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Imaging at a long distance often requires advanced image restoration algorithms to compensate for the distortions caused by atmospheric turbulence. However, unlike many standard restoration problems such as deconvolution, the forward image formation model of the atmospheric turbulence does not have a simple expression. Thanks to the Zernike representation of the phase, one can show that the forward model is a combination of tilt (pixel shifting due to the linear phase terms) and blur (image smoothing due to the high order aberrations). Confusions then arise between the ordering of the two operators. Should the model be tilt-then-blur, or blur-then-tilt? Some papers in the literature say that the model is tilt-then-blur, whereas more papers say that it is blur-then-tilt. This paper clarifies the differences between the two and discusses why the tilt-then-blur is the correct model. Recommendations are given to the research community. [ABSTRACT FROM AUTHOR]

Since the beginning of the altimeter mission TOPEX/Poseidon (T/P), followed by Jason-1 and Jason-2 on similar orbits, and many other missions on different orbits (ERS, EnviSat, etc.), mean sea level (MSL) products became essential for the comprehension of global ocean circulation. Since early in the T/P mission, a suspicious signal, having a period of near 59 days and amplitude of roughly 5 mm, was apparent in the Global MSL record. Compared with the 4–5-mm amplitude of the annual signal, the 59-day signal has understandably attracted attention. Moreover, the same signal has been subsequently detected in Jason-1 and later in Jason-2 MSLs. In 2010, the Ocean Surface Topography Science Team (OSTST) concluded this signal as the aliasing of a higher frequency error inherited from the tide model correction: the semi-diurnal wave S2. The source of this error was mainly attributed to T/P measurements, which were assimilated in ocean tide models. When these models are used in the computation of T/P MSL, most of the error cancels. However, this error is communicated to Jason-1 and Jason-2 MSLs. In order to gather and publish the OSTST analyses on this matter, this paper first attempts to list the myriad possibilities for the puzzling 59-day error in MSL. Then, this paper goes deeper into the description of the main contributor to this list: the tide models error. Indeed, since 2010, considerable efforts have been undertaken within the ocean tide community in order to correct ocean tide S2-waves from this error, particularly in the Goddard Ocean Tide (GOT) and finite element solution (FES) latest versions. Comparing several GOT and FES versions and a pure hydrodynamic tide model, this paper assesses, quantifies, and describes a reduction of the MSL 59-day error thanks to the latest releases. These analyses also confirm that a large part of this error has its origins in the T/P mission and has contaminated ocean tide solutions and Jason-1 and Jason-2 MSLs. They also suggest that ocean tide is not the only possible vector. Jason-1 and Jason-2 MSLs contain additional 59-day error—though to a lesser extent—that may either come from the measurements themselves or from another vector. [ABSTRACT FROM AUTHOR]

Existence of haze significantly degrades visual quality and hence negatively affects the performance of visual surveillance, video analysis, and human–machine interaction. To remove haze from a visual signal, in this paper, we propose a generative adversarial network for visual haze removal called HRGAN. HRGAN consists of a generator network and a discriminator network. A unified network jointly estimating transmission maps, atmospheric light, and haze-free images (called UNTA) is proposed as the generator network of HRGAN. Instead of being optimized by minimizing the pixel-wise loss, HRGAN is optimized by minimizing a novel loss function consisting of pixel-wise loss, perceptual loss, and adversarial loss produced by a discriminator network. Classical model-based image dehazing algorithms consist of three separate stages: 1) estimating transmission map; 2) estimating atmospheric light; and 3) restoring haze-free image by using an atmospheric scattering model to process the transmission map and atmospheric light. Such a separate scheme is not guaranteed to achieve optimal results. On the contrary, UNTA performs transmission map estimation and atmospheric light estimation simultaneously to obtain joint optimal solutions. The experimental results on both synthetic and real-world image databases demonstrate that HRGAN outperforms the state-of-the-art algorithms in terms of both effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

This paper presents an improved magnetic circuit (MC) model considering the leakage, cross coupling, and saturation effects for the performance analysis of an integrated 3 degrees of freedom magnetic bearing (3-DOF MB). Compared with the conventional MC model, this paper analyzes the permanent-magnet bias field, radial and axial control current fields together. By using this improved MC model, it reveals the cross-coupling effect between radial and axial directions in such an integrated 3-DOF MB. The stiffnesses of radial force are significantly influenced by the axial control current, while the stiffnesses of the axial force are independent of the radial control current. Its accuracy is verified by the 3-D finite-element method. [ABSTRACT FROM AUTHOR]

This paper introduces a new aerodynamic-traction principle to handle delicate and clean products, such as silicon wafers, glass sheets, or flat foodstuffs. The product is carried on a thin air cushion and transported along the system by induced airflows. This induced airflow is an indirect effect of strong vertical air jets that pull the surrounding fluid. This paper provides a qualitative explanation of the operating principles and a description of the experimental device. First experimental results with active control are presented. The maximum velocity and acceleration that can be obtained for the considered device geometry meet the requirements for industrial applications. [ABSTRACT FROM PUBLISHER]

This is the second of two papers that quantify the high added value of frequent 3-D radar observations of the atmosphere to capture the dynamics of weather systems. Recent advances in small-satellite and radar technologies, such as the “Radar in Cubesat” developed at the Jet Propulsion Laboratory, are paving the way for the design of convoys of spaceborne radars that can directly observe the evolution of severe weather at very fine temporal scales. The analyses presented here are to establish the relation between such observations to the underlying cloud variables and processes, and to quantify the sensitivity to the different physical and instrument parameters. In this paper, we quantify the uncertainty in the relation between the measured radar reflectivities Z and their time derivatives d_{t} Z , on one hand, and the underlying rate of change of the condensed-water mass M$ , and fluxes of dry and moist air in convection, on the other hand. The uncertainties are due to the variability of the atmospheric parameters as well as the constraints of an observation strategy that would use pairs of spaceborne instruments. We specifically analyze the sensitivities for pairs of satellites, each carrying a Ka-band profiling radar. Our simulations show that, with a convoy of two spacecraft separated by ~90 s, each with a pointing accuracy of ~0.025° in rms error, a sensitivity of 17 dBZ and a precision of 1 dBZ, the proposed observation strategy would capture more than 70% of the tropical convection between 5 and 10 km of altitude and resolve the air-mass and condensed-water fluxes. [ABSTRACT FROM AUTHOR]

In an effort to study and characterize scattering mechanisms of debris particles in tornadoes, a numerical polarimetric radar emulator was developed. This paper is primarily motivated by attempts to explain radar observations near tornadoes. One such observation is the regions of negative differential reflectivity, which have been found near tornadoes but they are yet to be explained physically. There are hypotheses that suggest common debris alignment and/or dominant scattering from objects with high radar-cross-section (RCS) values that cause negative ZDR , but they are extremely challenging to verify due to the inherent danger near the vicinity of tornadoes. It is, however, possible to numerically construct the scenes through representative simulations to verify the plausible causes. This serves as our primary motivation to develop the radar emulator. The novel aspects of this paper are the realistic trajectory derivation, which is based on a physical air-drag model, and the representative diversity of RCS contributions from each debris object, developed through realistic polarimetric RCS modeling and anechoic chamber measurements. [ABSTRACT FROM PUBLISHER]

The paper [1] reports on comparative experiments on a triggered-gap electrode used as an early streamer emission air terminal, with some equivalent circuit analysis of the triggering circuit and simplified electric field calculations. [ABSTRACT FROM PUBLISHER]

This paper focuses on broadband electromagnetic (EM) modeling of composite materials. A homogenization method is carried out by combining finite element calculations with a numerical inversion technique: first, the transmission and reflection coefficients of the composite plate are computed over a large frequency band (up to 50 GHz) using a 3-D finite-element method. Then an inversion technique is applied in order to extract EM properties. This approach extends the application domain of classical homogenization methods by enabling the modeling of different types of composites. [ABSTRACT FROM AUTHOR]

The main challenging problems in ocean current retrieval from along-track interferometric (ATI)-synthetic aperture radar (SAR) are phase calibration and wave bias removal. In this paper, a method based on differential InSAR (DInSAR) technique for correcting the phase offset and its variation is proposed. The wave bias removal is assessed using two different Doppler models and two different wind sources. In addition to the wind provided by an atmospheric model, the wind speed used for wave correction in this work is extracted from the calibrated SAR backscatter. This demonstrates that current retrieval from ATI-SAR can be completed independently of atmospheric models. The retrieved currents, from four TanDEM-X (TDX) acquisitions over the Öresund channel in the Baltic Sea, are compared to a regional ocean circulation model. It is shown that by applying the proposed phase correction and wave bias removal, a good agreement in spatial variation and current direction is achieved. The residual bias, between the ocean model and the current retrievals, varies between 0.013 and 0.3 m/s depending on the Doppler model and wind source used for wave correction. This paper shows that using SAR as a source of wind speed reduces the bias and root-mean-squared-error (RMSE) of the retrieved currents by 20% and 15%, respectively. Finally, the sensitivity of the sea current retrieval to Doppler model and wind errors are discussed. [ABSTRACT FROM AUTHOR]

In recent years, learning-based single image dehazing networks have been comprehensively developed. However, performance improvement is limited due to domain shift between trained synthetic hazy images and untrained real-world hazy images. To alleviate this issue, this paper proposes a real-world dehazing targeted training scheme which nearly realizes paired real-world data training. As a result, a Twofold Multi-scale Generative Adversarial Network (TMS-GAN) consisting of a Haze-generation GAN (HgGAN) and a Haze-removal GAN (HrGAN) is designed. HgGAN attributes real haze properties to synthetic images and HrGAN removes haze from both synthetic and generated fake realistic data under supervision. Thus, the proposed method can better adapt to real-world image dehazing using this cooperative training scheme. Meanwhile, several structural advances of TMS-GAN also improve dehazing performance. Specifically, a haze residual map based on atmospheric scattering model is deduced in HgGAN for fake realistic data generation. The dual-branch generator in HrGAN draws attention to detail restoration by one branch along with another color-branch. A plug-and-play Multi-attention Progressive Fusion Module (MAPFM) is proposed and inserted in both HgGAN and HrGAN. MAPFM incorporates multi-attention mechanism to guide multi-scale feature fusion in a progressive manner, in which Adjacency-attention Block (AAB) can capture contributing features of each level and Self-attention Block (SAB) can establish non-local dependency of feature fusion. Experiments on mainstream benchmarks show that the proposed framework is superior especially on real-world hazy images among single image dehazing methods. [ABSTRACT FROM AUTHOR]

The availability of multiangular information from the NASA Multi-angle Imaging SpectroRadiometer (MISR) instrument provides an excellent opportunity for the characterization of surface anisotropy, which can be used for improving surface albedo estimation. However, the MISR data have been reported with large uncertainties and data gaps due to inaccurate aerosol estimation and/or cloud masking limiting its otherwise broader applications. To mitigate these issues, two approaches were proposed to estimate land surface albedo directly from surface reflectance (LSA_sfc) and Top-of-Atmosphere reflectance (LSA_toa), respectively. As a further development of the traditional albedo algorithms, this is the first attempt to simultaneously utilize multispectral and multiangular information in surface albedo estimation without any prior constraining information. Validations at AmeriFlux sites show that the proposed algorithms can achieve accuracies similar to that of the MISR product with respective bias and RMSE of 0.004 and 0.032 for LSA_sfc and 0.005 and 0.032 for LSA_toa algorithms. We found that the LSA_toa algorithm can significantly reduce data gaps and provide accurate surface albedo retrievals with two to three times more valid data than the current MISR product. In addition, these approaches can be easily applied to other optical sensors to produce accurate and gap-free clear-sky surface albedo estimations. The results of this paper also highlight the importance of having two to three simultaneous observations with sufficient angular sampling, which can improve albedo accuracy and reduce data gaps. [ABSTRACT FROM PUBLISHER]

Topographic effects on canopy reflectance play a pivotal role in the retrieval of surface biophysical variables over rugged terrain. In this paper, we proposed a new canopy anisotropic reflectance model for discrete forests, Geometric Optical and Mutual Shadowing and Scattering-from-Arbitrarily-Inclined-Leaves model coupled with Topography (GOSAILT), which considers the effects of slope, aspect, geotropic nature of tree growth, multiple scattering, and diffuse skylight. GOSAILT-simulated areal proportions of four scene components (i.e., sunlit crown, shaded crown, sunlit background, and shaded background) were evaluated using the Geometric Optical model for Sloping Terrains (GOST) model. The canopy reflectances simulated by GOSAILT were validated against two reflectance data sets: Discrete anisotropic radiative transfer (DART) simulations and wide-angle infrared dual-model line/area array scanner (WIDAS) observations. Compared with a horizontal surface, the forest canopy reflectance over a steep slope (60°) is significantly distorted with absolute (relative) bias values of 0.048 (79.60%) and 0.056 (12.02%) for the red and near-infrared (NIR) bands, respectively. The GOSAILT-simulated component areal proportions show close agreements with GOST. Moreover, GOSAILT simulations have high overall accuracy (red band: coefficient of determination ($R^{2}) = 0.96$ ; root-mean-square error (RMSE) = 0.003; and mean absolute percentage error (MAPE) = 3.91%; and NIR band: $R^{2} = 0.78$ , RMSE = 0.019; MAPE = 3.94%) when compared with the DART simulations. These extensive validations indicate good performances of GOSAILT in canopy reflectance simulations over sloped surfaces. [ABSTRACT FROM AUTHOR]

The airborne Operation IceBridge and spaceborne CryoSat-2 missions observe polar sea ice at different spatial and temporal scales as well as with different sensor suites. Comparison of data products from IceBridge and CryoSat-2 is complicated by the fact that they use different geophysical corrections: reference ellipsoid, geoid model, tide model, and atmospheric corrections to derive surface elevation and sea-ice freeboard. In this paper, we compare sea-ice surface elevation and freeboard using eight coincident CryoSat-2, Airborne Topographic Mapper (ATM), and Land, Vegetation, and Ice Sensor (LVIS) observations with direct IceBridge underflights of CryoSat-2 ground tracks. We apply identical geophysical corrections to CryoSat-2 and IceBridge data to eliminate elevation biases due to these differences and focus on differences due to retracker performance. The IceBridge ATM and LVIS elevation and freeboard and Snow Radar snow depth data sets are averaged to each CryoSat-2 footprint for comparison. With snow depth measurements, we are able to compare elevations and freeboards at the snow/ice interface for five different CryoSat-2 retrackers (ESA, GSFCv1, AWI, JPL, and GSFCv2) and IceBridge. The overall mean of freeboard differences between GSFCv2, ESA, AWI, JPL retrackers, and ATM are in agreement within 0.05 m. However, the five different CryoSat-2 retrackers show distinct differences in mean elevation over leads and over floes. This suggests that the physical interpretation of the different retrackers needs to be considered depending on usage, for example, elevations from CryoSat-2 retrackers need to be carefully calibrated before comparing with elevation from other satellites for long-term surface elevation trends. [ABSTRACT FROM AUTHOR]

Estimation of daily downward shortwave radiation (DSR) is of great importance in global energy budget and climatic modeling. The combination of satellite-based instantaneous measurements and temporal extrapolation models is the most feasible way to capture daily radiation variations at large scales. However, previous studies did not pay enough attention to topographic effects and simple temporal extrapolation methods were applied directly to rugged terrains which cover a large amount of the land surface. This paper, divided into two parts, aims at analyzing the topographic uncertainties of existing models and proposing a better method based on a mountain radiative transfer (MRT) model to calculate daily DSR. As the first part, this paper analyze the spatiotemporal variations of DSR influenced by topographic effects and checks the applicability of three temporal extrapolation methods on cloud-free days. Considering that clouds also have a strong influence on solar radiation, cloud-free days are chosen for targeted analysis of topographic effects on DSR. Three indices, the coefficient of variation, entropy-based dispersion coefficient (CH), and sill of semivariogram, are put forward to give a quantitative description of spatial heterogeneity. Our results show that the topography can dramatically strengthen the spatial heterogeneity of DSR. The index, CH, has an advantage for quantifying spatial heterogeneity as it offers a tradeoff between accuracy and efficiency. Spatial heterogeneity distorts the daily variation of DSR. Application of extrapolation methods in rugged terrains leads to overestimation of daily average DSR up to 60 W/m2 and a maximum 200 W/m2 error of instantaneous DSR on cloud-free days. This paper makes a quantitative analysis of topographic effects under different spatiotemporal conditions, which lays the foundation for developing a new extrapolation method. [ABSTRACT FROM AUTHOR]

We propose an airborne collapse capacitive micromachined ultrasonic transducer (CMUT) as a practical viable ultrasound transducer capable of providing a stable performance at the off-resonance frequencies. Traditional practice is to bias the CMUT plate close to collapse voltage to achieve high coupling coefficient and sense the incoming ultrasound as an open-circuit receive voltage signal of the transducer or short-circuit receive current (SCRC). Maintaining CMUT plate in the vicinity of collapse threshold is rather difficult. In this paper, an analytic approach to design an airborne collapsed-mode CMUT for maximum off-resonance sensitivity is presented. We use small-signal circuit model to evaluate the performance of a collapsed CMUT for varying operating conditions. CMUT operational parameters that yield the highest off-resonance SCRC are directly obtained from performance design curves. Collapsed CMUT plate is then biased in a critical biasing region that produces a stable and maximum off-resonance sensitivity. We experimentally verify and measure a stable sensitivity of a fabricated collapsed CMUT cell of −60 dB V/Pa at 100 kHz when biased between 50 to 65 V. We characterize our linear circuit model performance against the measured performance of collapsed CMUT in air within 4-dB tolerance. [2018-0058] [ABSTRACT FROM AUTHOR]

In this paper, we tackle the problem of single image dehazing with a convolutional neural network. Within this network, we develop a multi-level fusion module to utilize both low-level and high-level features. The low-level features help to recover finer details, and the high-level features discover abstract semantics. They are complementary in the restoring of clear images. Moreover, a Residual Mixed-convolution Attention Module (RMAM) with an attention block is proposed to guide the network to focus on important features in the learning process. In this RMAM, group convolution, depth-wise convolution, and point-wise convolution are mixed, and thus it is much faster than its counterparts. With these two modules, we thus have an end-to-end network without explicitly estimating the atmospheric light intensity and the transmission map in the classical atmosphere scattering model. Both qualitative and quantitative experimental studies are carried out on public datasets including RESIDE, DCPDN-TestA, and the real-world dataset. The extensive results demonstrate both the effectiveness and efficiency of the proposed solution to single image dehazing. [ABSTRACT FROM AUTHOR]

Haze caused by atmospheric scattering and absorption would severely affect scene visibility of an image. Thus, image dehazing for haze removal has been widely studied in the literature. Within a hazy image, haze is not confined in a small local patch/position, while widely diffusing in a whole image. Under this circumstance, global context is a crucial factor in the success of dehazing, which was seldom investigated in existing dehazing algorithms. In the literature, the global context (GC) block has been designed to learn point-wise long-range dependencies of an image for global context modeling; however, patch-wise long-range dependencies were ignored. To image dehazing, patch-wise long-range dependencies should be highlighted to cooperate with patch-wise operations of image dehazing. In this paper, we first extend the point-wise GC into a Pyramid Global Context (PGC), which is a multi-scale GC, after undergoing the pyramid pooling. Thus, patch-wise long-range dependencies can be explored by the PGC. Then, the proposed PGC is plugged into a U-Net, getting an attentive U-Net. Further, the attentive U-Net is optimized by importing ResNet’s shortcut connection and dilated convolution. Thus, the finalized dehazing model can explore both long-range and patch-wise context dependencies for global context modeling, which is crucial for image dehazing. The extensive experiments on synthetic databases and real-world hazy images demonstrate the superiority of our model over other representative state-of-the-art models from both quantitative and qualitative comparisons. [ABSTRACT FROM AUTHOR]

An image can be decomposed into two parts: the basic content and details, which usually correspond to the low-frequency and high-frequency information of the image. For a hazy image, these two parts are often affected by haze in different levels, e.g., high-frequency parts are often affected more serious than low-frequency parts. In this paper, we approach the single image dehazing problem as two restoration problems of recovering basic content and image details, and propose a Dual-Path Recurrent Network (DPRN) to simultaneously tackle these two problems. Specifically, the core structure of DPRN is a dual-path block, which uses two parallel branches to learn the characteristics of the basic content and details of hazy images. Each branch consists of several Convolutional LSTM blocks and convolution layers. Moreover, a parallel interaction function is incorporated into the dual-path block, thus enables each branch to dynamically fuse the intermediate features of both the basic content and image details. In this way, both branches can benefit from each other, and recover the basic content and image details alternately, therefore alleviating the color distortion problem in the dehazing process. Experimental results show that the proposed DPRN outperforms state-of-the-art image dehazing methods in terms of both quantitative accuracy and qualitative visual effect. [ABSTRACT FROM AUTHOR]

Atmospheric scattering model (ASM) is one of the most widely used model to describe the imaging processing of hazy images. However, we found that ASM has an intrinsic limitation which leads to a dim effect in the recovered results. In this paper, by introducing a new parameter, i.e., light absorption coefficient, into ASM, an enhanced ASM (EASM) is attained, which can address the dim effect and better model outdoor hazy scenes. Relying on this EASM, a simple yet effective gray-world-assumption-based technique called IDE is then developed to enhance the visibility of hazy images. Experimental results show that IDE eliminates the dim effect and exhibits excellent dehazing performance. It is worth mentioning that IDE does not require any training process or extra information related to scene depth, which makes it very fast and robust. Moreover, the global stretch strategy used in IDE can effectively avoid some undesirable effects in recovery results, e.g., over-enhancement, over-saturation, and mist residue, etc. Comparison between the proposed IDE and other state-of-the-art techniques reveals the superiority of IDE in terms of both dehazing quality and efficiency over all the comparable techniques. [ABSTRACT FROM AUTHOR]

The simulation of magnetically geared electrical machines using the finite element method is an especially demanding task when movement has to be considered. Several methods that facilitate movement exist. In this paper, two of these methods, the macro air-gap element (AGE) and the moving band (MB) are applied in a time-stepped static simulation of a magnetically geared machine (MGM). The methods are evaluated in terms of accuracy and computational efficiency, vitally important factors for numerical optimization. The implementation of both methods exploit the multi-core architecture of modern CPUs to solve several steps in parallel, drastically reducing the simulation time. Nevertheless, the computational cost of the AGE is prohibitively high in the simulation of MGMs. The MB is computationally efficient and good accuracy can be achieved using a multilayer approach. [ABSTRACT FROM PUBLISHER]

In 2016, three new realizations of the International Terrestrial Reference System (ITRS), namely, DTRF2014, ITRF2014, and JTRF2014, have been released. In this paper, we evaluate these ITRS realizations for precise orbit determination of ten high and low Earth orbiting geodetic satellites using satellite laser ranging (SLR) observations. We show the reduction of observation residuals and estimated range biases, when using these new ITRS realizations, as compared with the previous ITRS realization for SLR stations—SLRF2008. Thus, the mean SLR root-mean-square (RMS) fits reduce (improve), on average over all satellites tested, by 3%, 3.6%, 8.1%, and 7.7% at 1993.0–2015.0, when using ITRF2014, DTRF2014, and DTRF2014 with non-tidal loading (NTL), and JTRF2014 realizations, respectively. The improvement of the RMS fits is even larger at 2015.0–2017.0: 14% and 15.5% using ITRF2014 and DTRF2014, respectively. For the altimetry satellite Jason-2, we found improvements in the RMS and mean of the sea surface height crossover differences with the new ITRS realizations, as compared with SLRF2008. We show that JTRF2014, after an editing done for SLR stations Conception and Zimmerwald, and DTRF2014 with NTL corrections result in the smallest RMS and absolute mean fits of SLR observations indicating the best performance among the ITRS realizations tested, while using SLRF2008 and ITRF2014 causes a 0.2–0.3 mm/y trend in the mean of SLR fits at 2001.0–2017.0. [ABSTRACT FROM AUTHOR]

The fundamental performance of contact/clearance sensor, namely embedded contact sensor (ECS), is addressed in this paper. Both simulation and experiment results revealed that ECS is a promising sensor for low clearance and high reliability at subnanometer regime. The ECS dc signal intrinsically comes from multiple sources including TFC heater, air-bearing surface cooling, and friction heating at head/disk contact. Both ECS dc and ac signals detect head/disk contact. The dc signal comes from the sensor resistance change due to friction heating at contact, but the ac signal is dominated by spacing modulation caused by air-bearing vibration, and partially from the pulse-like friction heating. ECS ac signal responds significantly to disk microwaviness at narrow clearance region. Furthermore, ECS could detect asperities, pit, and lube mogul. The mechanism for asperity detection is friction heating. The mechanism for pit detection is worse cooling when sensor flying over the pit. That for mogul detection is better cooling at narrower spacing when the sensor is flying over the mogul. [ABSTRACT FROM PUBLISHER]

Transactive control is a type of distributed control strategy that uses market mechanisms to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building heating, ventilation, and air-conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from systems engineering building (SEB) located on our Pacific Northwest National Laboratory campus. We next present a transactive control market structure for commercial building HVAC systems, and describe its agent bidding and market clearing strategies. Several case studies are performed in a simulation environment using building controls virtual test bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak shaving, load shifting, and strategic conservation for commercial building HVAC systems. [ABSTRACT FROM AUTHOR]

In this paper, an analytical field calculation model is built for surface inset permanent magnet (SIPM) machines with high saliency ratio. The high saliency ratio of SIPM machine is obtained using unequal $d$ - $q$ axis air-gap length based on the SIPM rotor structure. High saliency ratio can produce large reluctance torque and wide speed range. To get a fast and exact knowledge of flux distribution and operation parameters of the SIPM machine with high saliency ratio, the field solving domain is divided into five subdomains, i.e., stator slots, stator slot openings, air-gap, rotor air slots, and rotor magnets. The vector potential in each subdomain is governed by Maxwell’s equation and can be solved using the variable separation method and boundary conditions between adjacent subdomains. In addition, the cogging torque, back electromotive force (EMF), inductance, output torque, and unbalanced magnetic force (UMF) are calculated based on the field model. All the field calculation results are compared with those of finite element analysis (FEA), and it is shown that analytical field calculation model is fast and accurate. Furthermore, the effects of $q$ -axis air-gap length and pole arc ratio on machine parameters, such as cogging torque, back EMF, saliency ratio, output torque, and UMF, are also investigated using the analytical field calculation model. [ABSTRACT FROM PUBLISHER]

This paper proposes a nonlinear adaptive lumped parameter magnetic circuit (LPMC) model for a new spoke-type fault-tolerant permanent-magnet (ST-FTPM) brushless motor. The LPMC method, which reduces the total computational time greatly, can be used as a finite-element method (FEM) assistant design tool. Hence, it is used to calculate the flux linkage, back-electromotive force (back-EMF), inductance, and torque performance of the ST-FTPM motor. The novelty of this paper is to predict short-circuit current based on the developed LPMC model. Meanwhile, in order to ensure the analytical accuracy, the magnetic saturation is considered in the model design. The effectiveness of the presented LPMC model is verified by FEM and the experiments. [ABSTRACT FROM PUBLISHER]

Supporting different stakeholder viewpoints across the product lifecycle requires semantic richness to represent product-related information and enable multiview engineering simulations. This paper proposes a multilevel product modeling framework enabling stakeholders to define product models and relate them to physical or simulated instances. The framework is defined within the Model-Driven Architecture using the multilevel (data, model, metamodel) approach. The data level represents real-world products, the model level describes models (product models) of real-world products, and the metamodel level describes models of the product models. The metamodel defined in this paper is specialized from a web ontology language enabling product designers to express the semantics of product models in an engineering-friendly way. The interactions between these three levels are described to show how each level in the framework is used in a product engineering context. A product design scenario and user interface for the product metamodel is provided for further understanding of the framework. [ABSTRACT FROM PUBLISHER]

In the early days of computer control, only one centralized computer was responsible for executing the algorithms. Increasingly, computer control algorithms reside inside individual system components in a distributed fashion. Variable camshaft timing (VCT) is an appealing feature for automotive engines because it allows optimization of the cam timing over a wide range of operating conditions. In this paper, a method to distribute the discrete multiple-input mutiple-output controller for the VCT engine to improve the component swapping modularity of the VCT actuator and the EGO sensor components using network communications is presented. First, a discrete LQG controller is designed, and then this controller is distributed to the engine control unit, the VCT controller, and the EGO sensor controller in order to maximize the component swapping modularity of the system. A control oriented pre-optimization technique, which simplifies the optimization problem, and a candidate solution was devised to maximize component modularity. [ABSTRACT FROM PUBLISHER]

This brief paper describes the development of a pulse compression probing algorithm for real-time monitoring of nonlinear dynamic systems. The probing outputs of a system being monitored are estimates of the sequences of Markov parameters at the current operating point. By imposing signal to noise ratios at both the controlled outputs and the probing outputs, the probing inputs are designed to be non-intrusive and with the intention that the resulting probing outputs are unaffected by other applied signals to the system. The probing algorithm is implemented on a Virtex-5 field-programmable gate-array evaluation platform to expedite real-time processing, and is applied to monitoring the health of the NASA Generic Transport Aircraft Model (GTM). Samples of probing output residuals are evaluated using the Hotelling's T^2-test for change detection when significant noise is present in the system. This brief paper focuses its discussion on the method of rapid collection of independent samples to reduce detection delay. [ABSTRACT FROM PUBLISHER]

The advent of routine collection of high-quality digital photography provides for traditional uses, as well as “remote sensing” uses such as the monitoring of environmental indicators. A well-devised monitoring system, based on consistent data and methods, provides the opportunity to track and communicate changes in features of interest in a way that has not previously been possible. Data that are geometrically and radiometrically consistent are fundamental to establishing systems for monitoring. In this paper, we focus on models for the radiometric calibration of mosaics consisting of thousands of images. We apply the models to the data acquired by the Australian Commonwealth Scientific and Industrial Research Organisation and its partners as part of regular systematic acquisitions over the city of Perth for a project known as Urban Monitor. One goal of the project, and hence the model development, is to produce annually updated mosaics calibrated to reflectance at 0.2-m ground sample distance for an area of approximately 9600 \km^2. This equates to terabytes of data and, for frame-based instruments, tens of thousands of images. For the experiments considered in this paper, this requires mosaicking estimates derived from 3000 digital photographic frames, and the methods will shortly be expanded to 30 000+ frames. A key part of the processing is the removal of spectral variation due to the viewing geometry, typically attributed to the bidirectional reflectance distribution function (BRDF) of the land surface. A variety of techniques based on semiempirical BRDF kernels have been proposed in the literature for correcting the BRDF effect in single frames, but mosaics with many frames provide unique challenges. This paper presents and illuminates a complete empirical radiometric calibration method for digital aerial frame mosaics, based on a combined model that uses kernel-based techniques for BRDF correction and incorporates additive and multiplicative terms for correcting other effects, such as variations due to the sensor and atmosphere. Using ground truth, which consists of laboratory-measured white, gray, and black targets that were placed in the field at the time of acquisition, we calculate the fundamental limitations of each model, leading to an optimal result for each model type. We demonstrate estimates of ground reflectance that are accurate to approximately 10%, 5%, and 3% absolute reflectances for ground targets having reflectances of 90%, 40%, and 4%, respectively. [ABSTRACT FROM AUTHOR]

Estimating the contribution of the forests to carbon sequestration is commonly done by applying forest growth models. Such models inherently use field observations such as leaf area index (LAI), whereas a relevant information is also available from remotely sensed images. This paper aims to improve the LAI estimated from the forest growth model [physiological principals predicting growth (3-PG)] by combining these values with the LAI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. A Bayesian networks (BNs) approach addresses the bias in the 3-PG model and the noise of the MODIS images. A novel inference strategy within the BN has been developed in this paper to take care of the different structures of the inaccuracies in the two data sources. The BN is applied to the Speulderbos forest in The Netherlands, where the detailed data were available. This paper shows that the outputs obtained with the BN were more accurate than either the 3-PG or the MODIS estimate. It was also found that the BN is more sensitive to the variation of the LAI derived from MODIS than to the variation of the LAI 3-PG values. In this paper, we conclude that the BNs can improve the estimation of the LAI values by combining a forest growth model with satellite imagery. [ABSTRACT FROM AUTHOR]

Single image haze removal is an extremely challenging problem due to its inherent ill-posed nature. Several prior-based and learning-based methods have been proposed in the literature to solve this problem and they have achieved visually appealing results. However, most of the existing methods assume constant atmospheric light model and tend to follow a two-step procedure involving prior-based methods for estimating transmission map followed by calculation of dehazed image using the closed form solution. In this paper, we relax the constant atmospheric light assumption and propose a novel unified single image dehazing network that jointly estimates the transmission map and performs dehazing. In other words, our new approach provides an end-to-end learning framework, where the inherent transmission map and dehazed result are learned jointly from the loss function. The extensive experiments evaluated on synthetic and real datasets with challenging hazy images demonstrate that the proposed method achieves significant improvements over the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The paper comprises a new systematic approach to determine the critical ambient field needed for positive streamer propagation in nonuniform field gaps. It is shown that such critical streamer penetration field is a function of the basic value previously established for uniform field gaps and the degree of ambient field nonuniformity. The latter quantity is defined by the ratio of the maximum to mean ambient electric fields along the streamer propagation path, which can be determined either analytically or by charge simulation. Such functional dependence of the critical streamer penetration gradient on field nonuniformity has been determined for different rod topologies of rod-plane gap as well as for single and bundle conductor plane gaps. The model is used to determine critical streamer penetration fields and streamer lengths under different impulse voltage levels for different gap configurations and for a tall ground structure exposed to ambient impulse field. The findings of this method are compared to available experimental results and the agreement is found satisfactory. [ABSTRACT FROM AUTHOR]

The goal of this paper is to identify the parameter set of a given electrical machine. The identification method is based on data assimilation coupled with the finite-element method. Data assimilation method is an optimization approach that limits the space of candidate parameter sets by centering it on those of the ideal machine. An application to an electrical machine is presented based on the analysis of flux sensor signals. The methodology is validated using twin experiments that consider simulated data and tested considering the measurements extracted from the real alternator. [ABSTRACT FROM AUTHOR]

Nowadays, hard disk drive filling with helium has emerged to achieve highly stable magnetic recording. The bearing force in helium is different from that in air. This paper uses the 3-D direct simulation Monte Carlo method to investigate the bearing force over bit-patterned media in the filling gases of air and helium under different conditions, including groove depth, ambient temperature, slider surface temperature, rotation speed of the disk, and different velocity losses during the collision process between the gas molecules and the slider. [ABSTRACT FROM AUTHOR]

In this paper, through-silicon-via (TSV) dispensing is introduced to address the underfill challenge for a 3-D chip stack package. An edge flood failure would form if the underfill flow breaks through the planar sidewalls of a 3-D package. The edge flood failure could lead to an incomplete underfill and the occupation of a huge area on the substrate. In order to avoid an edge flood, the encapsulant pressure around the chip edges cannot exceed the limit equilibrium pressure. The TSVs in the stacked chips should be aligned in the vertical direction, because this aligned configuration has the lowest risk of forming an edge flood. In order to find a tradeoff between the short filling time and the low risk of forming an edge flood, an optimized TSV pattern, including central and outer TSVs, is proposed for the underfill of a 3-D chip stack package. The central TSVs allow a constant flow rate to obtain a fast filling effect. The outer TSVs allow free droplets to eliminate the potential edge flood during the underfilling of the area around the chip edges. The test vehicle was a four-layer die/interposer stack package. The effect of the TSV underfill was inspected by acoustic scanning and cross sectioning. The inspection results showed that the underfill was completed without voids and the solder joints were well covered by the encapsulant. [ABSTRACT FROM PUBLISHER]

Atmospheric scattering model (ASM) has been widely used in hazy image restoration. However, the recovered albedo might deviate from the real scene once the input hazy image cannot fully satisfy the model’s assumptions such as the homogeneous atmosphere and even illumination. In this paper, we break these limitations and redefine a more reliable ASM (RASM) that is extremely adaptable for various practical scenarios. Benefiting from RASM, a simple yet effective Bayesian dehazing algorithm (BDPK) is further proposed based on the prior knowledge. Our strategy is to convert the single image dehazing problem into a maximum a-posteriori probability one that can be approximated as an optimization function using the existing priori constraints. To efficiently solve this optimization function, the alternating minimizing technique is introduced, which enables us to directly restore the scene albedo. Experiments on a number of challenging images reveal the power of BDPK on removing haze and verify its superiority over several state-of-the-art techniques in terms of quality and efficiency. [ABSTRACT FROM AUTHOR]

In this paper, a three-dimensional (3-D) path-following control design for an underactuated stratospheric airship is proposed based on the parameterized path description. The desired attitude, velocity, and the path parameter updating law are obtained by employing the guidance-based path-following principle. The resultant system possesses a cascaded structure, which consists of a guidance loop, an attitude stabilization loop, and a velocity tracking loop. The stability analysis shows that the path-following error and all states of the closed-loop system are ultimately uniformly bounded. Simulation results demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domain experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings. [ABSTRACT FROM PUBLISHER]

Coastlines, shoals, and reefs are some of the most dynamic and constantly changing regions of the globe. The emergence of high-resolution satellites with new spectral channels, such as the WorldView-2, increases the amount of data available, thereby improving the determination of coastal management parameters. Water-leaving radiance is very difficult to determine accurately, since it is often small compared to the reflected radiance from other sources such as atmospheric and water surface scattering. Hence, the atmospheric correction has proven to be a very important step in the processing of high-resolution images for coastal applications. On the other hand, specular reflection of solar radiation on nonflat water surfaces is a serious confounding factor for bathymetry and for obtaining the seafloor albedo with high precision in shallow-water environments. This paper describes, at first, an optimal atmospheric correction model, as well as an improved algorithm for sunglint removal based on combined physical and image processing techniques. Then, using the corrected multispectral data, an efficient multichannel physics-based algorithm has been implemented, which is capable of solving through optimization the radiative transfer model of seawater for bathymetry retrieval, unmixing the water intrinsic optical properties, depth, and seafloor albedo contributions. Finally, for the mapping of benthic features, a supervised classification methodology has been implemented, combining seafloor-type normalized indexes and support vector machine techniques. Results of atmospheric correction, remote bathymetry, and benthic habitat mapping of shallow-water environments have been validated with in situ data and available bionomic profiles providing excellent accuracy. [ABSTRACT FROM PUBLISHER]

A methodology for integrating multiple cues for tracking was proposed in several papers. These papers claim that, unlike other methodologies, conditional independence of the cues is not assumed. This brief communication 1) refutes this claim and 2) points out other major problems in the methodology. [ABSTRACT FROM AUTHOR]

A modified coarse-grained, bead-spring model was used to investigate the effect of lubricant fragments (LF) on lubricant transfer from a rotating disk to a slider in this paper. The simulation results indicate that full lubricant molecules cannot transfer to the slider surface for large enough slider to disk spacing. However, degraded lubricant molecules, namely LF, are able to transfer from the disk to the slider. LF with lower molecular weight is easier to transfer to the slider. The amount of the transferred LF decreases with increased spacing between the slider and the disk. The amount of the transferred lubricant also depends on the lubricant decomposed position, i.e., LF without end groups are more readily transferred to the slider. [ABSTRACT FROM AUTHOR]

In this paper, we show the application of numerical simulation for the virtual testing of a very complex system under high-intensity radiated fields (HIRF) conditions. Numerical results have been compared to measurements performed on a C-295 aircraft. The approach is based on the use of multiple tools for the preprocessing, computation, and postprocessing, all of them integrated under the same framework. This study is a part of the HIRF SE project, and the final step for the validation of the tools involved there, to introduce the use of simulation in the whole aircraft certification process in an HIRF environment. The main goal of the project is to provide the aeronautic industry with a numerical modeling computing framework, which could be used to predict the electromagnetic performance, and to carry out parametrical studies during the design phase, when changes are simpler and less costly. It could also lead in the future to a considerable reduction on the certification/qualification testing phase on air vehicles, to cross validate the results obtained from measurement and simulation providing best confidence in them, and to attain a more exhaustive analysis to achieve a higher level in the air vehicle safety. [ABSTRACT FROM PUBLISHER]

The paper presents the IECo (Israel Electric Co) long-term environmental study aimed at development of Digital Dust Sedimentation Model which provides an Outdoor Insulation Pollution Mapping for Local Grid. The Concept of the study is based on the Authors' idea on strong correlation between IEC 60721 Dust Sedimentation Index vs. IEC TC 60815 Site Pollution Severity Indices within considered geographic domain. The developed Pollution Maps have been validated vs. long-term ESDD-NSDD field-measurements and continuous monitoring of PM10 fraction with correlation factors r=0.830 and r=0.697 respectively. To prove the model reliability the calibration was done for different geographic locations in different time intervals. The first-time developed innovative technology is expected to provide cost benefits with respect to dimensioning and maintenance of outdoor insulators, PV-Plants, and other pollution-sensitive local installations. [ABSTRACT FROM AUTHOR]

In this paper, the dynamic performance evaluation of a 5-degree of freedom (DOF) magnetic levitation and guidance device is addressed. In particular, the electromagnetic forces from an equivalent magnetic circuit model are coupled to a 5-DOF dynamic motion model of the device. With the proposed model, dynamic behaviors are simulated by considering the dynamic interactions between levitation and guidance elements while both systems are operating. In addition, the experimental system is successfully tested and stable levitation and guidance is demonstrated at the desired operating gap and unexpected disturbance forces. [ABSTRACT FROM AUTHOR]

The calculation of the high-altitude electromagnetic pulse (HEMP) fields resulting from a nuclear explosion is dependent on the modeling of secondary electrons generated by the high-energy Compton electrons. In this paper, we discuss different modeling procedures used for this task and show how modeling a delay in the formation of the conductivity resulting from the low-energy electrons affects the HEMP electric fields at the surface of the ground. [ABSTRACT FROM AUTHOR]

This paper analyzes the thermal performance of a data center on a rack level, by utilizing racks stocked with 1U servers. Eleven different rack models covering a wide range of server arrangements with void spaces are presented and modeled in a raised-floor configuration. The objective is to investigate the thermal performance of semipopulated racks with different server arrangements. The inlet and outlet temperature profiles of the models are presented and the overall effect of each model on the thermal performance of a specific rack is discussed. Findings point toward the detailed modeling of semipopulated racks to investigate the main locations of the temperature spikes adjacent to the rack inlet and outlets as well as the recirculation zones. [ABSTRACT FROM PUBLISHER]

Neural networks (NNs) are developed for estimating the error variances of individual infrared and microwave atmospheric temperature and humidity profile retrievals, thus potentially significantly improving their assimilation into numerical weather prediction models. Currently, most assimilation processes require error covariance matrices that are typically estimated over diverse profile ensembles. In addition to these “ensemble error variances,” this work explores the estimation of “sample error variances” that are relevant to a single sample of the ensemble (that is, an individual profile retrieval and its error at each pressure level). This analysis is facilitated by considering an individual profile retrieval as the most likely sample from a distribution of retrievals, given an individual sensor observation vector. The sample error variance is defined as the variance of this distribution. The approach described in this paper does not attempt to compute these retrieval distributions explicitly, as this is computationally prohibitive for hyperspectral sounders. Instead, NNs are trained to estimate the variances of these distributions directly. Examples over ocean utilizing AIRS/AMSU soundings on the NASA Aqua satellite and those from a proposed hyperspectral microwave sounder show that the predicted sample error variances agree well with the true sample error variances as determined by European Centre for Medium-Range Weather Forecasts analyzes colocated to the sensor observations. Furthermore, simple quality indicators derived using thresholding of the sample variance estimates compare favorably to AIRS Level-2 Version-5 quality flags. [ABSTRACT FROM PUBLISHER]

The purpose of this paper is to study the critical breakdown voltage or U50 - corresponding to the 50% probability of breakdown for a single impulse application - of long air-gaps under positive and negative switching impulse voltages, using predictive dynamic models. The knowledge of this important parameter is of practical interest to the design engineer. The models previously developed by the authors are based on equivalent electrical network, gas discharge theories and physical laws. Various gap geometry and atmospheric conditions were considered. The U50, determined using the up and down method along with other important parameters, were compared to experimental data. Good agreements were found between simulated and experimental results. The results obtained indicate that U50 prediction is possible, using the proposed models. Knowledge of the gap factor and weather conditions might help applying corrections to determine the breakdown strength under various conditions. These dynamic models might therefore be useful to estimate the required clearances of air gaps in the preliminary design phase over a wide range of geometry and some atmospheric factors; therefore reducing the required full-scale testing. [ABSTRACT FROM AUTHOR]

Thermal models of buildings are often used to identify energy savings within a building. Given that a significant proportion of that energy is typically used to maintain building temperature, establishing the optimal control of the buildings thermal system is important. This requires an understanding of the thermal dynamics of the building, which is often obtained from physical thermal models. However, these models require detailed building parameters to be specified and these can often be difficult to determine. In this paper, we propose an evolutionary approach to parameter identification for thermal models that are formulated as an optimization task. A state-of-the-art evolutionary algorithm, i.e., SaNSDE+, has been developed. A fitness function is defined, which quantifies the difference between the energy-consumption time-series data that are derived from the identified parameters and that given by simulation with a set of predetermined target model parameters. In comparison with a conventional genetic algorithm, fast evolutionary programming, and two state-of-the-art evolutionary algorithms, our experimental results show that the proposed SaNSDE$+$ has significantly improved both the solution quality and the convergence speed, suggesting this is an effective tool for parameter identification for simulated building thermal models. [ABSTRACT FROM PUBLISHER]