitable calibration approach is proposed in this paper. The proposed calibration approach uses a new model for linearization of diode power detectors suitable for wideband real (modulated) wireless signals. To verify the proposed model and calibration procedure, a 2–18-GHz wideband six-port-based receiver system is set up and its performance is verified using wireless signals having different bandwidth and modulation schemes. The new calibration algorithm improved the error vector magnitude (EVM) of the receiver system from 7.9% to 1.6% for a 64-QAM signal with a bandwidth of 2 MHz and a data rate of 12 Mb/s. To show the usefulness of the model for real communication signals, wideband code division multiple access (WCDMA) and wireless local area network (WLAN) signals are received and EVM of 4.7% and 3.4% are reported for the WCDMA and the WLAN signals, respectively. [ABSTRACT FROM AUTHOR]