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The article investigates the noise level and mission-to-mission stability of Global Positioning System (GPS) radio occultation (RO) neutral atmospheric bending angle data at the UCAR COSMIC Data Analysis and Archive Center in the U.S. The angle is quantified based on random and differences for various satellites and instruments. Higher noise level is noted for F3C bending angles compared to Metop/GRAS bending angles. The GRAS bending angle profiles are found relative to climatology.

Faculty in the College of Engineering at the University of Alabama developed a multidisciplinary course in applied spectral analysis that was first offered in 1996. The course is aimed at juniors majoring in electrical, mechanical, industrial, or aerospace engineering. No background in signal processing or Fourier analysis is assumed; the requisite fundamentals are covered early in the course and followed by a series of laboratories in which the fundamental concepts are applied. In this paper, a laboratory module on fault detection in rolling element bearings is presented. This module is one of two laboratory modules focusing on machine condition monitoring applications that were developed for this course. Background on the basic operational characteristics of rolling element bearings is presented, and formulas given for the calculation of the characteristic fault frequencies. The shortcomings of conventional vibration spectral analysis for the detection of bearing faults is examined in the context of a synthetic vibration signal that students generate in MATLAB. This signal shares several key features of vibration signatures measured on bearing housings. Envelope analysis and the connection between bearing fault signatures and amplitude modulation/demodulation is explained. Finally, a graphically driven software utility (a set of MATLAB m-files) is introduced. This software allows students to explore envelope analysis using measured data or the synthetic signal that they generated. The software utility and the material presented in this paper constitute an instructional module on bearing fault detection that can be used as a stand-alone tutorial or incorporated into a course. [ABSTRACT FROM AUTHOR]

The low cost, simple, noninvasive, and continuous measurement of cerebral blood flow velocity (CBFV) by transcranial Doppler is becoming a common clinical tool for the assessment of cerebral hemodynamics. CBFV monitoring can also help with noninvasive estimation of intracranial pressure and evaluation of mild traumatic brain injury. Reliable CBFV waveform analysis depends heavily on its accurate beat-to-beat delineation. However, CBFV is inherently contaminated with various types of noise/artifacts and has a wide range of possible pathological waveform morphologies. Thus, pulse onset detection is in general a challenging task for CBFV signal. In this paper, we conducted a comprehensive comparative analysis of three popular pulse onset detection methods using a large annotated dataset of 92,794 CBFV pulses—collected from 108 subarachnoid hemorrhage patients admitted to UCLA Medical Center. We compared these methods not only in terms of their accuracy and computational complexity, but also for their sensitivity to the selection of their parameters' values. The results of this comprehensive study revealed that using optimal values of the parameters obtained from sensitivity analysis, one method can achieve the highest accuracy for CBFV pulse onset detection with true positive rate (TPR) of 97.06% and positive predictivity value (PPV) of 96.48%, when error threshold is set to just less than 10 ms. We conclude that the high accuracy and low computational complexity of this method (average running time of 4ms/pulse) makes it a reliable algorithm for CBFV pulse onset detection. [ABSTRACT FROM AUTHOR]

Despite their importance as a fundamental constraint on Earth properties, regional-scale measurements of body-wave seismic attenuation are scarce. This is partially a result of the difficulty in producing robust estimates of attenuation. In this paper, we focus on measuring differential attenuation on records of teleseismic P waves. We examine a unique data set of five records of the North Korean nuclear test of 2017 measured at five broad-band seismic stations deployed within a few metres of each other but using different installation procedures. Given their extreme proximity, we expect zero differential intrinsic attenuation between the different records. However, we find that different attenuation measurement methods and implementation parameters in fact produce significant apparent differential attenuation (Δ t *). Frequency-domain methods yield a wide range of Δ t * estimates between stations, depending on measurement bandwidth and nuances of signal processing. This measurement instability increases for longer time windows. Time domain methods are largely insensitive to the frequency band being considered but are sensitive to the time window that is chosen. We determine that signal-generated noise can affect measurements in both the frequency and time domain. In some cases, the range of results amounts to a significant fraction of the range of differential attenuation across the conterminous United States as determined by a recent study. We suggest some approaches to manage the inherent instability in these measurements and recommend best practices to confidently estimate body wave attenuation. [ABSTRACT FROM AUTHOR]

With the transition to digital terrestrial television (DTV) in the U.S. scheduled to be complete by 2009, the Federal Communications Commission (FCC) has issued a notice of proposed rule making (NPRM) that, if adopted, would allow transmission by unlicensed devices on frequencies of vacated television channels. The FCC is required by statute to avoid harmful interference to licensed TV channels. This paper addresses two of the core questions related to the proposed introduction of unlicensed transmissions in the vacated TV channels: Do the proposed rules provide DTV stations adequate protection from interference from these devices? If not, what rules must be adopted to avoid harmful interference to terrestrial DTV service from these devices? [ABSTRACT FROM AUTHOR]

This paper highlights recent results obtained with the Turbulent Eddy Profiler (TEP), which was developed by the University of Massachusetts. This unique 915-MHz radar has up to 64 spatially separated receiving elements, each with an independent receiver. The calibrated raw data provided by this array could be processed using sophisticated imaging algorithms to resolve the horizontal structures within each range gate. After collecting all of the closely spaced horizontal slices, the TEP radar can produce three-dimensional images of echo power, radial velocity, and spectral width. From the radial velocity measurements, it is possible to estimate the three-dimensional wind with high horizontal and vertical resolution. Given the flexibility of the TEP system, various array configurations are possible. In the present work exploitation of the flexibility of TEP is attempted to enhance the rejection of clutter from unwanted biological targets. From statistical studies, most biological clutter results from targets outside the main imaging field of view, that is, the sidelobes and grating lobes (if they exist) of the receiving beam. Because the TEP array's minimum receiver separation exceeds the spatial Nyquist sampling requirement, substantial possibilities for grating-lobe clutter exist and are observed in actual array data. When imaging over the transmit beam volume, the receiving array main lobe is scanned over a ±12.5° region. This scanning also sweeps the grating lobes over a wide angular region, virtually guaranteeing that a biological scatterer outside of the main beam will appear somewhere in the imaged volume. This paper focuses on suppressing pointlike targets in the grating-lobe regions. With a subtle change to the standard TEP array hardware configuration, it is shown via simulations and actual experimental observations (collected in June 2003) that adaptive beamforming methods can subsequently be used to significantly suppress the effects of point targets on the wind field estimates. These pointlike targets can be birds or planes with strong reflectivity. By pointlike the authors mean its appearance is a distinct point (up to the imaging resolution) in the images. The pointlike strong reflectivity signature exploits the capability of adaptive beamforming to suppress the interference using the new array configuration. It should be noted that this same array configuration does not exhibit this beneficial effect when standard Fourier beamforming is employed. [ABSTRACT FROM AUTHOR]

Reliable bridge-condition evaluation and early detection of bridge-component failures are critical for bridge owners in the US for better utilization of available resources. Remote bridge monitoring systems (RBMS) have been perceived to assist periodic evaluation of structures to supplement bridge-management systems with quantitative data, and for examining new design techniques. Many RBMS thus far are based on measured bridge vibration. One of the major issues in developing RBMS is lack of reliable methods to obtain modal parameters using traffic excitation. This paper addresses one such signal processing method and discusses the results obtained using data measured from one of the RBMS installed in New York State bridges. Results indicate that it is necessary to find the natural modes, which are most insensitive to environmental parameter variations, for structural monitoring and damage detection. [ABSTRACT FROM AUTHOR]

In this paper, we first investigate the power spectral densities (PSD) of bipolar modulated Direct Sequence Ultra Wide Band (DS-UWB) signals using various pulse shapes under the FCC UWB emission mask. Considered pulse shapes are the first five derivatives of the Gauss pulse (p1, p2, p3, p4 and p5), the first four orthogonal modified Hermite waveforms, and Daubechies wavelets (db-q). It is observed in the PSD results that p4 and p5 Gauss pulses, the Daubechies (db-q) for q>4 comply with the FCC UWB rule by selecting proper values for the pulse duration. Then, we derive the pulse shape dependent probability of error expression for bipolar DS-UWB signals over the standard UWB channel. The five pulse shapes (p4, p5, db-5, db-6 and db-7) complying with the FCC emission mask are numerically compared by using the derived probability of error expression over the CM1 model of the Standard UWB channel. Results reveal that the Daubechies have better performance than those of the two Gauss pulses. [ABSTRACT FROM AUTHOR]

At Rice University, we have undertaken a project to construct a framework for generating high-level problem solving languages that can achieve high performance on a variety of platforms. The underlying strategy, called telescoping languages, builds problem-solving systems from domain-specific libraries and scripting languages by extensively preanalyzing libraries to produce a precompiler that optimizes library calls within the scripts as if they were primitives in the underlying language. Our study of applications written in Matlab by the signal processing group at Rice University has identified a collection of old and new optimizations that show promise for this particular domain. Two promising new optimizations are procedure vectorization and procedure strength reduction. By transforming these programs, at source level, according to the strategies described in this paper, we were able to achieve speedups ranging from a factor of 1.1 to 1.6 over the entire applications—with speedups for individual functions as high as 3.3. [ABSTRACT FROM AUTHOR]

Bridges are the essential components in lifeline transportation systems, and their safe operation is of great importance. Information on structural damage could assist in timely repairs and reduce downtime. With the latest advancements in sensing technology, collecting vibration data from bridges has become more accessible. However, effective vibration processing is still a challenge, given the high dimensionality and massive size of vibration data. Existing studies have shown that machine/deep learning techniques can be valuable tools for this task. However, the learning and computational capacities of these models are challenged in the presence of large sensor arrays. We propose Trident as a novel deep learning framework that enables automatic damage feature extraction by simultaneously learning from temporal and three-dimensional (3D) spatial variations of 6D input data in instrumented bridges. Trident is equipped with 3 ConvLSTM3D branches to achieve this goal. A 3D steel truss bridge subject to dynamic traffic loads is monitored for its vibrations to evaluate Trident's robustness in finding damaged elements. A damage dataset of 52,800 vehicle passing simulations is generated leveraging a database of 528 passenger vehicles in the United States, obtained from the National Highway and Traffic Safety Administration. Bayesian optimization is utilized to tune the model's hyperparameters, achieving a test Node Average Geometric Mean Accuracy of 86%. This level of performance is promising given the high dimensionality and complexities of the output space in vibration-based monitoring. Trident's concept can be extended to other vibration monitoring tasks with different time series data and damage labeling strategies. [ABSTRACT FROM AUTHOR]

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description. [ABSTRACT FROM AUTHOR]

Abstract: Based on such criteria as safety and mission success, programmatic risk, affordability, and extensibility/flexibility, the National Aeronautics and Space Administration (NASA) has chosen fission surface power (FSP) as the primary energy source for building a sustained human presence on the Moon, exploring Mars, and extremely long-duration space missions. The current benchmark FSP system has a mission life of at least 8 years during which time there is no opportunity for repair, sensor calibrations, or periodic maintenance tasks that are normally performed on terrestrial-based nuclear power plants during scheduled outages. Current technology relies heavily on real-time human interaction, monitoring and control. However; due to the long communication times between the Earth and Moon, or Mars, real-time human control is not possible, resulting in a critical need to develop autonomous health monitoring technology for FSP systems.This paper describes the design and development of an autonomous health monitoring system that will (1) provide on-line calibration monitoring, (2) reduce uncertainties in sensor measurements, and (3) provide sensor validation and fault detection capabilities for the control systems of various FSP subsystems. The health monitoring system design integrates a number of signal processing algorithms and techniques such as cross-calibration, empirical modeling using neural networks, and physical modeling under a modular signal processing platform that will enable robust sensor and system monitoring without the need for human interaction. Prototypes of the health monitoring system have been tested and validated on data acquired from preliminary subsystem testing of NASA''s FSP Technology Demonstration Unit (TDU) as well as simulated laboratory data. Results from this testing have demonstrated the utility and benefits that such autonomous health monitoring systems can provide to FSP subsystems and other potential applications within NASA such as launch vehicle systems, other nuclear power systems, and ground operations. [Copyright &y& Elsevier]

We present a parametric framework for the joint processing of heterogeneous data, specifically for a binary classification problem. Processing such a data set is not straightforward as heterogeneous data may not be commensurate. In addition, the signals may also exhibit statistical dependence due to overlapping fields of view. We propose a copula-based solution to incorporate statistical dependence between disparate sources of information. The important problem of identifying the best copula for binary classification problems is also addressed. Computer simulation results are presented to demonstrate the feasibility of our approach. The method is also tested on real-data provided by the National Institute of Standards and Technology (NIST) for a multibiometric face recognition application. Finally, performance limits are derived to study the influence of statistical dependence on classification performance. [ABSTRACT FROM AUTHOR]

Abstract: Four decades ago, argued that spatial autocorrelation (i.e., local distance and configuration effects) and distance decay (i.e., global distance effects) intermingle in the estimation of spatial interaction model specifications. Today, massive computer power available with a desktop PC offers the necessary resources to account for these spatial autocorrelation effects within spatial interaction. Simple gravity model respecifications have been analyzed by and by . These results have been extended to a doubly-constrained gravity model respecification by . This paper summarizes results from a further refinement of this doubly-constrained respecification, namely differentiating within and between areal unit flows. In doing so, an eigenfunction-based spatial filter description of spatial autocorrelation is constructed, which lends itself to visualization of analytical spatial autocorrelation components. Results are illustrated with the 2000 journey-to-work dataset for the extended state of Pennsylvania, USA. [Copyright &y& Elsevier]

Abstract: Contemporary narratology (narrative theory) offers a useful framework for interpreting interstellar messages that have already been sent to potential extraterrestrial recipients, as well as for designing messages that may be transmitted in the future. In this paper, narratological concepts are used to analyze in depth a single interstellar message sequence, elucidating methods by which various parts of speech (nouns, verbs, adjectives, and adverbs) can be paired with pictures to describe the human body in motion. The concept of focalization is applied to the message sequence''s use of isolation and magnification, which highlight the structure and function of the human body and its constituent parts. The challenges of interpreting gaps within narratives, as well as the setting in which events occur, are considered. The importance of closure in providing a fitting end to narratives is examined, and the plausibility of creating images that could be interpreted correctly by extraterrestrial intelligence is assessed. Narratological concepts examined here, as well as additional aspects of narrative, provide important resources for future work in interpreting and designing interstellar messages. [Copyright &y& Elsevier]

Abstract: The aim of HuLCC (the human language chorus corpus), is to provide a resource of sufficient size to facilitate inter-language analysis by incorporating languages from all the major language families: for the first time all aspects of typology will be incorporated within a single corpus, adhering to a consistent grammatical classification and granularity, which historically adopt a plethora of disparate schemes. An added feature will be the inclusion of a common text element, which will be translated across all languages, to provide a precise comparable thread for detailed linguistic analysis for translation strategies and a mechanism by which these mappings can be explicitly achieved. Methods developed to solve unambiguous mappings across these languages can then be adopted for any subsequent message authored by the SETI community. Initially, it is planned to provide at least 20,000 words for each chosen language, as this amount of text exceeds the point where randomly generated text can be disambiguated from natural language and is of sufficient size useful for message transmission (Elliot, 2002). This paper details the design of this resource, which ultimately will be made available to SETI upon its completion, and discusses issues ‘core’ to any message construction. [Copyright &y& Elsevier]

Abstract: Despite the fact that major efforts have been expended on passive searches for extraterrestrial signals, few deliberate “transmissions” to potential alien recipients have occurred. These have generally taken the form of simple graphics depicting such things as our appearance, location, and biological construction. In this paper, we consider (a) the fundamental technical and astronomical limitations to interstellar messaging—in other words, how many “bits” could any society reasonably send, and (b) what might be a likely transmission strategy. These considerations suggest approaches for SETI programs, as well as giving insight into the types of messages we might construct for eventual replies to received signals. [Copyright &y& Elsevier]

Abstract: While most optical SETI experiments are configured to detect nanosecond pulses, the majority of their counterpart radio searches integrate for seconds to minutes, looking for unchanging narrow-band carriers or slowly pulsed modulation. The former approach is suggested as an effective way to stand out against stellar photon noise, while the latter approach is dictated by the dispersive effects of the interstellar medium as well as the high visibility of narrow-band signal components. In this paper, we consider effective signal strategies for those that produce, rather than simply search for, optical and radio beacons—signals that are designed to elicit responses from technological civilizations. By considering the communication problem from the point of view of the transmitters, rather than the receivers, we deduce some likely signal characteristics for beacons, and concommitant new strategies for SETI. [Copyright &y& Elsevier]

Gas transmission pipelines in the United States are primarily inspected using the magnetic flux leakage (MFL) nondestructive evaluation (NDE) technique. However, accurate analysis of the NDE signals in terms of the underlying defects requires a thorough knowledge of various operational parameters such as B-H characteristics of the pipe wall, the velocity of the scanning tool, etc. In certain situations, information about such operational parameters is either absent or hard to obtain. Appropriate signal processing techniques can be applied to the raw MFL signals to ensure that defect characterization is possible in spite of local variations in the test situation. This paper presents two such signal processing methods—one, to compensate the MFL signal for variations in pipe-material grade, and the other to remove the effects of signal distortion that occur due to the velocity of the scanning device. [ABSTRACT FROM AUTHOR]

The current state of infrastructure in the United States and worldwide has raised the need for reliable structural health monitoring techniques. Piezoelectric sensing, such as acoustic emission, has recently gained attention due to its high sensitivity and associated capability for early detection of damage. The high sensitivity of this method, however, results in the collection of data not directly related to damage growth. Current filtering procedures focus primarily on parametric analysis of the collected signals. This study focuses on developing more robust filtering techniques for acoustic emission data collected from a prestressed concrete specimen. Simulated data was generated to enable proper identification of the source of the collected signals. Filtering criteria were developed through characterization of the energy content using a wavelet transform. The developed filters were capable of separating the induced target signals from other signals with reasonable accuracy, and the results were verified through source location. The developed filters were validated using acoustic emission data collected during a load test. [ABSTRACT FROM AUTHOR]

Abstract: Background and Aims: In‐utero exposure to opioids including buprenorphine (BUP) has been shown to affect fetal activity, specifically heart‐rate variability (FHRV) and fetal movement (FM). Our objective was to extract simultaneous recordings of fetal cardiac and brain‐related activity in BUP‐maintained and non‐opioid exposed pregnant women using a novel non‐invasive biomagnetic technique. Design: A pilot study was conducted, recording and analyzing biomagnetic data from fetuses of BUP‐maintained and non‐opioid exposed pregnant women. Signals were acquired with the non‐invasive 151‐channel SARA (SQUID‐Array for Reproductive Assessment) system. Advanced signal‐processing techniques were applied to extract fetal heart and brain activity. Setting: University of Arkansas for Medical Sciences (UAMS, Little Rock, Arkansas, USA). Participants: Eight BUP‐maintained pregnant women from UAMS Women's Mental Health Program between gestational ages (GA) of 29–37 weeks who were treated with 8–24 mg of BUP daily. Sixteen pregnant women with no known opioid exposure in the same GA range were also included. Measurements: Outcome measures from the fetal heart and brain signals included: heart rate (FHR), FM, FHR accelerations, FHR–FM coupling, FHRV, fetal behavioral states (FBS) and power spectral density (PSD) of spontaneous brain activity. These measures were analyzed at three GA intervals. Findings: Fetal heart and brain activity parameters were extracted and quantified successfully from 18 non‐opioid and 16 BUP recordings. Overall analysis in both groups show that: FHR and FM ranged from 131 to 141 beats per minute (b.p.m.) and 5 to 11 counts, respectively. In the 35–37 weeks GA, the coupling duration (~9 s) was the shortest, while three of the FHRV parameters were the highest. The PSD of brain activity revealed highest power in 0.5‐4 Hz bandwidth. Transitions in FBS from quiet to active sleep were > 50% of sessions. Conclusions: This pilot study showed that a novel biomagnetic technique allows simultaneous quantification of cardiac and brain activities of a group of buprenorphine‐exposed and non‐exposed fetuses in the third trimester. [ABSTRACT FROM AUTHOR]

Objective: The primary goal of this study was to evaluate a new form of non-linear frequency compression (NLFC) in children. The new NLFC processing scheme is adaptive and potentially allows for a better preservation of the spectral characteristics of the input sounds when compared to conventional NLFC processing. Design: A repeated-measures design was utilised to compare the speech perception of the participants with two configurations of the new adaptive NLFC processing to their performance with the existing NLFC. The outcome measures included the University of Western Ontario Plurals test, the Consonant-Nucleus-Consonant word recognition test, and the Phonak Phoneme Perception test. Study sample: Study participants included 14 children, aged 6–17 years, with mild-to-severe low-frequency hearing loss and severe-to-profound high-frequency hearing loss. Results: The results indicated that the use of the new adaptive NLFC processing resulted in significantly better average word recognition and plural detection relative to the conventional NLFC processing. Conclusion: Overall, the adaptive NLFC processing evaluated in this study has the potential to significantly improve speech perception relative to conventional NLFC processing. [ABSTRACT FROM AUTHOR]

Background: U.S. natural gas production increased 40% from 2000 to 2015. This growth is largely related to technological advances in horizontal drilling and high-volume hydraulic fracturing. Environmental exposures upon impacted communities are a significant public health concern. Noise associated with natural gas compressor stations has been identified as a major concern for nearby residents, though limited studies exist. Objectives: We conducted a pilot study to characterize noise levels in 11 homes located in Doddridge County, West Virginia, and determined whether these levels differed based on time of day, indoors vs. outdoors, and proximity of homes to natural gas compressor stations. We also compared noise levels at increasing distances from compressor stations to available noise guidelines, and evaluated low frequency noise presence. Methods: We collected indoor and outdoor 24-hour measurements (Leq, 24hr) in eight homes located within 750 meters (m) of the nearest compressor station and three control homes located >1000m. We then evaluated how A-weighted decibel (dBA) exposure levels differed based on factors outlined above. Results: The geometric mean (GM) for 24-hour outdoor noise levels at homes located <300m (Leq,24hr: 60.3 dBA; geometric standard deviation (GSD): 1.0) from the nearest compressor station was nearly 9 dBA higher than control homes (Leq,24hr: 51.6 dBA; GSD: 1.1). GM for 24 hour indoor noise for homes <300m (Leq,24hr: 53.4 dBA; GSD: 1.2) from the nearest compressor station was 11.2 dBA higher than control homes (Leq,24hr: 42.2 dBA; GSD: 1.1). Indoor average daytime noise for homes <300m of the nearest compressor stations were 13.1 dBA higher than control homes, while indoor nighttime readings were 9.4 dBA higher. Conclusions: Findings indicate that living near a natural gas compressor station could potentially result in high environmental noise exposures. Larger studies are needed to confirm these findings and evaluate potential health impacts and protection measures. [ABSTRACT FROM AUTHOR]

Non-native bark and ambrosia beetles represent a threat to forests worldwide. Their invasion patterns are, however, still unclear. Here we investigated first, if the spread of non-native bark and ambrosia beetles is a gradual or a discontinuous process; second, which are the main correlates of their community structure; third, whether those correlates correspond to those of native species. We used data on species distribution of non-native and native scolytines in the continental 48 USA states. These data were analyzed through a beta-diversity index, partitioned into species richness differences and species replacement, using Mantel correlograms and non-metric multidimensional scaling (NMDS) ordination for identifying spatial patterns, and regression on distance matrices to test the association of climate (temperature, rainfall), forest (cover area, composition), geographical (distance), and human-related (import) variables with β-diversity components. For both non-native bark and ambrosia beetles, β-diversity was mainly composed of species richness difference than species replacement. For non-native bark beetles, a discontinuous invasion process composed of long distance jumps or multiple introduction events was apparent. Species richness differences were primarily correlated with differences in import values while temperature was the main correlate of species replacement. For non-native ambrosia beetles, a more continuous invasion process was apparent, with the pool of non-native species arriving in the coastal areas that tended to be filtered as they spread to interior portions of the continental USA. Species richness differences were mainly correlated with differences in rainfall among states, while rainfall and temperature were the main correlates of species replacement. Our study suggests that the different ecology of bark and ambrosia beetles influences their invasion process in new environments. The lower dependency that bark beetles have on climate allowed them to potentially colonize more areas within the USA, while non-native ambrosia beetles, being dependent on rainfall, are typically filtered by the environment. [ABSTRACT FROM AUTHOR]

Lung cancer remains the leading cause of cancer deaths in the US with >150,000 deaths per year. In order to more effectively reduce lung cancer mortality, more sophisticated screening paradigms are needed. Previously, our group demonstrated the use of low-coherence enhanced backscattering (LEBS) spectroscopy to detect and quantify the micro/nano-architectural correlates of colorectal and pancreatic field carcinogenesis. In the lung, the buccal (cheek) mucosa has been suggested as an excellent surrogate site in the “field of injury”. We, therefore, wanted to assess whether LEBS could similarly sense the presence of lung. To this end, we applied a fiber-optic LEBS probe to a dataset of 27 smokers without diagnosed lung cancer (controls) and 46 with lung cancer (cases), which was divided into a training and a blinded validation set (32 and 41 subjects, respectively). LEBS readings of the buccal mucosa were taken from the oral cavity applying gentle contact. The diagnostic LEBS marker was notably altered in patients harboring lung cancer compared to smoking controls. The prediction rule developed on training set data provided excellent diagnostics with 94% sensitivity, 80% specificity, and 95% accuracy. Applying the same threshold to the blinded validation set yielded 79% sensitivity and 83% specificity. These results were not confounded by patient demographics or impacted by cancer type or location. Moreover, the prediction rule was robust across all stages of cancer including stage I. We envision the use of LEBS as the first part of a two-step paradigm shift in lung cancer screening in which patients with high LEBS risk markers are funnelled into more invasive screening for confirmation. [ABSTRACT FROM AUTHOR]

ABSTRACT Secure distributed spectrum sensing (DSS) schemes in cognitive radio networks (CRNs) have been proposed to reliably detect the signals of the primary users (PUs) even when compromised nodes generate forged sensing reports. However, they have limited sensing accuracy for PU signals because of the absence of exact signal patterns of PUs. This is caused by Federal Communications Commission restriction on (no modification of) PUs, and thus, the CRNs cannot communicate with the PUs to obtain such patterns. We propose a verification framework utilizing primary user emulation signals that can be applied to existing DSS schemes to address this challenge. This will reinforce the robustness against forged sensing values. We then develop a concrete verification scheme based on this framework and an existing secure DSS scheme. We evaluate our approach via in-depth simulation and analysis compared with the existing scheme. Results show that our approach improves sensing accuracy and fusion speed in the cases of attack. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Each GPS IIIC space vehicle (SV) will broadcast a user range accuracy (URA) that bounds the errors in that SV's signal-in-space (SIS). An independent URA monitor (IUM) is examined as part of the next generation GPS Control Segment (OCX) to ensure URA bounding of errors in the SV ephemeris and clock corrections. Since the IUM operates on single snapshot data to maintain timely integrity, the minimum monitorable URAs (MMUs) are larger than if based on continuous tracking data and an orbital model. Operational feasibility of the IUM is assessed for the Localizer Performance with Vertical guidance (LPV) aircraft approach down to a 200 ft decision altitude (LPV200). Although the MMUs are larger than the URAs previously envisioned for GPS IIIC, availability for LPV200 would be sufficiently high at U.S. locations, including Alaska and Hawaii, but would be less than 0.99 at some non-U.S. locations analyzed, particularly in the Southern Hemisphere. Copyright © 2012 Institute of Navigation. [ABSTRACT FROM AUTHOR]

The Digital Beamforming Synthetic Aperture Radar (DBSAR) is a state-of-the-art L-band radar that employs advanced radar technology and a customized data acquisition and real-time processor in order to enable multimode measurement techniques in a single radar platform. DBSAR serves as a test bed for the development, implementation, and testing of digital beamforming radar techniques applicable to Earth science and planetary measurements. DBSAR flew its first field campaign on board the National Aeronautics and Space Administration P3 aircraft in October 2008, demonstrating enabling techniques for scatterometry, synthetic aperture, and altimetry. [ABSTRACT FROM AUTHOR]

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The article reports on the study conducted by Radu Stoleru of Texas A&M University and John A. Stankovic and Sang H. Son of the University of Virginia on node localization in wireless sensor networks and the potential of localization protocol composability in the U.S. There are several wireless sensor network (WSN) systems are developed for several domains including military surveillance, environmental monitoring, habitat monitoring and structural monitoring. When researchers studied how one can effectively locate sensor nodes at low cost, they failed because despite the myriads of schemes available in the market, no robust localization system has potential to provide the solution needed. Presented are the details of the research.

Transmit beampattern design is a critically important task in many fields including defense and homeland security as well as biomedical applications. Flexible transmit beampattern designs can be achieved by exploiting the waveform diversity offered by an array of sensors that transmit probing signals chosen at will. Unlike a standard phased-array, which transmits scaled versions of a single waveform, a waveform diversity-based system offers the flexibility of choosing how the different probing signals are correlated with one another. Recently proposed techniques for waveform diversity-based transmit beampattern design have focused on the optimization of the covariance matrix R of the waveforms, as optimizing a performance metric directly with respect to the waveform matrix is a more complicated operation. Given an R, obtained in a previous optimization stage or simply pre-specified, the problem becomes that of determining a signal waveform matrix X whose covariance matrix is equal or close to R, and which also satisfies some practically motivated constraints (such as constant-modulus or low peak-to-average-power ratio constraints). We propose a cyclic optimization algorithm for the synthesis of such an X, which (approximately) realizes a given optimal covariance matrix R under various practical constraints. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Objective: We examined the effects of knowledge of results (KR) on vigilance accuracy and report the first use of positive and negative predictive power (PPP and NPP) to assess vigilance training effectiveness.Background: Training individuals to detect infrequent signals among a plethora of nonsignals is critical to success in many failure-intolerant monitoring technologies. KR has been widely used for vigilance training, but the effect of the schedule of KR presentation on accuracy has been neglected. Previous research on training for vigilance has used signal detection metrics or hits and false alarms. In this study diagnosticity measures were applied to augment traditional analytic methods.Method: We examined the effects of continuous KR and a partial-KR regimen versus a no-KR control on decision diagnosticity.Results: Signal detection theory (SDT) analysis indicated that KR induced conservatism in responding but did not enhance sensitivity. However, KR in both forms equally enhanced PPP while selectively impairing NPP.Conclusion: There is a trade-off in the effectiveness of KR in reducing false alarms and misses. Together, SDT and PPP/NPP measures provide a more complete portrait of performance effects.Application: PPP and NPP together provide another assessment technique for vigilance performance, and as additional diagnostic tools, these measures are potentially useful to the human factors community. [ABSTRACT FROM AUTHOR]

We present a true random number generator which, contrary to other implementations, is not based on the explicit observation of complex micro-cosmic processes but on standard signal processing primitives, freeing the designer from the need for dedicated hardware. The system can be implemented from now ubiquitous analog-to-digital converters building blocks, and is therefore well-suited to embedding. On current technologies, the design permits data rates in the order of a few tens of megabits per second. Furthermore, the absence of predictable, repeatable behaviors increases the system security for cryptographic applications. The design relies on a simple inner model based on chaotic dynamics which, in ideal conditions, can be formally proven to generate perfectly uncorrelated binary sequences. Here, we detail the design and we validate the quality of its output against a couple of test suites standardized by the U.S. National Institute of Standards and Technology, both in the ideal ease and assuming implementation errors. [ABSTRACT FROM AUTHOR]

Changes over the years in tornado-warning performance in the United States can be modeled from the perspective of signal detection theory. From this view, it can be seen that there have been distinct periods of change in performance, most likely associated with deployment of radars, and changes in scientific understanding and training. The model also makes it clear that improvements in the false alarm ratio can only occur at the cost of large decreases in the probability of detection, or with large improvements in the overall quality of the warning system. [ABSTRACT FROM AUTHOR]

The state of the art in verifying the real-time requirements of applications developed using general processing graph models relies on simulation or off-line scheduling. We extend the state of the art by presenting analytical methods that support the analysis of cyclic processing graphs executed with on-line schedulers. We show that it is possible to compute the latency inherent in a processing graph independent of the hardware hosting the application. We also show how to compute the real-time execution rate of each node in the graph. Using the execution rate of each node and the time it takes per execution on a given processor, the resulting CPU utilization can be computed, as shown here for the Directed Low Frequency Analysis and Recording (DIFAR) acoustic signal processing application from the Airborne Low Frequency Sonar (ALFS) system of the SH-60B LAMPS MK III anti-submarine helicopter. [ABSTRACT FROM AUTHOR]

Compares the performance of two signal processing technologies, F0F1F2 and F0F1F2B3B4B5, on individuals using the Mini Speech Processor, a cochlear implant introduced in the United States in 1989. Evaluation of the two technologies using speech recognition tests and subjective ratings; Advantages of having subjects experience both technologies.

We propose a new theory of predation based on ‘signal-jamming.’ In our model the predator's characteristics are common knowledge, while the entrant is uncertain of his own future profitability. The entrant uses his current profit to decide whether to remain in the market, and the predator preys to ‘jam’ or interfere with this inference problem. Thus, our model differs from those based on ‘reputation effects,’ in which the predator preys to signal information about himself. [ABSTRACT FROM AUTHOR]

The article provides information concerning the exposure of human beings on many different sounds from multiple sources at the same time in the U.S. The author implies that the noisy signals interact and compete with each other when they are being processed by the brain, a process called simultaneous masking.

The convergent ablator experiments at the National Ignition Facility (NIF) are designed to measure the peak velocity and remaining ablator mass of an indirectly driven imploding capsule. Such a measurement can be performed using an x-ray source to backlight the capsule and an x-ray streak camera to record the capsule as it implodes. The ultimate goal of this experiment is to achieve an accuracy of 2% in the velocity measurement, which translates to a ±2 ps temporal accuracy over any 300 ps interval for the streak camera. In order to achieve this, a 4ω (263 nm) temporal fiducial system has been implemented for the x-ray streak camera at NIF. Aluminum, titanium, gold, and silver photocathode materials have been tested. Aluminum showed the highest relative quantum efficiency, with five times more peak signal counts per fiducial pulse when compared to Gold. The fiducial pulse data were analyzed to determine the centroiding statistical accuracy for incident laser pulse energies of 1 and 10 nJ, showing an accuracy of ±1.6 ps and ±0.7 ps, respectively. [ABSTRACT FROM AUTHOR]