ALBERT

Description: A set of three quad-pol images acquired at the L-band in interferometric repeat-pass mode by the German Aerospace Center (DLR) with the Experimental SAR (E-SAR) system, in parallel with the AgriSAR2006 campaign, has been used to provide, for the first time with airborne data, a demonstration of the retrieval of vegetation height from agricultural crops by means of polarimetric SAR interferometry (PolInSAR)-based techniques. Despite the low frequency of the data, hence providing a weak response from the vegetation volume in contrast to the ground, accurate estimates of vegetation height at field level have been obtained over winter rape and maize fields. The same procedure does not yield valid estimates for wheat, barley, and sugar beet fields due to a mismatch with the physical model employed in the inversion and to the specific crop condition at the date of acquisition. These results show the value of the information provided by both interferometry and polarimetry for some agriculture monitoring practices.

Description: The recently launched Soil Moisture and Ocean Salinity (SMOS) satellite is providing soil moisture observations at continental scales by measuring L-band microwave radiation emitted from the land surface. While its retrieval algorithms will correct for factors such as vegetation and surface roughness, it will not correct for soil salinity. This letter tests the assumption that soil salinity will have a negligible impact on L-band brightness temperature $(T_{b})$ at SMOS scales using field data; airborne $T_{b}$ observations were collected in a saline groundwater discharge area near Nilpinna Station, South Australia. At the 500-m scale, the airborne observations of $T_{b}$ could not be reproduced using the baseline algorithm of the SMOS Level 2 retrieval scheme, without accounting for soil salinity in the model. The analysis in this letter shows that soil moisture retrieval errors of at least 0.04 $hbox{m}^{3} hbox{m}^{-3}$ (i.e., the entire SMOS error budget) will occur due to salinity alone in SMOS footprints with saline coverage as low as 25% (possibly even much less). Consequently, fractional salinity coverage cannot be considered a negligible factor by microwave soil moisture satellite missions.

Description: Based on the difference in statistical distribution between the target and jamming signal in the synthetic aperture radar (SAR) image, this letter proposes a novel adaptive method for barrage jamming suppression. In this method, the covariance matrix of jamming is estimated from the SAR image. Then, the 2-D sinc function of the ideal point target is utilized as the steering vector to obtain the optimal adaptive filter. This filter can suppress the random barrage jamming effectively, thus improving the image contrast and interpretability. Additionally, this letter analyzes in detail the theoretical basis and performance of the proposed method. Finally, simulations are provided to demonstrate its effectiveness.

Description: The advent of submeter-resolution synthetic aperture radar (SAR) images from satellites such as TerraSAR-X has given a new dimension to SAR image understanding. Even though emphasis is always on discovering automatic means of target characterization, visual exploration of targets and objects is the first step in many applications. While considering the complex-valued SAR images, visual inspection of the targets in an image may provide incomplete and misleading information, as sometimes two entirely different behaving objects look quite similar in SAR images. Thus, a need was felt to develop a methodology to support visual target recognition and analysis. In this letter, we present a method which looks into the complex-valued spectrum of SAR images, thus allowing a detailed physical interpretation of the scattering behavior of objects. The presented method is a joint time–frequency analysis method based on sublook decomposition. With the presented results, we emphasize the use of complex-valued SAR images for target characterization, the use of which is primarily restricted to polarimetric and interferometric applications as of now.

Description: This letter presents a novel neighborhood-based ratio (NR) operator to produce a difference image for change detection in synthetic aperture radar (SAR) images. In order to reduce the negative influence of speckle noise on SAR images, the proposed NR operator produces a difference image by combining gray level information and spatial information of neighbor pixels. The performance comparisons of the proposed operator with a traditional ratio operator and a log-ratio operator indicate that the NR operator is superior to these traditional methods and produces better detection results.

Description: In this letter, the requirements to derive topography from a portable terrestrial radar interferometer are introduced, the instrument design and the relationship between interferometric phase shift and surface topography are explained, and two examples of topographic maps from measurements at the Rhone glacier and Grabengufer rock glacier in Switzerland are presented. In the first case, an external digital elevation model was used to assess the error of topography mapping with the portable radar interferometer and to analyze ice surface changes of the glacier in the last 14 years. We found that the height error standard deviation is about 3 m within a distance of 2 km from the sensor and observed massive thinning of the Rhone glacier. In the second case, we used the terrestrial radar interferometer in order to measure the height difference between August 2009 and March 2010 over the rock glacier as a consequence of its destabilization.

Description: We map the coseismic deformation of the 2011 Tohoku-Oki earthquake with data from three descending Envisat/ASAR tracks and six ascending ALOS/PALSAR tracks that cover most of northeastern Japan. Due to the inaccurate estimation of the satellite status, orbital ramps commonly exist in the coseismic interferograms, which resulted in inconsistency among the deformation maps released by several research groups. In this letter, calibration has been performed to accurately remove these ramps by a 2-D quadratic-phase model derived based on GPS measurements from the ARIA team at the Jet Propulsion Laboratory and Caltech. The average RMS of the interferometric synthetic aperture radar (InSAR) measurements, as compared with GPS measurements at the validation stations, has decreased from 17.8 to 7.7 cm after the orbital ramp correction is made, indicating that much more accurate InSAR measurements are achieved. The corrected coseismic deformation from the InSAR measurements is consistent with not only the GPS observations at the individual GPS stations but also with the coseismic deformation interferogram from interpolated GPS observation in the SAR viewing directions. The corrected coseismic deformation measurement results show a maximum line-of-sight displacement of up to 3.7 m from the ascending PALSAR tracks and 2.4 m from the descending ASAR tracks, respectively.

Description: Global Navigation Satellite Systems (GNSS) opportunity signals reflected at or near the Earth's surface have already shown their potential to perform retrievals of a number of geophysical parameters. Radio occultations using GNSS signals are also used for atmospheric sensing. This letter presents a GNSS technique to retrieve vegetation water content (VWC). This technique measures the received powers of the GPS signals in open sky and under the vegetation layer. From these two powers, the attenuation due to the vegetation is computed, which is related to the VWC. This letter presents the results obtained after deploying the instrument in a walnut-tree stand for 11 months.

Description: In this letter, an improved differential evolution (DE) for high-dimensional waveform inversion is proposed. In conventional evolutionary algorithms, an individual is treated as a whole, and all its variables (genes) are evaluated with a uniform fitness function. This evaluation criterion is not effective for a high-dimensional individual. Therefore, for high-dimensional waveform inversion, we incorporate the decomposition strategy of cooperative coevolution into DE to decompose the individual into some subcomponents. Another novel feature that we introduce is a local fitness function for each subcomponent, and a new mutation operator is designed to guide the mutation direction of each subcomponent with the corresponding local fitness value. Coevolution among different subcomponents is realized in the selection operation with the global fitness function. Many experiments have been carried out to evaluate the performance of this new algorithm. The results clearly show that, for high-dimensional waveform inversion, this algorithm is effective and performs better than some other methods. Finally, the new method has been applied to real seismic data.

Description: This letter proposes the kernel entropy component analysis for clustering remote sensing data. The method generates nonlinear features that reveal structure related to the Rényi entropy of the input space data set. Unlike other kernel feature-extraction methods, the top eigenvalues and eigenvectors of the kernel matrix are not necessarily chosen. Data are interestingly mapped with a distinct angular structure, which is exploited to derive a new angle-based spectral clustering algorithm based on the mapped data. An out-of-sample extension of the method is also presented to deal with test data. We focus on cloud screening from Medium Resolution Imaging Spectrometer images. Several images are considered to account for the high variability of the problem. Good results obtained show the suitability of the proposal.

Description: A major source of error for repeat-pass interferometric synthetic aperture radar is the phase delay in radio signal propagation through the atmosphere, particularly the part due to tropospheric water vapor. These effects become more significant for ScanSAR observations due to their wider coverage (e.g., 400 km $times$ 400 km for ENVISAT Advanced Synthetic Aperture Radar (ASAR) wide swath (WS) mode versus 100 km $times$ 100 km for ASAR image mode). In this letter, we demonstrate for the first time that a Medium Resolution Imaging Spectrometer water vapor correction model can significantly reduce atmospheric water vapor effects on ASAR WS interferograms, with the phase variation in non-deforming areas decreasing from 3.8 cm before correction to 0.4 cm after correction.

Description: Good behavior for the altitude estimation has been validated in terms of accuracy using instrumented GPS targets, as well as opportunistic ones (coherence of the altitude history with respect to the speed indicator). In most cases, this altitude estimation satisfied our objectives, even though they were quite ambitious objectives. A system such as this one should clearly distinguish the different altitudes of different flight patterns, and the difference between the two altitudes was equal to 330 m. This multistatic DVB-T SFN tracker is exploiting detections based on a 2D planar DVB-T receiving array: the parameters estimated are the bistatic range and Doppler, as well as the azimuth and elevation measurements. Some opportunistic targets have also been analyzed for validation of the 3D localization capacities, especially for low speed targets at very low altitude.

Description: A novel method enabling single-site localization of wireless emitters in a rich multipath environment is presented. The localization is based on a novel fingerprinting technique exploiting the spatial-temporal characteristics of the multipath signals received by the base station antenna array. The fingerprint is based on a lower dimensional signal subspace of the spatial-temporal covariance matrix, capturing the dominant multipath signals. The performance is validated with both simulated and real data, demonstrating localization accuracy of about 1 m in typical indoor environments.

Description: A quasi-optical interferometric technique capable of measuring antenna phase patterns without the need for a heterodyne receiver is presented. It is particularly suited to the characterization of terahertz antennas feeding power detectors or mixers employing quasi-optical local oscillator injection. Examples of recorded antenna phase patterns at frequencies of 1.4 and 2.5 THz using homodyne detectors are presented. To our knowledge, these are the highest frequency antenna phase patterns ever recovered. Knowledge of both the amplitude and phase patterns in the far field enable a Gauss–Hermite or Gauss–Laguerre beam-mode analysis to be carried out for the antenna, of importance in performance optimization calculations, such as antenna gain and beam efficiency parameters at the design and prototype stage of antenna development. A full description of the beam would also be required if the antenna is to be used to feed a quasi-optical system in the near-field to far-field transition region. This situation could often arise when the device is fitted directly at the back of telescopes in flying observatories. A further benefit of the proposed technique is simplicity for characterizing systems in situ, an advantage of considerable importance as in many situations, the components may not be removable for further characterization once assembled. The proposed methodology is generic and should be useful across the wider sensing community, e.g., in single detector acoustic imaging or in adaptive imaging array applications. Furthermore, it is applicable across other frequencies of the EM spectrum, provided adequate spatial and temporal phase stability of the source can be maintained throughout the measurement process. Phase information retrieval is also of importance to emergent research areas, such as band-gap structure characterization, meta-materials research, electromagnetic cloaking, slow light, super-lens design as well as near-field and virtual imaging app- ications.

Description: Direction of arrival (DOA) estimation is a classical problem in signal processing with many practical applications. Its research has recently been advanced owing to the development of methods based on sparse signal reconstruction. While these methods have shown advantages over conventional ones, there are still difficulties in practical situations where true DOAs are not on the discretized sampling grid. To deal with such an off-grid DOA estimation problem, this paper studies an off-grid model that takes into account effects of the off-grid DOAs and has a smaller modeling error. An iterative algorithm is developed based on the off-grid model from a Bayesian perspective while joint sparsity among different snapshots is exploited by assuming a Laplace prior for signals at all snapshots. The new approach applies to both single snapshot and multi-snapshot cases. Numerical simulations show that the proposed algorithm has improved accuracy in terms of mean squared estimation error. The algorithm can maintain high estimation accuracy even under a very coarse sampling grid.

Description: This paper investigates reliable and covert transmission strategies in a multiple-input multiple-output (MIMO) wiretap channel with a transmitter, receiver and an adversarial wiretapper, each equipped with multiple antennas. In a departure from existing work, the wiretapper possesses a novel capability to act either as a passive eavesdropper or as an active jammer, under a half-duplex constraint. The transmitter therefore faces a choice between allocating all of its power for data, or broadcasting artificial interference along with the information signal in an attempt to jam the eavesdropper (assuming its instantaneous channel state is unknown). To examine the resulting trade-offs for the legitimate transmitter and the adversary, we model their interactions as a two-person zero-sum game with the ergodic MIMO secrecy rate as the payoff function. We first examine conditions for the existence of pure-strategy Nash equilibria (NE) and the structure of mixed-strategy NE for the strategic form of the game. We then derive equilibrium strategies for the extensive form of the game where players move sequentially under scenarios of perfect and imperfect information. Finally, numerical simulations are presented to examine the equilibrium outcomes of the various scenarios considered.

Description: We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. We observe that the target and interference spectra are inherently sparse in the spatio-temporal domain. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data and produces an equivalent performance as the other existing STAP techniques. In addition, the use of an OFDM signal increases the frequency diversity of our system, as different scattering centers of a target resonate at different frequencies, and thus improves the target detectability. First, we formulate a realistic sparse-measurement model for an OFDM radar considering both the clutter and jammer as the interfering sources. Then, we apply a residual sparse-recovery technique based on the LASSO estimator to estimate the target and interference covariance matrices, and subsequently compute the optimal STAP-filter weights. Our numerical results demonstrate a comparative performance analysis of the proposed sparse-STAP algorithm with four other existing STAP methods. Furthermore, we discover that the OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.

Description: We present a novel fusion algorithm for electronic-reconnaissance (ER) satellite and optical imaging satellite data using coherent point set (CPS) analysis. This work is motivated by a large-scale maritime surveillance problem, where ship groups in the observations are of particular interest for tactical and strategic operations. Fusion of observations from ER satellite and optical imaging satellite is a challenging task. On the one hand, dense and continuous measurement is not available for optical imagery. On the other hand, it is difficult to extract robust features from ER measurements. Considering that the size of a ship is often less than the distance among different ships, we treat each ship as a mass point. The contributions of our work are threefold. First, multisensor data fusion is accomplished by CPS association. To the best of our knowledge, this letter is the first to investigate CPS for multimodal remote sensing data fusion. Second, a novel geometry descriptor, which encodes the topological characteristics of a point set, is presented. Third, we combine both topological features and attributive features within the framework of Dempster–Shafer theory for CPS analysis. The proposed method has been tested using different sets of simulated data and recorded data. Experimental results demonstrate the effectiveness of the proposed method.

Description: The 2008 Wenchuan Earthquake that occurred in a mountainous region of China induced massive landslides and caused numerous casualties and property losses. Analyzing the disturbances on vegetation detected from the abnormal sudden drops of the normalized difference vegetation index (NDVI) within a short period can be used for the purpose of rapid landslide identification. Although much research has confirmed the necessity of high-resolution satellite images in landslides identification, Moderate Resolution Imaging Spectroradiometry (MODIS) products still have their usefulness for high temporal resolution, as investigated by the authors. Using MODIS MOD09Q1 NDVI products at a temporal interval of 8 days during 2008, this letter presents a method that has been developed to identify landslide distribution and evolution patterns. First, to find the optimal threshold, the MODIS NDVI time series are analyzed in a training area by an iteration searching procedure. Second, the chosen threshold is used in a larger validation area. To examine the effectiveness of the proposed method, the results are compared to interpreted landslides using SPOT5 images with a spatial resolution of 2.5 m acquired before and after the main shock. An overall 75% accuracy is achieved, and better consistency is observed for landslides extending over one MODIS pixel. The proposed method has also been applied to the Wenchuan earthquake affected areas with seismic intensity IX and greater, and the similar spatial pattern of landslides distribution is obtained when compared with results by using high-resolution images and field investigation. This technique can be applied practically for rapid landslide assessment at a relatively large region after a major earthquake or other severe disturbance events.

Description: The new generation of synthetic aperture radar (SAR) sensors is providing images with very high spatial resolution, improved up to the meter scale. Such a resolution increase allows more accurate monitoring capabilities by means of interferometric approaches. The use of higher frequency enhances the sensitivity of the system even to minute changes, such as thermal dilations. This phenomenon has an impact on the interferometric products, particularly on the deformation velocity maps, if not properly handled. Man-made structures, such as steel core bridges and specific buildings, may be very sensible to thermal dilation effects. By extending the multitemporal differential interferometry SAR processing chains, in our case based on the multidimensional imaging (MDI) approach, an additional parameter related to temperature differences at acquisition instants, the thermal coefficient, can be accurately estimated. This parameter provides interesting perspectives in application to infrastructure monitoring: It brings information about the thermal behavior of the imaged objects. In this letter, we investigate the thermal response of the Musmeci bridge (Potenza, Italy), by experimenting the extended MDI approach on a real TerraSAR-X data set. Results highlight the possibility of such a technique to obtain measurements of the motion that is highly correlated with temperature, thus providing useful information about the static structure of bridges.

Description: The triplet Markov field (TMF) model is powerful in the nonstationary synthetic aperture radar (SAR) image analysis. Taking the speckle noise and the correlation of nonstationarities in two multitemporal SAR images into account, we propose a change-detection method based on the TMF model in this letter. The third field $U$ in the TMF model is redefined to describe the nonstationary textural similarity between the two images for change detection. The corresponding prior energy of $(X, U)$ is reconstructed. The adaptive weight parameter in prior energy is introduced to cope with the detection tradeoff issue. An automatic estimation of the parameter is obtained with low level of complexity. The Bayesian maximum posterior marginal criterion is utilized with the TMF model to obtain change detection. Experimental results on real SAR images validate the superiority of the proposed TMF method over the Markov random field method.

Description: A time series of COSMO-SkyMed (CSK) images is exploited for detection of seasonal snow cover in alpine areas. For the first time, a complete time series of CSK images acquired during snow fall and melt periods in winter 2010–2011 is addressed to verify the snow cover mapping capabilities of X-band radar images under different conditions (from dry to wet snow). The algorithm for snow detection is based on a multitemporal approach with the concept that free water in the snowpack attenuates the X-band synthetic aperture radar signal and wet snow can be classified by comparing images acquired under wet snow and snow-free conditions. Thresholds to make this distinction are compared across all the images to check sensitivity to different winter conditions and land-use classes. The impact of variable and fixed thresholds on the retrieved snow-covered areas is assessed. Snow maps from CSK images compared with Landsat Enhanced Thematic Mapper Plus snow maps indicate a constant underestimation in the detection of snow extent, particularly during winter season, thus showing a scarce sensitivity of X-band signals to snow in dry conditions. Probability of error maps are also calculated for each CSK snow map, thus providing information on the classification error associated to each pixel labeled as snow. The analysis of the snow line variation during spring determines good time consistency in the determination of snow maps from CSK images.

Description: Wavelet packet analysis (WPA) and gray model (GM) are investigated for nonlinear unsupervised feature extraction of hyperspectral remote sensing data in this letter. Treated as derivative series, a hyperspectral response curve of each pixel is decomposed into an approximation and various detailed compositions by WPA, and then, GM is continuously applied to find the relationship among those detailed compositions. Cluster–space representation is used for determining the optimal wavelet. New extracted features can reveal the intrinsic identities of hyperspectral data. Experimental results show the feasibility and reliability of our proposed method in terms of classification accuracy.

Description: This letter proposes a new supervised linear feature extractor for hyperspectral image classification. The criterion for feature extraction is a modified maximal relevance and minimal redundancy (MRMD), which has been used for feature selection until now. The MRMD is a function of mutual information terms, which possess higher order statistics of data; thus, it is effective for hyperspectral data with informative higher order statistics. The batch and stochastic versions of the gradient ascent are performed on the MRMD to find the optimal parameters of a linear feature extractor. Preliminary results achieve better classification performance than the traditional methods based on the first- and second-order moments of data.

Description: The high-resolution imaging of a highly squinted synthetic aperture radar remains difficult because of the severe coupling between the range and the azimuth. “Squint minimization” compensates for the range walking in the azimuth time domain, which efficiently increases the orthogonality between the range and the azimuth. However, this “squint minimization” introduces the azimuth space-variant phases, which can be compensated by the azimuth nonlinear chirp-scaling (ANCS) algorithm using large computational loads. In this letter, an azimuth overlapped subaperture algorithm (AOSA) is proposed to compensate for these phases in the Doppler frequency domain. The validity constraint of this algorithm is then analyzed. The AOSA has an advantage over ANCS in terms of the computational load and is considerably more suitable for real-time processing.

Description: The potential of polarimetric synthetic aperture radar data for the soil surface characterization of bare agricultural soils was investigated by using air- and spaceborne data acquired by Radar Aéroporté Multi-Spectral d'Etude des Signatures (RAMSES), Système Expérimental de Télédétection Hyperfréquence Imageur (SETHI), and RADARSAT-2 sensors over several study sites in France. Fully polarimetric data at ultrahigh frequency, X-, C-, L-, and P-bands were compared. The results show that the main polarimetric parameters studied (entropy, $alpha$ angle, and anisotropy) are not very sensitive to the variation of the soil surface parameters. Low correlations are observed between the polarimetric and soil parameters (moisture content and surface roughness). Thus, the polarimetric parameters are not very relevant to the characterization of the soil surface over bare agricultural areas.

Description: Airborne dual-polarization observations of sea surface normalized radar cross section (NRCS) were conducted over the North Atlantic during January–February 2011. Observations were made using the University of Massachusetts' Imaging Wind and Rain Airborne Profiler radar system installed on the National Oceanic and Atmospheric Administration's WP-3D research aircraft during several winter storm events to determine the high-wind response of the sea surface NRCS for both horizontal and vertical polarizations. During the flights, the aircraft performed several constant-roll circle maneuvers to allow collection of NRCS over a range of incidence angles. We find consistency with prior reports in the polarization ratio observed at moderate incidence angles at the winds encountered. For larger incidence angles, we observe a measurable decrease in polarization ratio with increasing wind speed.

Description: A narrowband mid-infrared (mid-IR) guided-mode resonance filter (GMRF) is designed and fabricated using a Hafnium Dioxide film/quartz wafer material system. The fabricated GMRF is then integrated into an erbium (Er)-doped Zr-Ba-La-Al-Na (ZBLAN) fluoride glass fiber laser as a wavelength selective feedback element. The laser operated at 2782 nm with a line-width less than 2 nm demonstrates the viability of GMRFs for wavelength selection in the mid-IR.

Description: We propose a mutually injection-locked tunable (MILT) laser for L-band generation based on arrayed waveguide grating and gain-saturated reflective semiconductor optical amplifiers. The laser generates a 3-dB bandwidth less than 0.05 nm and a high and uniform sidemode suppression ratio $({rm SMSR}>52~{rm dB},~Delta{rm SMSR}>3~{rm dB})$ over 40 L-band wavelengths. Using an MILT laser greatly reduced the phase noise, which is measured to be ${-}{rm 107.83}~{rm dBc}/{rm Hz}$ at a frequency of 10-kHz offset from the center. Furthermore, the 1.25-Gb/s directly modulated transmission performance of the MILT laser shows that there is a power penalty of ${sim}{rm 0.2}~{rm dB}$ over a 20-km single mode fiber.

Description: Remember James Bond and the Sony Ericsson cell phone he used to drive a BMW 750 iL in the 2008 Bond movie, Tomorrow Never Dies? Your smartphone and your car (and very likely you) aren't quite ready for that kind of driving experience, but the technology and automakers are getting closer to that level of capability

Description: IEEE Signal Processing Magazine (SPM) is a tutorial-style magazine that brings to the signal processing community bimonthly survey articles of the most recent advances in signal processing theory and applications. For this issue, the Editor-in-Chief invited Andrea Cavallaro and Andres Kwasinski, the area editors for columns and forum, to write a brief on their editorial work.

Description: Cooperation is known as an effective strategy in nature to achieve individual or common goals and is a key element in evolution for optimization, as Darwin pointed out in his famous work. Cooperation among weaker individuals (such as hyenas) has the potential to outperform stronger individuals (cheetahs) agnostic to the principle of cooperation. The concept of cooperation has been applied to mobile communication networks with the first appearance of so-called ad hoc networks or meshed networks. But this kind of cooperation is a special form of cooperation, later referred to as forced cooperation, controlled by an overlay unit and not built up by selfish individuals. The research field of social mobile clouds is looking into the possibility to increase the potential of cooperation among selfishly driven users by introducing novel technologies such as network coding as well as socially driven incentives introduced by several well known social networks.

Description: High Efficiency Video Coding (HEVC) is a new video compression standard developed jointly by ITU-T Video Coding Experts Group (VCEG) and ISO/IEC Moving Pictures Expert Group (MPEG) through their Joint Collaborative Team on Video Coding (JCT-VC). The first version of HEVC will be finalized by the JCT-VC in January 2013. The HEVC project was launched to achieve major savings—e.g., reduction by about half for 1,280 # 720 high-definition (HD) and higher-resolution progressives can video—for equivalent visual quality relative to the bit rate needed by the widely used H.264/ MPEG-4 Advanced Video Coding (AVC) standard. For high resolution video where such additional compression is most urgently required, implementations of the current draft standard are already meeting or exceeding the targeted goal. We review the architecture and building blocks of HEVC, which were carefully selected with regard to compression capability versus complexity and to enable parallelism for the signal processing operations. Given the benefits that HEVC provides, it is likely to become the new primary reference for video compression.

Description: A central biological process in all living organisms is gene translation. Developing a deeper understanding of this complex process may have ramifications to almost every biomedical discipline. Reuveni et al. recently proposed a new computational model of gene translation called the Ribosome Flow Model (RFM). In this paper, we consider a particular case of this model, called the Homogeneous Ribosome Flow Model (HRFM). From a biological viewpoint, this corresponds to the case where the transition rates of all the coding sequence codons are identical. This regime has been suggested recently based on experiments in mouse embryonic cells. We consider the steady-state distribution of the HRFM. We provide formulas that relate the different parameters of the model in steady state. We prove the following properties: 1) the ribosomal density profile is monotonically decreasing along the coding sequence; 2) the ribosomal density at each codon monotonically increases with the initiation rate; and 3) for a constant initiation rate, the translation rate monotonically decreases with the length of the coding sequence. In addition, we analyze the translation rate of the HRFM at the limit of very high and very low initiation rate, and provide explicit formulas for the translation rate in these two cases. We discuss the relationship between these theoretical results and biological findings on the translation process.

Description: Ranking genes in functional networks according to a specific biological function is a challenging task raising relevant performance and computational complexity problems. To cope with both these problems we developed a transductive gene ranking method based on kernelized score functions able to fully exploit the topology and the graph structure of biomolecular networks and to capture significant functional relationships between genes. We run the method on a network constructed by integrating multiple biomolecular data sources in the yeast model organism, achieving significantly better results than the compared state-of-the-art network-based algorithms for gene function prediction, and with relevant savings in computational time. The proposed approach is general and fast enough to be in perspective applied to other relevant node ranking problems in large and complex biological networks.

Description: An important objective of modeling biological phenomena is to develop therapeutic intervention strategies to move an undesirable state of a diseased network toward a more desirable one. Such transitions can be achieved by the use of drugs to act on some genes/metabolites that affect the undesirable behavior. Due to the fact that biological phenomena are complex processes with nonlinear dynamics that are impossible to perfectly represent with a mathematical model, the need for model-free nonlinear intervention strategies that are capable of guiding the target variables to their desired values often arises. In many applications, fuzzy systems have been found to be very useful for parameter estimation, model development and control design of nonlinear processes. In this paper, a model-free fuzzy intervention strategy (that does not require a mathematical model of the biological phenomenon) is proposed to guide the target variables of biological systems to their desired values. The proposed fuzzy intervention strategy is applied to three different biological models: a glycolytic-glycogenolytic pathway model, a purine metabolism pathway model, and a generic pathway model. The simulation results for all models demonstrate the effectiveness of the proposed scheme.

Description: Advertisement: This publication offers open access options for authors. IEEE open access Publishing.

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Description: Provides a listing of current staff, committee members and society officers.

Description: Cognitive control is part of a wider framework called cognitive dynamic systems, which builds on a paradigm of cognition composed of five elements: perception??action cycle, memory, attention, intelligence, and language. Any closed-loop feedback control system is based on the perception??action cycle. Adaptive control systems, it can be argued, incorporate the attention and intelligence aspects of the paradigm, but not memory. The language component becomes relevant to a network of cognitive agents. Cognitive control depends on an understanding of the information gap - the distance between relevant information extracted from measurements and the sufficient information that is required. Cognitive control should not be thought of as a replacement system design paradigm; it is additive in nature. It augments state-control paradigms such as adaptive control and neurocontrol. Using cognitive control, we can improve the utilization of computational resources and manage risk more effectively.

Description: In modern wireless communication systems, it is very important to realize simultaneously high-efficiency and linear operation of power amplifiers. This paper-overview describes the historical aspect of the Doherty approach to the power-amplifier design introduced in 1936 and modern trends in Doherty amplifier (DA) design techniques using multistage and asymmetric multiway architectures. To increase efficiency over the power backoff range, the switchmode class-E, conventional class-F, or inverse class-F operation mode by controlling the second and third harmonics can be used in the load network. The DA with a series-connected load, and inverted, push–pull, balanced, and parallel Doherty architectures are also described and discussed. Finally, examples of the lumped DA implemented in monolithic microwave integrated circuits, digitally driven Doherty technique, and broadband capability of the two-stage DA are given.

Description: This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.

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Description: This paper reports the design and implementation of a two-axis capacitive-type accelerometer using well-known two poly-Si processes. The accelerometer design consists of a pendulum proof-mass (bulk Si), a gimbal-spring (poly-Si film), and vertical-comb sensing electrodes. This design has three merits: 1) pendulum proof-mass to produce torque by in-plane acceleration; 2) high-aspect-ratio-micromachined (HARM) gimbal-springs enable the detection of two-axis accelerations; and 3) vertical-combs of different vertical positions enable the differential sensing electrodes design to detect the angular motion. In short, this paper exploits the vertical-comb electrodes for differential capacitive sensing to detect the two-axis in-plane accelerations. Measurement results show that the sensitivities (nonlinearity) of etch direction are 17.87 mV/G (2.65%) of X-axis, and 16.54 mV/G (2.71%) of Y-axis in the excitation range of 0.6~2 G. Due to the HARM gimbal-spring design, the cross axis sensitivity introduced by the Z-axis excitation is less than 0.3% for both X-axis and Y-axis sensing. However, the cross-axis error between the X-axis and the Y-axis sensing elements still need to be improved.

Description: In this survey, we present a comprehensive list of major known security threats within a cognitive radio network (CRN) framework. We classify attack techniques based on the type of attacker, namely exogenous (external) attackers, intruding malicious nodes and greedy cognitive radios (CRs). We further discuss threats related to infrastructure-based CRNs as well as infrastructure-less networks. Besides the short-term effects of attacks over CRN performance, we also discuss the often ignored longer term behavioral changes that are enforced by such attacks via the learning capability of CRN. After elaborating on various attack strategies, we discuss potential solutions to combat those attacks. An overview of robust CR communications is also presented. We finally elaborate on future research directions pertinent to CRN security. We hope this survey paper can provide the insight and the roadmap for future research efforts in the emerging field of CRN security.

Description: This paper is inspired by how cognitive control manifests itself in the human brain and does so in a remarkable way. It addresses the many facets involved in the control of directed information flow in a dynamic system, culminating in the notion of information gap, defined as the difference between relevant information (useful part of what is extracted from the incoming measurements) and sufficient information representing the information needed for achieving minimal risk. The notion of information gap leads naturally to how cognitive control can itself be defined. Then, another important idea is described, namely the two-state model, in which one is the system's state and the other is the entropic state that provides an essential metric for quantifying the information gap. The entropic state is computed in the perceptual part (i.e., perceptor) of the dynamic system and sent to the controller directly as feedback information. This feedback information provides the cognitive controller the information needed about the environment and the system to bring reinforcement leaning into play; reinforcement learning (RL), incorporating planning as an integral part, is at the very heart of cognitive control. The stage is now set for a computational experiment, involving cognitive radar wherein the cognitive controller is enabled to control the receiver via the environment. The experiment demonstrates how RL provides the mechanism for improved utilization of computational resources, and yet is able to deliver good performance through the use of planning. The paper finishes with concluding remarks.

Description: Carbon nanotubes (CNTs) improve the sensitivity of electrochemical biosensors. An optimized CNT/trasducer integration is required to realize accurate devices. The nanotube orientation on the sensor electrode is a key parameter. The role of the sidewalls and the tips in the electroactivity of the nanosensor is presently investigated in the literature. In addition, nanotube hydrophobicity is a drawback for biosensing purposes. Indeed, samples are always in water conditions and the integration biomacromolecules-CNTs are often required. In this paper, a comparison of CNTs with and without exposed walls before and after an acid treatment is proposed. It is done by using contact angle measurements and electrochemical measurements of the electroactive compound potassium ferricyanide. Finally, the electrochemistry of two biomolecules is investigated with those nanostructures more suitable for biodetection.

Description: This paper presents a comprehensive study of the design aspects of eddy-current displacement sensor (ECS) systems. In accordance with the sensor analysis presented in this paper, design strategies to compensate for important sensor imperfections are recommended. To this end, the challenges that are associated with ECS interfaces are identified, with focus on advanced industrial applications. This paper also provides a technical overview of the design advances of ECS interfaces proposed in the last decade and evaluates their pros and cons. Recently reported interface solutions for demanding industrial applications with respect to high resolution, stability, bandwidth, and low power consumption, at a sufficiently high excitation frequency, are addressed in more detail.

Description: Ambulatory monitoring of the electrocardiogram (ECG) is a highly relevant topic in personal healthcare. A key technical challenge is overcoming artifacts from motion in order to produce ECG signals capable of being used in clinical diagnosis by a cardiologist. An electrode-tissue impedance is a signal of significant interest in reducing the motion artifact in ECG recordings on the go. A wireless system containing an ultralow-power analog front-end ECG signal acquisition, as well as the electrode-tissue impedance, is used in a validation study on multiple subjects. The goal of this paper is to study the correlation between motion artifacts and skin electrode impedance for a variety of motion types and electrodes. We have found that the correlation of the electrode-tissue impedance with the motion artifact is highly dependent on the electrode design the impedance signal (real, imaginary, absolute impedance), and artifact types (e.g., push or pull electrodes). With the chosen electrodes, we found that the highest correlation was obtained for local electrode artifacts (push, pull, electrode) followed by local skin (stretch, twist, skin) and global artifacts (walk, jog, jump). The results show that the electrode-tissue impedance can correlate with the motion artifacts for local disturbance of the electrodes and that the impedance signals can be used in motion artifact removal techniques such as adaptive filtering.

Description: A single-chip smart flow sensor based on a thermal principle is presented. The device is fabricated through a commercial complementary metal-oxide-semiconductor (CMOS) process combined with a postprocessing procedure. A configurable electronic interface performing signal reading and nonideality compensation is integrated with the sensing structures on the same chip. The interface implements recently proposed approaches to offset and pressure effect compensation. Detailed experimental results are presented demonstrating correct operation of the proposed microsystem.

Description: In this paper, the results of the long-term temperature monitoring of the compact muon solenoid experiment (CMS) at CERN are shown. The measurements were carried out by means of a system based on fiber Bragg grating (FBG) sensors in wavelength-division multiplexing (WDM). Due to the harsh working conditions at the CMS, the FBG sensor represents the ideal candidate to realize a reliable and accurate sensing system. The sensing principles of the FBG sensor and its temperature characteristics are introduced. A temperature monitoring system based on FBG for high-energy physics applications is designed and installed. The sensing system was used successfully last year in monitoring the temperature of CMS bulkhead. The reported results show good reliability and high accuracy of the FBG sensing system during the long-time working stage.

Description: An inductance-capacitance-resistor (LCR) loop is composed, by connecting an inductive coil with a capacitance element end by end. Without any electric connection with other circuits, higher quality factor can be easily obtained. The loop is inserted into the electromagnetic coupling path of coil-based sensing system, such as the case of eddy-current sensor. When the system is working at the natural resonant frequency of the loop, the coupling efficiency and, therefore, the sensing performance could be improved significantly. Protocol systems, simulating the operation cases of wireless passive sensor and eddy current proximity sensor, are constructed and tested experimentally. The results indicate that, in case of coil-coupled wireless passive sensing system, the received signal's amplitude is enlarged remarkably with a coaxially inserted LCR loop. Moreover, when the loop is coaxially placed on top of the sensing coil of eddy current sensor, not only higher sensitivity and resolution, but also larger monotonic detection range could be achieved.

Description: In this paper, a measurement system for human joint movements monitoring based on a simple and low-cost intensity modulated fiber-optic curvature sensor is presented. The implemented curvature sensor is made up of a plastic optical fiber, which is optimized for small curvature measurements, and has a high sensitivity in a wide measuring range. The sensor sensitivity and resolution, in the measurement range, are 20 ${rm mV}/^{circ}$ and 1 $^{circ}$ , respectively. The fabrication process of proposed curvature sensor is also given. The implemented sensor is wearable, noninvasive, nonintrusive, and completely harmless. In this paper, the characteristics of the sensor measured in laboratory conditions as well as measurements of the human knee joint movements are given. Wireless electronics based on ZigBee are also presented. Therefore, the sensor has the possibility of wireless measurement. The main advantages of this sensor are simplicity, lightness, and flexibility. This sensor is also electrically safe and immune to electromagnetic interference. The application, which provides a possibility of remote human joints monitoring over the internet is implemented in the LabVIEW software package.

Description: We present experimental demonstrations of a self-repairing polymer waveguide strain sensor packaged in a polyimide capillary. The waveguide is fabricated between two multi-mode optical fibers through an ultraviolet curable resin and operates as a strain sensor by interrogation of the infrared power transmission through the waveguide. The packaging improves the performance of the sensor as compared to a previous unpackaged version, by removing previous “no-response” zones. The resulting sensor output is monotonic throughout the measurement range. The hysteresis in the sensor behavior among multiple loading cycles is also significantly reduced. A jump in the sensor output voltage is observed after the sensor self-repair process, which presents challenges for calibration of the sensor.

Description: Control of lighting systems that adapt to daylight is known to be energy efficient. An underlying challenge in such control is the estimation of daylight level. We consider the problem of disaggregated estimation of the daylight and artificial light levels in a lighting system. To facilitate this disaggregation, the light output from each light source is modulated and the system operates under a carrier sense multiple access with collision avoidance protocol. At the light sensor, the received electrical signal is a superposition of the light contributions from daylight and artificial light sources. We present algorithms to process the sensor signal to estimate the daylight and artificial light levels. An optimum joint least-squares estimator is analyzed and, subsequently, two practical successive estimation algorithms are proposed. The performance of these algorithms is evaluated analytically and validated via experimental results.

Description: The design of complex analog interfaces would largely benefit from model-based development and compositional methods to improve the quality of its final result. However, analog circuit behaviors are so tightly intertwined with their environment that: 1) abstractions needed for model-based design are often not accurate, thus making it difficult to achieve reliable system performance estimations, and 2) generic, design-independent interfaces that are needed to develop compositional techniques are very difficult to define. In this paper, we propose a platform-based design methodology that uses analog contracts to develop reliable abstractions and design-independent interfaces. A contract explicitly handles pairs of properties, representing the assumptions on the environment and the promises of a component under these assumptions. Horizontal contracts encode composition rules that constrain how library elements should be “legally” used. Vertical contracts define under which conditions an aggregation of components satisfies the requirements posed at a higher level of abstraction. If both sets of contracts are satisfied, we can produce implementations by composition and refinement that are correct by construction. We demonstrate the effectiveness of this approach on the design of an ultra-wide band receiver used in an Intelligent Tire system, an on-vehicle wireless sensor network for active safety applications.

Description: A smart system for flow measurement is presented, consisting of a micromachined thermal flow sensor combined with a smart front-end electronic interface. The flow sensor is based on a novel thermal transduction method, which combines the hot-film and calorimetric sensing principles. The sensor consists of four germanium thermistors embedded in a thin membrane and connected to form a Wheatstone bridge supplied with a constant DC current. In this configuration, both the bridge unbalance voltage and the voltage at the bridge supply terminals are functions of the flow offering high initial sensitivity, i.e., near zero flow and wide measurement range, respectively. The front-end interface is based on a CMOS relaxation oscillator circuit where the frequency and the duty cycle of a rectangular-wave output signal are related to the bridge unbalance voltage and the voltage at the bridge supply terminals, respectively. Furthermore, the amplitude of the output signal is a linear function of the operating temperature. In this way, a single output signal advantageously carries two pieces of information related to the flow velocity and provides an additional measurement of the sensor operating temperature, which enables the correction of the temperature dependence of the sensor readouts. The system has been experimentally characterized for the measurement of nitrogen gas flow velocity at different sensor temperatures. The initial sensitivities at room temperature result 13.7 kHz/(m/s) and 23.5%/(m/s), in agreement with FEM simulations, for frequency and duty cycle readouts, respectively, with an equivalent velocity resolution of about 0.5 and 1.3 cm/s.

Description: An automated data fusion and visualization process is developed for nondestructive evaluation and direct visualization of internal defects of concrete structures based on impact-echo testing using source–receiver arrays. In the process, the ratio between the amplitudes of major echo peaks in the frequency spectrum (after noise reduction) and the bottom echo signal is proposed as a feature parameter for data fusion. The fused results then go through image segmentation, which combines thresholding and region growing to extract defect regions for visualization. The effectiveness of the automated data fusion and visualization process is validated using both numerical simulation and experimental testing.

Description: Integrated complementary metal-oxide-semiconductor (CMOS)-microelectro mechanical systems (MEMS) beam-array resonators that take advantage of the pull-in effect to surmount limitations of standard CMOS foundry processes have been demonstrated to attain electrode-to-resonator gap spacing at a deep-submicrometer range. Such deep-submicrometer gaps lead to much larger electromechanical coupling coefficient and smaller motional impedance as compared with conventional CMOS-MEMS technologies. In addition, a unique frequency tuning capability by modulating the mechanical boundary conditions (“BC”) of the resonators has also been proposed. Furthermore, the mechanically coupled array approach used in this paper not only provides five times smaller motional impedance compared with that of a single resonator but offers superior power handling capability due to higher stiffness of the arrayed resonator. In such an array design, high velocity coupling for beam-array resonators effects a single resonance behavior without spurious modes. With the increase of an applied dc-bias which simultaneously serves for functions of pull-in and resonator operation, the upward frequency shift of resonance caused by boundary condition change offers opposite tuning mechanism against the well-known effect of electrical stiffness. As a result, frequency variation induced by the BC-modulation and electrical stiffness would yield a frequency-insensitive region under a certain dc-bias voltage. Furthermore, the use of metal/oxide composite materials for resonator structures in this paper substantially alleviates residual stress often seen in the CMOS layers as compared to mere-metal resonators.

Description: We report the fabrication and characterization of a surface plasmon resonance (SPR)-based fiber-optic sensor for the detection of low-density lipoprotein (LDL). The probe is prepared by first coating a 50-nm-thick gold film on the unclad portion of the optical fiber core and then immobilizing 4-aminothiophenol (4-ATP), followed by antiapolipoprotein B, over the 4-ATP/Au surface. Spectral interrogation technique is used for the characterization of the probe. SPR spectra are recorded for sample solutions of LDL with concentrations in the range of 0–190 mg/dl. Sensitivity of the sensor is found to be 0.18387 nm per mg/dl. Furthermore, the response time of the sensor is very small (around 2 min). The sensor can be utilized in online monitoring as well. This paper may result in the commercialization of a miniaturized low-cost reusable fast and accurate optical fiber sensor for the detection of LDL level in human blood.

Description: This paper introduces a new foundation for ultra-cooperative communications based on very low signal-to-noise ratio (SNR) channels between mobile sensor nodes grouped in spatially distributed clusters. In this new framework, we define a cluster entity as a sensor network of wireless nodes with, but not limited to, scale-free topology. We define a physical wireless scale-free model for the clusters that extends the abstract scale-free model developed by Barabasi-Albert for network graphs to the wireless channel. Our air interface model is based on orthogonal frequency division multiplexing with Rayleigh flat fading channels and additive white Gaussian noise. For intracluster communications, we have developed the new concept of consensus in a wireless network framework to improve performance. This new approach is ideal for distributed long-range low power sensor networks with ultra-low power signals well below the noise floor. For a cluster size of 100 nodes, we achieve BER of at an SNR of ${-}{rm 25}~{rm dB}$ in Rayleigh fading. This method enables reliability in both fading channels for intracluster communications and can support ultra-long range or ultra-low power communications links. We establish the fundamental principles involving the relationship between cluster sizes and communication performance, and illustrate $7times$ gains in range performance using HATA path loss models.

Description: A low power temperature sensor followed by a switched capacitor amplifier, a buffer stage, and a 12-bit successive approximation analogue-to-digital converter (ADC) for autonomous multi-sensor systems is presented. The proposed design is accurate within 0.01 $^{circ}{rm C}$ from ${-}{rm 55}^{circ}{rm C}$ to 125 $^{circ}{rm C}$ . A proportional to absolute temperature source was used as a temperature sensor. The read-out enables a differential reading of a reference and actual temperature. The subsequent ADC digitizes the output signal. The ADC has a figure-of-merit of 66 fJ/conversion-step at a bit-clock of 50 kHz. The system is implemented in an NXP CMOS 0.14- $mu{rm m}$ technology. The die area is 0.27 ${rm mm}^{2}$ , and the whole system consumes less than 16 $mu{rm W}$ . Design and measurements are presented.

Description: In this paper, research on a vibration sensor (accelerometer) that converts mechanical load to an electrical signal is carried out. An accelerometer mathematical model is developed to select the best damping rate value to reduce the measurement error as much as possible. The main purpose of this paper is to enhance the vibration sensor performances (choice of the best value of damping rate and minimization of measurement error by increasing sensor precision and reliability). The developed model is validated by computer simulation and experimental tests. The obtained results have demonstrated that an appropriate damping rate can reduce measurement error of relative movement to 1%.

Description: A simple sensor system designed to monitor the temperature or strain of a certain number of critical points along a structure is presented and demonstrated. It is based on the remote interrogation of fiber Bragg gratings (FBGs) placed in series by means of a Brillouin fiber laser. Three FBGs were interrogated 50 km from the processing unit using 8 mW of Brillouin pump. Heterodyne detection brings forth a signal-to-noise ratio of approximately 40 dB in our measurements.

Description: The publication offers a note of thanks and lists its reviewers.

Description: One of the fundamental issues in sensor networks is the coverage problem, which reflects how well a field is monitored or tracked by sensors. Various versions of this problem have been studied, such as object, area, barrier, and hole coverage problems. In this paper, we define a new $k$ -angle object coverage problem in a wireless sensor network. Each sensor can only cover a limited angle and range, but can freely rotate to any direction to cover a particular angle. Given a set of sensors and a set of objects at known locations, the goal is to use the least number of sensors to $k$ -angle-cover the largest number of objects such that each object is monitored by at least $k$ sensors satisfying some angle constraint. We propose centralized and distributed polynomial-time algorithms to solve this problem. Simulation results show that our algorithms can be effective in maximizing coverage of objects. A prototype system is developed to demonstrate the usefulness of angle coverage.

Description: Morphological image processing is a type of processing based on the theory of mathematical morphology, by which the spatial forms or the structures of objects in an image are modified. This objects-oriented image processing is advantageous for a sensor to make a decision, although is not good enough for visual aesthetics (or entertainment) purposes. Therefore, morphological image processing is suitable for sensing applications. It is noted that there are two special features associated with the video sensor networks: 1) limited resource and 2) the nonvisual aesthetics (or not for entertainment) purpose. Therefore, an approach of particular image processing on the sensor network is proposed in this paper. In this approach, the image is compressed using the quad tree data structure and is also processed in this structure using morphological operations to achieve the sensing purpose. Both the speed and the compression efficiencies of this proposed approach are verified from the sensor's perspective in our experiments.

Description: The remotely powered underwater acoustic sensor networks (RPUASN) paradigm is introduced, whereby sensor nodes harvest and store the power supplied by an external acoustic source, indefinitely extending their lifetime. Necessary source characteristics are determined. Feasibility is illustrated with realistic examples, and open research issues are pointed out. Performance of RPUASN is directly related to the sensing coverage and communication connectivity over the field the sensor nodes are deployed. The required number of RPUASN nodes and the volume which is guaranteed to be covered by the nodes are analyzed in terms of electrical power, range, directivity, and transmission frequency of the external acoustic source, and node power requirements.

Description: The design, implementation, and characterization of a microelectromechanical systems (MEMS) capacitive accelerometer-based middle ear microphone are presented in this paper. The microphone is intended for middle ear hearing aids as well as future fully implantable cochlear prosthesis. Human temporal bones acoustic response characterization results are used to derive the accelerometer design requirements. The prototype accelerometer is fabricated in a commercial silicon-on-insulator (SOI) MEMS process. The sensor occupies a sensing area of 1 mm × 1 mm with a chip area of 2 mm × 2.4 mm and is interfaced with a custom-designed low-noise electronic IC chip over a flexible substrate. The packaged sensor unit occupies an area of 2.5 mm × 6.2 mm with a weight of 25 mg. The sensor unit attached to umbo can detect a sound pressure level (SPL) of 60 dB at 500 Hz, 35 dB at 2 kHz, and 57 dB at 8 kHz. An improved sound detection limit of 34-dB SPL at 150 Hz and 24-dB SPL at 500 Hz can be expected by employing start-of-the-art MEMS fabrication technology, which results in an articulation index of approximately 0.76. Further micro/nanofabrication technology advancement is needed to enhance the microphone sensitivity for improved understanding of normal conversational speech.

Description: Breathwalk is a science of combining specific patterns of footsteps synchronized with the breathing. In this study, we developed a multimedia-assisted Breathwalk-aware system which detects user's walking and breathing conditions and provides appropriate multimedia guidance on the smartphone. Through the mobile device, the system enhances user's awareness of walking and breathing behaviors. As an example application in slow technology, the system could help meditator beginners learn “walking meditation,” a type of meditation which aims to be as slow as possible in taking pace, to synchronize footstep with breathing, and to land every footstep with toes first. In the pilot study, we developed a walking-aware system and evaluated whether multimedia-assisted mechanism is capable of enhancing beginner's walking awareness while walking meditation. Experimental results show that it could effectively assist beginners in slowing down the walking speed and decreasing incorrect footsteps. In the second experiment, we evaluated the Breathwalk-aware system to find a better feedback mechanism for learning the techniques of Breathwalk while walking meditation. The experimental results show that the visual-auditory mechanism is a better multimedia-assisted mechanism while walking meditation than visual mechanism and auditory mechanism.

Description: We have acquired 2-D and 3-D microwave tomographic images of the calcaneus bones of two patients to assess correlation of the microwave properties with X-ray density measures. The two volunteers were selected because each had one leg immobilized for at least six weeks during recovery from a lower leg injury. A soft-prior regularization technique was incorporated with the microwave imaging to quantitatively assess the bulk dielectric properties within the bone region. Good correlation was observed between both permittivity and conductivity and the computed tomography-derived density measures. These results represent the first clinical examples of microwave images of the calcaneus and some of the first 3-D tomographic images of any anatomical site in the living human.

Description: Diagnostic confirmation of cancer in solid organs is based on biopsy findings. In a standard 12-core prostate biopsy protocol, conventional biopsy needles sample only 0.95% (∼0.228 cm $^{3}$ ) of a typical 24-cm $^{3}$ prostate gland. The primary objective of this study was to enhance the sensitivity of standard biopsy protocol by gauging electrical properties of tissue simultaneously with tissue extraction for histopathology analysis. A conventional biopsy (Bx) needle was instrumented with an electrical impedance spectroscopy (EIS) sensor to interrogate the tissue volume surrounding the needle tip. The EIS-Bx device was evaluated in a series of saline bath and ex vivo porcine experiments. It was found to sense a volume of 0.286 cm $^{3}$ of tissue around the needle tip. EIS measurements were recorded from three ex vivo human prostates using the device, and the extracted biopsy cores were histologically assessed. Prostate conductivity σ ranged from 0.179 to 0.3310 S/m for benign tissues and 0.0746 to 0.0837 S/m for malignant tissues at frequencies ranging from 1 to 100 kHz. Relative permittivity ϵ $_{r}$ ranged from 2.10×10 $^{6}$ to 2.9 × 10 $^{4}$ for benign and 6.63×10 $^{5}$ to 5.3 × 10 $^{3}$ for cancer tissues over the same frequency range. Both are found to be significantly higher in normal prostate tissues than in malignant tissue $(p$ 〈 0.00001).

Description: Due to the growing shortage of donor livers, more patients are waiting for transplantation. Living donor liver transplantation may help expanding the donor pool, but is often confronted with the small-for-size syndrome. Since the hemodynamic effects of partial hepatectomy are not fully understood, we developed an electrical rat liver model to compare normal with resected liver hemodynamics. Detailed geometrical data and 3-D reconstructions of the liver vasculature of two rats were gathered by combining vascular corrosion casting, micro-CT scanning, and image processing. Data extrapolations allowed obtaining a total liver pressure- and flow-driven electrical analog. Subsequently, virtual resections led to 70%, 80%, or 90% partial hepatectomy models. Results demonstrated hyperperfusion effects such as portal hypertension and elevated lobe-specific portal venous flows (11, 12, and 24 mmHg, and 1.0–3.0, 1.8–3.5, and 7.4 ml/min for 70%, 80%, and 90% hepatectomy, respectively). Comparison of two 90% resection techniques demonstrated different total arterial flows (0.28 ml/min versus 0.61 ml/min), portal (24 mmHg versus 21 mmHg), and sinusoidal pressures (14 mmHg versus 9.5–12 mmHg), probably leading to better survival for lower portal and sinusoidal pressures. Toward the future, the models may be extrapolated to human livers and help us to optimize hepatectomy planning.

Description: This paper presents a useful technique for totally automatic detection of myocardial infarction from patients’ ECGs. Due to the large number of heartbeats constituting an ECG and the high cost of having all the heartbeats manually labeled, supervised learning techniques have achieved limited success in ECG classification. In this paper, we first discuss the rationale for applying multiple instance learning (MIL) to automated ECG classification and then propose a new MIL strategy called latent topic MIL, by which ECGs are mapped into a topic space defined by a number of topics identified over all the unlabeled training heartbeats and support vector machine is directly applied to the ECG-level topic vectors. Our experimental results on real ECG datasets from the PTB diagnostic database demonstrate that, compared with existing MIL and supervised learning algorithms, the proposed algorithm is able to automatically detect ECGs with myocardial ischemia without labeling any heartbeats. Moreover, it improves classification quality in terms of both sensitivity and specificity.

Description: In high-field magnetic resonance imaging (MRI) systems, $B_0$ fields of 7 and 9.4 T, the RF field shows greater inhomogeneity compared to clinical MRI systems with $B_0$ fields of 1.5 and 3.0 T. In multichannel RF coils, the magnitude and phase of the input to each coil element can be controlled independently to reduce the nonuniformity of the RF field. The convex optimization technique has been used to obtain the optimum excitation parameters with iterative solutions for homogeneity in a selected region of interest. The pseudoinverse method has also been used to find a solution. The simulation results for 9.4- and 7-T MRI systems are discussed in detail for the head model. Variation of the simulation results in a 9.4-T system with the number of RF coil elements for different positions of the regions of interest in a spherical phantom are also discussed. Experimental results were obtained in a phantom in the 9.4-T system and are compared to the simulation results and the specific absorption rate has been evaluated.

Description: Motivated by the goals of automatically extracting vessel segments and constructing retinal vascular trees with anatomical realism, this paper presents and analyses an algorithm that combines vessel segmentation and grouping of the extracted vessel segments. The proposed method aims to restore the topology of the vascular trees with anatomical realism for clinical studies and diagnosis of retinal vascular diseases, which manifest abnormalities in either venous and/or arterial vascular systems. Vessel segments are grouped using extended Kalman filter which takes into account continuities in curvature, width, and intensity changes at the bifurcation or crossover point. At a junction, the proposed method applies the minimum-cost matching algorithm to resolve the conflict in grouping due to error in tracing. The system was trained with 20 images from the DRIVE dataset, and tested using the remaining 20 images. The dataset contained a mixture of normal and pathological images. In addition, six pathological fluorescein angiogram sequences were also included in this study. The results were compared against the groundtruth images provided by a physician, achieving average success rates of 88.79% and 90.09%, respectively.

Description: Model averaging is a widely used technique in biomedical applications. Two established model averaging methods, iterative shape averaging (ISA) method and virtual insect brain (VIB) method, have been applied to several organisms to generate average representations of their brain surfaces. However, without sufficient samples, some features of the average Drosophila brain surface obtained using the above methods may disappear or become distorted. To overcome this problem, we propose a Bézier-tube-based surface model averaging strategy. The proposed method first compensates for disparities in position, orientation, and dimension of input surfaces, and then evaluates the average surface by performing shape-based interpolation. Structural features with larger individual disparities are simplified with half-ellipse-shaped Bézier tubes, and are unified according to these tubes to avoid distortion during the averaging process. Experimental results show that the average model yielded by our method could preserve fine features and avoid structural distortions even if only a limit amount of input samples are used. Finally, we qualitatively compare our results with those obtained by ISA and VIB methods by measuring the surface-to-surface distances between input surfaces and the averaged ones. The comparisons show that the proposed method could generate a more representative average surface than both ISA and VIB methods.

Description: The aim of this study is to investigate muscular fatigue and to propose a new fatigue index based on the continuous wavelet transform (CWT) which is compared to the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles [electromyogram (EMG)] acquired during an electrically stimulated contraction thanks to two modules (electromyostimulation + electromyography recording) that can analyze EMG signals in real time during electromyostimulation. The extracted parameters are compared with each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustness of the index obtained using CWT.

Description: Patient-specific mathematical models of respiratory mechanics can offer substantial insight into patient state and pulmonary dynamics that are not directly measurable. Thus, they offer significant potential to evaluate and guide patient-specific lung protective ventilator strategies for acute respiratory distress syndrome (ARDS) patients. To assure bedside applicability, the model must be computationally efficient and identifiable from the limited available data, while also capturing dominant dynamics and trends observed in ARDS patients. In this study, an existing static recruitment model is enhanced by considering alveolar distension and implemented in a novel time-continuous dynamic respiratory mechanics model. The model was tested for structural identifiability and a hierarchical gradient descent approach was used to fit the model to low-flow test responses of 12 ARDS patients. Finally, a comprehensive practical identifiability analysis was performed to evaluate the impact of data quality on the model parameters. Identified parameter values were physiologically plausible and very accurately reproduced the measured pressure responses. Structural identifiability of the model was proven, but practical identifiability analysis of the results showed a lack of convexity on the error surface indicating that successful parameter identification is currently not assured in all test sets. Overall, the model presented is physiologically and clinically relevant, captures ARDS dynamics, and uses clinically descriptive parameters. The patient-specific models show the ability to capture pulmonary dynamics directly relevant to patient condition and clinical guidance. These characteristics currently cannot be directly measured or established without such a validated model.

Description: In this paper, a new conductive polymer foam-surfaced electrode was proposed for use as a capacitive EEG electrode for nonintrusive EEG measurements in out-of-hospital environments. The current capacitive electrode has a rigid surface that produces an undefined contact area due to its stiffness, which renders it unable to conform to head curvature and locally isolates hairs between the electrode surface and scalp skin, making EEG measurement through hair difficult. In order to overcome this issue, a conductive polymer foam was applied to the capacitive electrode surface to provide a cushioning effect. This enabled EEG measurement through hair without any conductive contact with bare scalp skin. Experimental results showed that the new electrode provided lower electrode–skin impedance and higher voltage gains, signal-to-noise ratios, signal-to-error ratios, and correlation coefficients between EEGs measured by capacitive and conventional resistive methods compared to a conventional capacitive electrode. In addition, the new electrode could measure EEG signals, while the conventional capacitive electrode could not. We expect that the new electrode presented here can be easily installed in a hat or helmet to create a nonintrusive wearable EEG apparatus that does not make users look strange for real-world EEG applications.

Description: Understanding the skin's material properties and natural motion is critical to a myriad of applications from tissue engineering to spacesuits. While there is an extensive understanding of human skin properties based on active tensile testing, both in vitro and in vivo, there is a little current knowledge of the strains experienced by skin during natural movements. Using a motion capture system, we have developed a new technique to measure skin movement and strain around the knee during a squatting motion. With these new data, we are also able to calculate the local direction of lines of nonextension, or contours of the skin that remain a constant length during motion, lines of minimum extension, and lines of minimum compression.

Description: A partially perturbed particle swarm optimization (PPSO) has been proposed for identifying the parameters of the Beeler–Reuter (BR) equation from action potential data. In the PPSO algorithm, the 63 BR equation parameters are divided into groups, and parameter patterns are made from the combination of the groups. PPSO enhances the capability of conventional particle swarm optimization (CPSO) by partially perturbing the coordinates of the globally best particle with the patterns when the searching process is locally confined. “Experimental data” were produced for cardiac myocytes simulated by the BR equation and the equation of Luo and Rudy (1991), and were used to test the algorithm of PPSO. The test results show that PPSO was able to identify the parameters of the BR equation effectively for different cardiac myocytes, while still retaining the conceptual simplicity and easy implementation of CPSO.

Description: Accurate glycemic control (AGC) is difficult due to excessive hypoglycemia risk. Stochastic TARgeted (STAR) glycemic control forecasts changes in insulin sensitivity to calculate a range of glycemic outcomes for an insulin intervention, creating a risk framework to improve safety and performance. An improved, simplified STAR framework was developed to reduce light hypoglycemia and clinical effort, while improving nutrition rates and performance. Blood glucose (BG) levels are targeted to 80–145 mg/dL, using insulin and nutrition control for 1–3 h interventions. Insulin changes are limited to +3U/h and nutrition to ±30% of goal rate (minimum 30%). All targets and rate change limits are clinically specified and generalizable. Clinically validated virtual trials were run on using clinical data from 371 patients (39841 h) from the Specialized Relative Insulin and Nutrition Tables (SPRINT) cohort. Cohort and per-patient results are compared to clinical SPRINT data, and virtual trials of three published protocols. Performance was measured as time within glycemic bands, and safety by patients with severe (BG 〈 40 mg/dL) and mild (%BG 〈 72 mg/dL) hypoglycemia. Pilot trial results from the first ten patients (1486 h) are included to support the in-silico findings. In both virtual and clinical trials, mild hypoglycemia was below 2% versus 4% for SPRINT. Severe hypoglycemia was reduced from 14 (SPRINT) to 6 (STAR), and 0 in the pilot trial. AGC was tighter than both SPRINT clinical data and in-silico comparison protocols, with 91% BG within the specified target (80–145 mg/dL) in virtual trials and 89.4% in pilot trials. Clinical effort (measurements) was reduced from 16.2/day to 11.8/day (13.5/day in pilot trials). This STAR framework provides safe AGC with significant reductions in hypoglycemia and clinical effort due - o stochastic forecasting of patient variation—a unique risk-based approach. Initial pilot trials validate the in-silico design methods and resulting protocol, all of which can be generalized to suit any given clinical environment.