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In this paper, we consider the development of algorithms for the automatic detection of buried threats using ground penetrating radar (GPR) measurements. GPR is one of the most studied and successful modalities for automatic buried threat detection (BTD), and a large variety of BTD algorithms have been proposed for it. Despite this, large-scale comparisons of GPR-based BTD algorithms are rare in the literature. In this paper, we report the results of a multi-institutional effort to develop advanced BTD algorithms for a real-world GPR BTD system. The effort involved five institutions with substantial experience with the development of GPR-based BTD algorithms. In this paper, we report the technical details of the advanced algorithms submitted by each institution, representing their latest technical advances, and many state-of-the-art GPR-based BTD algorithms. We also report the results of evaluating the algorithms from each institution on the large experimental data set used for development. The experimental data set comprised 120 000 m2 of GPR data using surface area, from 13 different lanes across two U.S. test sites. The data were collected using a vehicle-mounted GPR system, the variants of which have supplied data for numerous publications. Using these results, we identify the most successful and common processing strategies among the submitted algorithms, and make recommendations for GPR-based BTD algorithm design. [ABSTRACT FROM AUTHOR]

This paper describes the application of a novel multiobjective self-adaptive differential evolution (MOSADE) algorithm for the simultaneous optimization of component sizing and control strategy in parallel hybrid electric vehicles (HEVs). Based on an electric assist control strategy, the HEV optimal design problem is formulated as a nonlinear constrained multiobjective problem with competing and noncommensurable objectives of fuel consumption and emissions. The driving performance requirements are considered constraints. The proposed MOSADE approach adopts an external elitist archive to retain nondominated solutions that are found during the evolutionary process. To preserve the diversity of Pareto optimal solutions, a progressive comparison truncation operator based on the normalized nearest neighbor distance is proposed. Moreover, a fuzzy set theory is employed to extract the best compromise solution. Finally, the optimization is performed over the following three typical driving cycles that are currently used in the U.S. and European communities: 1) the file transfer protocol; 2) ECE +EUDC; and 3) Urban Dynamometer Driving Schedule. The results demonstrate the capability of the proposed approach to generate well-distributed Pareto optimal solutions of the HEV multiobjective optimization design problem. The comparison with the reported results of genetic-algorithm-based weighting sum approaches and Nondominated Sorting Genetic Algorithm II reveals the superiority of the proposed approach and confirms its potential for optimal HEV design. [ABSTRACT FROM PUBLISHER]

Current spatial database systems offer limited querying capabilities beyond binary topological relations. This paper introduces a model for projective relations between regions to support other qualitative spatial queries. The relations are ternary because they are based on the collinearity invariant of three points under projective geometry. The model is built on a partition of the plane into separate zones that are obtained from projective properties of two reference objects: Then, by considering the empty/nonempty intersections of a primary object with these zones, the model is able to distinguish between 34 different projective relations. Then, the paper proposes original algorithms for computing the relations under the assumption that regions of the plane are stored as vector polygons in a spatial database. These algorithms run in optimal O(n log n) time. [ABSTRACT FROM AUTHOR]

Reverse link capacity of a direct-sequence code-division multiple-access (DS-CDMA) system in a multicell environment has been studied recently, and significant capacity improvements due to the use of beamforming have been observed. However, system performance with beamforming will be affected by several impairments, such as direction of arrival estimation errors, array perturbations, mutual coupling, and signal spatial spreads. In this paper, reverse link performance of CDMA systems with beamforming under these impairments (imperfect beamforming) is investigated. A simplified beamforming model is developed to evaluate the system performance in terms of user capacity, bit-error rates (BER), and outage probabilities. Both signal-to-interference-ratio-based power control and strength-based power control are considered in this paper. The capacity and BER degradations due to different impairments are shown, and outage probabilities under different power control schemes are examined. [ABSTRACT FROM AUTHOR]

A new algorithm of matrix spectral factorization is proposed which can be applied to compute an approximate spectral factor of any positive definite matrix function which satisfies the Paley-Wiener condition. ref refid="fnote1"/ id="fnote1" asterisk="no"paraThis paper includes the detailed proofs for an innovative method for matrix spectral factorization that can be used in numerous applications, including filtering, data compression, and wireless communications. A U.S. patent application has been submitted for this innovation through the Technology Commercialization Center, University of Maryland.para [ABSTRACT FROM AUTHOR]

Ice concentration retrieved from spaceborne passive-microwave observations is a prime input to operational sea-ice-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)-York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate ice concentration from Special Sensor Microwave/Imager observations. This paper furnishes a comparison between ice concentrations (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian Ice Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total ice concentration by 18.35% and 9.66% concentration counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved concentrations of thin and thick ice are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total ice concentration approaches 100 %. If thin and thick ice types coexist in comparable concentrations, the algorithms' estimates agree with CIS's estimates. In terms of ice concentration retrieval, thin ice is more problematic than thick ice. The concept of using a single tie point to represent a thin ice surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total ice concentration in slightly more agreement with CIS's estimates, NT2 provides better agreement in retrieving thin and thick ice concentrations. [ABSTRACT FROM AUTHOR]

Incorporating constraints into frequent itemset mining not only improves data mining efficiency, but also leads to concise and meaningful results. In this paper, a framework for closed constrained gradient itemset mining in retail databases is proposed by introducing the concept of gradient constraint into closed itemset mining. A tailored version of CLOSET+, LCLOSET, is first briefly introduced, which is designed for efficient closed itemset mining from sparse databases. Then, a newly proposed weaker but antimonotone measure, top-X average measure, is proposed and can be adopted to prune search space effectively. Experiments show that a combination of LCLOSET and the top-X average pruning provides an efficient approach to mining frequent closed gradient itemsets. [ABSTRACT FROM AUTHOR]

Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each source node must send all its locally generated data to only one of the BSs. To maximize network lifetime, it is essential to optimally match each source node to a particular BS and find an optimal routing solution. A polynomial time heuristic is proposed for optimal BS selection and anycast via a sequential fixing procedure. Through extensive simulation results, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution. [ABSTRACT FROM AUTHOR]

Privacy is becoming a major issue in ad hoc networks. In this paper, using pseudonimity for achieving communication anonymity in networks that apply geographic-routing algorithms is explored. An Anonymous Receiver-Contention POsitioning (ARCPO) routing algorithm is proposed. Node identities (IDs) are kept anonymous. Pseudonyms, i.e., the positions of destinations, are used for data-packet delivery. The anonymity for a destination relies on the difficulty of matching its position to its ID by any observer. Position servers that provide node position information act as trusted third parties and handle identity management. Node mobility makes the use of the pseudonym momentary, and therefore can further improve privacy. The anonymity for the source and intermediate nodes in the path is also achieved because they are not required to reveal any identity information. A receiver-contention mechanism is proposed so that a next hop can be generated without local position information exchange, which otherwise may lead to severe privacy degradation. Analysis and simulation show that while ARCPO guarantees anonymous communication in ad hoc networks, its routing performance degrades moderately compared with other position routing algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to improve turbo code performance on the space time transmit diversity (STTD) code-division multiple-access (CDMA) forward link through better estimation of the channel state information (CSI) required by the mobile turbo decoder. An improved CSI estimation scheme that accounts for the unique nature of CDMA STTD intracell interference is presented. It is compared to a standard CSI estimation scheme that assumes all STTD interference and noise can be represented as additive white Gaussian noise at the mobile receiver input. An STTD CDMA forward link simulation shows that link performance is significantly improved when the mobile turbo decoder uses the more accurate CSI provided by improved estimation. However, the degree of improvement depends on the turbo decoding algorithm, mobile velocity, and whether the base station is using STTD or single-antenna transmission. [ABSTRACT FROM AUTHOR]

Energy-efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts toward it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, this paper proposes a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, a fully distributed localized routing algorithm is further presented, which is proved to converge at the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate the proposed solution. [ABSTRACT FROM AUTHOR]

A new multicarrier system, termed multisymbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM), is proposed, in which one cyclic prefix (CP) is used for multiple OFDM symbols. The original motivation for the MSE-OFDM proposal is to reduce the redundancy due to the CP in static-channel environments. The authors then found that an alternative implementation of the system can be used to improve the robustness to frequency offset and reduce the peak-to-average power ratio (PAPR). Equalization and demodulation algorithms for the MSE-OFDM system are proposed. A new preamble and the corresponding frequency-offset and channel estimation techniques are studied for the MSE-OFDM system. Using the proposed MSE-OFDM preamble, the joint maximum likelihood (ML) estimation of the frequency offset and the channel impulse response (CIR) is investigated in this paper. Possible ways to reduce the joint estimation complexity, including exploitation of the preamble structure, approximation of the joint ML estimator, and fast Fourier transform (FFT) pruning, are discussed. The performance of the proposed MSE-OFDM systems and channel estimators are analyzed and verified through numerical simulations. An analysis on the bandwidth efficiency, the performance with frequency offset, and the PAPR of the MSE-OFDM system are also presented. [ABSTRACT FROM AUTHOR]

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called ‘aggregators.’ Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments. [ABSTRACT FROM AUTHOR]

Joint scheduling and power control schemes have previously been proposed to reduce power dissipation in wireless ad hoc networks. However, instead of power consumption, throughput is a more important performance concern for some emerging multihop wireless networks, such as wireless mesh networks. This paper examines joint link scheduling and power control with the objective of throughput improvement. The MAximum THroughput link Scheduling with Power Control (MATH-SPC) problem is first formulated and then a mixed integer linear programming (MILP) formulation is presented to provide optimal solutions. However, simply maximizing the throughput may lead to a severe bias on bandwidth allocation among links. To achieve a good tradeoff between throughput and fairness, a new parameter called the demand satisfaction factor (DSF) to characterize the fairness of bandwidth allocation and formulate the MAximum Throughput fAir link Scheduling with Power Control (MATA-SPC) problem is defined. An MILP formulation and an effective polynomial-time heuristic algorithm, namely, the serial linear programming rounding (SLPR) heuristic, to solve the MATA-SPC problem are also presented. Numerical results show that bandwidth can be fairly allocated among all links/flows by solving the MILP formulation or by using the heuristic algorithm at the cost of a minor reduction of network throughput. In addition, extensions to end-to-end throughput and fairness and multiradio wireless multihop networks are discussed. [ABSTRACT FROM AUTHOR]

We introduce new methods for increasing the performance of multiprogram digital audio broadcast systems, e.g., satellite digital audio broadcasting. Joint multiprogram encoding is an attractive possibility for parallel broadcasting of a large number of programs. Joint coding extended over multiple audio frames in time give further improvements. The benefits of this kind of statistical multiplexing yield improved audio quality and/or higher capacity in terms of number of programs. We describe the new Joint Multiple Program Encoding Technique in the context of the perceptual audio coding (PAC) type of algorithms. We also describe methods for multi-program transmission including Equal Error Protection (EEP) as well as Unequal Error Protection (UEP) and improved error concealment for multiple program transmission. Some of the techniques described in this paper, are currently being used in satellite digital audio broadcasting in the United States. [ABSTRACT FROM AUTHOR]

Validation is an important and particularly challenging task for remote sensing of soil moisture. A key issue in the validation of soil moisture products is the disparity in spatial scales between satellite and in situ observations. Conventional measurements of soil moisture are made at a point, whereas satellite sensors provide an integrated area/volume value for a much larger spatial extent. In this paper, four soil moisture networks were developed and used as part of the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) validation program. Each network is located in a different climatic region of the U.S., and provides estimates of the average soil moisture over highly instrumented experimental watersheds and surrounding areas that approximate the size of the AMSR-E footprint. Soil moisture measurements have been made at these validation sites on a continuous basis since 2002, which provided a seven-year period of record for this analysis. The National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) standard soil moisture products were compared to the network observations, along with two alternative soil moisture products developed using the single-channel algorithm (SCA) and the land parameter retrieval model (LPRM). The metric used for validation is the root-mean-square error (rmse) of the soil moisture estimate as compared to the in situ data. The mission requirement for accuracy defined by the space agencies is 0.06 \m^3/\m^3. The statistical results indicate that each algorithm performs differently at each site. Neither the NASA nor the JAXA standard products provide reliable estimates for all the conditions represented by the four watershed sites. The JAXA algorithm performs better than the NASA algorithm under light-vegetation conditions, but the NASA algorithm is more reliable for moderate vegetation. However, both algorithms have a moderate to large bias in all cases. The SCA had the lowest overall rmse with a small bias. The LPRM had a very large overestimation bias and retrieval errors. When site-specific corrections were applied, all algorithms had approximately the same error level and correlation. These results clearly show that there is much room for improvement in the algorithms currently in use by JAXA and NASA. They also illustrate the potential pitfalls in using the products without a careful evaluation. [ABSTRACT FROM AUTHOR]

The US National High Magnetic Field Laboratory constructed and tested a stand-alone 80 T prototype magnet. The activity was in support of the insert magnet development project for the US-DOE-NSF 100 Tesla Multi-Pulse Magnet Program. The 80 T magnet assembly was developed to simulate the physical conditions an insert magnet would encounter during peak field operations at 105 T… The design incorporated further improvements to the engineering template developed from the 65 T and 75 T pulsed magnets now in use at the NHMFL Pulsed Field Facility at Los Alamos National Laboratory. Two coaxially nested solenoid coils comprised the 80 T prototype magnet design. The windings are in series electrically. The inner coil is constructed with materials & techniques identical to those in use for the 100 T insert program. The outer coil is a conventional winding. The prototype was successfully trained to a peak field of ~80.4 T. 80 T pulsed operations were repeated until the coil assembly faulted after 10 full-field pulses. Post-fault inspection of the magnet assembly indicated that the outer magnet winding failed structurally. This paper will present an overview of the 80 T prototype's design, construction, and performance. A review of the magnets failure mode will be presented. Additionally, we will discuss new design criteria for stand alone high-field pulsed magnet based upon the 80 T prototype experience. [ABSTRACT FROM AUTHOR]

Relational databases are the most popular repository for structured data, and is thus one of the richest sources of knowledge in the world. In a relational database, multiple relations are linked together via entity-relationship links. Multirelational classification is the procedure of building a classifier based on information stored in multiple relations and making predictions with it. Existing approaches of Inductive Logic Programming (recently, also known as Relational Mining) have proven effective with high accuracy in multirelational classification. Unfortunately, most of them suffer from scalability problems with regard to the number of relations in databases. In this paper, we propose a new approach, called CrossMine, which includes a set of novel and powerful methods for multirelational classification, including 1) tuple ID propagation, an efficient and flexible method for virtually joining relations, which enables convenient search among different relations, 2) new definitions for predicates and decision-tree nodes, which involve aggregated information to provide essential statistics for classification, and 3) a selective sampling method for improving scalability with regard to the number of tuples. Based on these techniques, we propose two scalable and accurate methods for multirelational classification: CrossMine-Rule, a rule-based method and CrossMine-Tree, a decision-tree-based method. Our comprehensive experiments on both real and synthetic data sets demonstrate the high scalability and accuracy of the CrossMine approach. [ABSTRACT FROM AUTHOR]

Support Vector Machines (SVMs) have been adopted by many data mining and information-retrieval applications for learning a mining or query concept, and then retrieving the ‘top-k’ best matches to the concept. However, when the data set is large, naively scanning the entire data set to find the top matches is not scalable. In this work, we propose a kernel indexing strategy to substantially prune the search space and, thus, improve the performance of top-k queries. Our kernel indexer (KDX) takes advantage of the underlying geometric properties and quickly converges on an approximate set of top-k instances of interest. More importantly, once the kernel (e.g., Gaussian kernel) has been selected and the indexer has been constructed, the indexer can work with different kernel-parameter settings (e.g., γ and σ) without performance compromise. Through theoretical analysis and empirical studies on a wide variety of data sets, we demonstrate KDX to be very effective. An earlier version of this paper appeared in the 2005 SIAM International Conference on Data Mining [24]. This version differs from the previous submission in providing a detailed cost analysis under different scenarios, specifically designed to meet the varying needs of accuracy, speed, and space requirements, developing an approach for insertion and deletion of instances, presenting the specific computations as well as the geometric properties used in performing the same, and providing detailed algorithms for each of the operations necessary to create and use the index structure. [ABSTRACT FROM AUTHOR]

In this paper, the authors study the performance of scheduling algorithms exploiting the multiuser selection diversity. Schedulers with affordable-rate transmission and adaptive transmission based on the absolute signal-to-noise ratio (SNR) and the normalized SNR are considered. In contrast to previous studies on the multiuser-diversity systems, the channel dynamics is taken into consideration in this paper by a novel formulation based on the level crossing analysis of stochastic processes. Then, the authors make the connection between the Doppler frequency shift, which indicates the channel temporal correlation, and the average (channel) access time, the average waiting time (AWT) between accesses, and the average access rate (AAR) of active users. These properties are important for the scheduler design, especially for applications where delay is a concern. In addition, analytical expressions for the system throughput and the degree of fairness (DOF) when users have nonidentical average channel conditions are presented. These expressions quantify the effect of disparateness in users' average channel conditions on the system performance. [ABSTRACT FROM AUTHOR]

This paper examines the problem of quality-of-service group communications in a heterogeneous network, which consists of multiple mobile ad hoc networks attached to the backbone Internet. A heuristic multicast algorithm named delay and delay variation multicast algorithm (DDVMA) is proposed. DDVMA is designed for solving the delay- and delay-variation-bounded multicast tree problem, which has been proved to be NP-complete. It can find a multicast tree satisfying the multicast end-to-end delay constraint and minimizing the multicast delay variation. Two concepts, which can help the DDVMA achieve better performance in terms of multicast delay variation than the delay and delay variation constraint algorithm that is known to be the most efficient so far, are proposed, namely, 1) the proprietary second shortest path and 2) the partially proprietary second shortest path. An analysis is given to show the correctness of DDVMA, and simulations are conducted to demonstrate the performance improvement of DDVMA in terms of multicast delay variation. It is also shown that the strategy employed by DDVMA is also applicable to handling the mobility of mobile hosts in a heterogeneous network. [ABSTRACT FROM AUTHOR]

The Tropospheric Emission Spectrometer (TES) is one of four instruments onboard the Earth Observing System Aura satellite. The TES Science Investigator-led Processing System (SIPS) Facility performs production processing of all TES science data. When the TES project was proposed in 1988, its science algorithms were still evolving, but it was already understood to be at least two orders of magnitude more complex than its NASA predecessor, the Atmospheric Trace Molecule Spectroscopy (ATMOS) instrument. In addition, the expected data volume of the TES instrument would be more than 1000 times greater than that of ATMOS. Development of the TES SIPS faced a number of technical challenges. It also would have been impractical and prohibitively costly to develop the TES SIPS facility without carefully deploying the computing technologies that have recently become available. This paper describes how the challenges were met in the development of the facility by making use of evolving hardware technology and software refinement. The process revealed that the architecture of the hardware implemented was highly dependent upon the processing algorithm, and a stable algorithm was needed early in the hardware development process for performance analysis and benchmarking. [ABSTRACT FROM AUTHOR]

The Earth Observing System (EOS) Microwave Limb Sounder (MLS) is an atmospheric remote sensing experiment led by the Jet Propulsion Laboratory of the California Institute of Technology. The objectives of the EOS MLS are to learn more about stratospheric chemistry and causes of ozone changes, processes affecting climate variability, and pollution in the upper troposphere. The EOS MLS is one of four instruments on the National Aeronautics and Space Administration (NASA) EOS Aura spacecraft launched on July 15, 2004, with an operational period extending at least 5 years after launch. This paper describes the architecture and capabilities of the Science Data Processing System (SDPS) for the EOS MLS. The SDPS consists of two major component—the Science Computing Facility and the Science Investigator-led Processing System. The Science Computing Facility provides the facilities for the EOS MLS Science Team to perform the functions of scientific algorithm development, processing software development, quality control of data products, and scientific analyses. The Science Investigator-led Processing System processes and reprocesses the science data for the entire mission and delivers the data products to the Science Computing Facility and to the Goddard Space Flight Center Earth Science Distributed Active Archive Center, which archives and distributes the standard science products. The Science Investigator-led Processing System is developed and operated by Raytheon Information Technology and Scientific Services of Pasadena under contract with Jet Propulsion Laboratory. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Instrument (OMI) on EOS/Aura offers unprecedented spatial and spectral resolution, coupled with global coverage, for space-based UV measurements of sulfur dioxide (SO2). This paper describes an OMI SO2 algorithm (the band residual difference) that uses calibrated residuals at SO2 absorption band centers produced by the NASA operational ozone algorithm (OMTO3). By using optimum wavelengths for retrieval of SO2, the retrieval sensitivity is improved over NASA predecessor Total Ozone Mapping Spectrometer (TOMS) by factors of 10 to 20, depending on location. The ground footprint of OMI is eight times smaller than TOMS. These factors produce two orders of magnitude improvement in the minimum detectable mass of SO2. Thus, the diffuse boundaries of volcanic clouds can be imaged better and the clouds can be tracked longer. More significantly, the improved sensitivity now permits daily global measurement of passive volcanic degassing of SO2 and of heavy anthropogenic SO2 pollution to provide new information on the relative importance of these sources for climate studies. [ABSTRACT FROM AUTHOR]

Epilepsy is the most prevalent neurological disorder affecting both adults and children. Over two-and-one-half million individuals in the United States have epilepsy and 25% of them do not respond to drugs. A significant focus of current research efforts is the development of a fully implantable device for real-time seizure detection and automated warning and blockage of seizures. The purpose of this paper is to describe and demonstrate the feasibility of incorporating a novel tool, the percentile tracking filter into a successful, validated seizure detection algorithm to create an analog seizure detection device. We demonstrate, in a small-scale study, that the performance of this analog implementation is statistically similar to a digital implementation of a previously described and successfully validated seizure digital algorithm. This analog implementation can be realized into an application specific integrated circuit that is suitable for a fully implantable device for seizure monitoring, warning and treatment, which is likely to consume very little power, a feature of practical value. [ABSTRACT FROM AUTHOR]

Scheduling plays an important role in providing quality of service (QoS) support to multimedia communications in various kinds of wireless networks, including cellular networks, mobile ad hoc networks, and wireless sensor networks. The authors propose a scheduling algorithm at the medium access control (MAC) layer for multiple connections with diverse QoS requirements, where each connection employs adaptive modulation and coding (AMC) scheme at the physical (PHY) layer over wireless fading channels. Each connection is assigned a priority, which is updated dynamically based on its channel and service status; the connection with the highest priority is scheduled each time. The authors' scheduler provides diverse QoS guarantees, uses the wireless bandwidth efficiently, and enjoys flexibility, scalability, and low implementation complexity. Its performance is evaluated via simulations. [ABSTRACT FROM AUTHOR]

This paper describes methods for automatically analyzing formal, state-based requirements specifications for some aspects of completeness and consistency. The approach uses a low-level functional formalism, simplifying the analysis process. State-space explosion problems are eliminated by applying the analysis at a high level of abstraction; i.e., instead of generating a reachability graph for analysis, the analysis is performed directly on the model. The method scales up to large systems by decomposing the specification into smaller, analyzable parts and then using functional composition rules to ensure that verified properties hold for the entire specification. The analysis algorithms and tools have been validated on TCAS II, a complex, airborne, collision-avoidance system required on all commercial aircraft with more than 30 passengers that fly in U.S. airspace. [ABSTRACT FROM AUTHOR]

We infer peak currents from radiation electric field peaks of 48 positive return strokes acquired in Gainesville, FL, USA, from 2007 to 2008. In doing so, we use the transmission line model, National Lightning Detection Network (NLDN) -reported distances, and assumed return-stroke speed. From a similar analysis of negative subsequent strokes, it appears that the implied return-stroke speed in the NLDN field-to-current conversion equation is 1.8 × 10^8 m/s (the NLDN peak current estimation algorithm is calibrated for negative subsequent strokes). The NLDN uses the same field-to-current conversion procedure (and hence the same implied return-stroke speed) for positive return strokes. However, NLDN-reported peak currents for positive return strokes differ from peak currents predicted by the transmission line model with an assumed return-stroke speed of 1.8 × 10^8 m/s. The discrepancy between regression equations for negative and positive return strokes suggests that the NLDN procedure to compensate for field propagation effects and find the average range-normalized signal strength (RNSS) works differently for these two groups of strokes. We find that the difference can be explained by the bias toward NLDN sensor reports from larger distances for positive strokes combined with the higher relative sensor gain (the ratio of sensor's peak current estimate to the NLDN-reported peak current) at larger distances. [ABSTRACT FROM PUBLISHER]

We introduce a labeled point set registration algorithm based on a family of novel information-theoretic measures derived as a generalization of the well-known Shannon entropy. This generalization, known as the Havrda–Charvat–Tsallis entropy, permits a fine-tuning between solution types of varying degrees of robustness of the divergence measure between multiple point sets. A variant of the traditional free-form deformation approach, known as directly manipulated free-form deformation, is used to model the transformation of the registration solution. We provide an overview of its open source implementation based on the Insight Toolkit of the National Institutes of Health. Characterization of the proposed framework includes comparison with other state of the art kernel-based methods and demonstration of its utility for lung registration via labeled point set representation of lung anatomy. [ABSTRACT FROM AUTHOR]

A variant of the popular nonparametric nonuniform intensity normalization (N3) algorithm is proposed for bias field correction. Given the superb performance of N3 and its public availability, it has been the subject of several evaluation studies. These studies have demonstrated the importance of certain parameters associated with the B-spline least-squares fitting. We propose the substitution of a recently developed fast and robust B-spline approximation routine and a modified hierarchical optimization scheme for improved bias field correction over the original N3 algorithm. Similar to the N3 algorithm, we also make the source code, testing, and technical documentation of our contribution, which we denote as "N4ITK," available to the public through the Insight Toolkit of the National Institutes of Health. Performance assessment is demonstrated using simulated data from the publicly available Brainweb database, hyperpolarized ³He lung image data, and 9.4T postmortem hippocampus data. [ABSTRACT FROM AUTHOR]

An automatic left ventricle (LV) segmentation algorithm is presented for quantification of cardiac output and myocardial mass in clinical practice. The LV endocardium is first segmented using region growth with iterative thresholding by detecting the effusion into the surrounding myocardium and tissues. Then the epicardium is extracted using the active contour model guided by the endocardial border and the myocardial signal information estimated by iterative thresholding. This iterative thresholding and active contour model with adaptation (ITHACA) algorithm was compared to manual tracing used in clinical practice and the commercial MASS Analysis software (General Electric) in 38 patients, with Institutional Review Board (IRB) approval. The ITHACA algorithm provided substantial improvement over the MASS software in defining myocardial borders. The ITHACA algorithm agreed well with manual tracing with a mean difference of blood volume and myocardial mass being 2.9 ± 6.2 mL (mean ± standard deviation) and -0.9 ± 16.5 g, respectively. The difference was smaller than the difference between manual tracing and the MASS software (approximately -20.0 ± 6.9 mL and -1.0 ± 20.2 g, respectively). These experimental results support that the proposed ITHACA segmentation is accurate and useful for clinical practice. [ABSTRACT FROM AUTHOR]

Satellite-derived aerosol data sets, such as those provided by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, are greatly improving our understanding of global aerosol optical depth (AOD). Yet, there are sampling issues. MODIS' specific orbital geometry, convolved with the need to avoid bright surfaces (glint, desert, clouds, etc.), means that AOD can be under- or over-sampled in places. When deriving downstream products, such as daily or monthly gridded AOD, one must consider the spatial and temporal density of the measurements relative to the gradients of the true AOD. Additionally, retrieval confidence criteria should be considered. Averaged products are highly dependent on choices made for data aggregation and weighting, and sampling errors can be further propagated when deriving regional or global "mean" AOD. Different choices for aggregation and weighting result in estimates of regional and global means varying by 30% or more. The impacts of a particular averaging algorithm vary by region and surface type and can be shown to represent different tolerance for clouds and retrieval confidence. [ABSTRACT FROM AUTHOR]

On April 10, 2006, Major General Bostick, the Commanding General of the United States Army Recruiting Command (USAREC), in conjunction with the Assistant Secretary of the Army for Manpower and Reserve Affairs, approved a new method of selecting individuals from within the Army for recruiting duty. Implementation currently waits for similar and current research concerning drill sergeants. Previously, the Army assigned successful noncommissioned officers (NCOs), regardless of inherent sales and marketing skills, into the recruiting force. The Army learned skills that make a successful combat leader do not always translate well into recruiting duty. This research began in 2001, after recruiting shortages, when the Army began researching recruiter selection methods. The result is an application that combines statistical learning with industrial and organizational (IO) psychology. The resulting selection model determines the better NCOs for service as detailed recruiters in the United States Army Recruiting Command, a 6000 plus sales force located worldwide. The application enhances IO psychology by providing a statistical prediction of job performance derived from psychological inventories and biographical data. The application uses a combination of statistical learning, variable selection methods, and IO psychology to determine the better prediction function approximation with variables obtained from the noncommissioned officer leadership skills inventory (NLSI) and biographical data. The application also creates a methodology for iteratively developing a statistical learning model. We learned that random forest models outperformed support vector regressions and stepwise regression for these data. A greedy algorithm enhanced model generalization by selecting a good subset of prediction variables. The model represents a multimodal relationship primarily between recruiter age, NLSI score, and, to a lesser degree, 34 other variables. The resulting model runs in R s- - tatistical language and is controlled within an Excel worksheet environment by using Visual Basic Application language and RExcel. The end product enables general utilization of a statistically elegant model, normally reserved for advanced researchers, engineers, statisticians, and economists. [ABSTRACT FROM PUBLISHER]

The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy COs flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)/fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28 %, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%–30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production. [ABSTRACT FROM AUTHOR]

An adaptive carrier interferometry (CI) scheme is proposed for multicarrier code-division multiple-access (MC-CDMA) systems where it is assumed that there is a feedback channel between the receiver and the transmitter. By exploiting the additional degree of freedom in selecting the amplitudes of the subcarriers in accordance with the channel condition, the proposed scheme attains a significant performance gain over the conventional CI-MC-CDMA systems in which a constant amplitude is set for all the carriers. Two adaptation strategies, namely 1) local adaptation and 2) global adaptation, are considered for estimating the appropriate subcarrier amplitudes at the receiver in the proposed systems. Both single-user adaptation, where the other users do not adapt, and multiuser adaptation, in which all users adapt, are investigated. A further advantage of the proposed scheme is that it eliminates the peak-to-average power ratio problem present in the conventional CI-MC-CDMA systems. [ABSTRACT FROM AUTHOR]

One of the primary design requirements of automotive generation systems is maximizing power density subject to the constraint of minimizing the overall system cost. However, with the progress made in the reduction of automotive drive train noise, the torque ripple of the generator has been found to be a dominant noise source under idle conditions at high electrical loads. Thus, an added design constraint is the minimization of the torque ripple produced by the machine. In order to evaluate alternative machine designs (and select an optimal), numerical tools are typically applied. In this research, a focus is placed on the creation of numerical tools that can be used to effectively search for an optimal design. A primary tool is an evolutionary algorithm (EA) that has been integrated within a customized magnetic equivalent circuit (MEC) model of the machine. The selection of an EA that is most likely to converge to an optimal solution in the least amount of time is described along with its use in selecting an optimal rotor-pole geometry. [ABSTRACT FROM AUTHOR]

We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Instrument (OMI) onboard the NASA Earth Observing System (EOS) Aura spacecraft is a nadir-viewing spectrometer that measures solar reflected and backscattered light in a selected range of the ultraviolet and visible spectrum. The instrument has a 2600-km-wide viewing swath, and it is capable of daily, global contiguous mapping. We developed and implemented a surface ultraviolet (UV) irradiance algorithm for OMI that produces noontime surface spectral UV irradiance estimates at four wavelengths (305, 310, 324, and 380 nm). Additionally, noontime erythemal dose rate and the erythemal daily dose are estimated. The OMI surface UV algorithm inherits from the surface UV algorithm developed by NASA Goddard Space Flight Center for the Total Ozone Mapping Spectrometer (TOMS). The OMI surface UV irradiance products are produced and archived in HDF5-EOS format by Finnish Meteorological Institute. The accuracy of the surface UV estimates depend on UV wavelength and atmospheric and other geolocation specific conditions ranging from 7%to 30%. A postprocessing aerosol correction can be applied at sites with additional ground-based measurements of the aerosol absorption optical thickness. The current OMI surface UV product validation plan is presented. [ABSTRACT FROM AUTHOR]

The retrieval algorithms for the Earth Observing System Microwave Limb Sounder (MLS) on the Aura spacecraft, launched on July 15, 2004, are described. These algorithms are used to produce estimates of geophysical parameters such as vertical profiles of atmospheric temperature and composition (‘Level 2’ data) from the calibrated MLS observations of microwave limb radiance (‘Level 1’ data). The MLS algorithms are based on the standard optimal estimation approach, a weighted nonlinear least squares optimization with a priori constraints. New aspects include adaptation to a two-dimensional system, and an approach to the issues of retrieval ‘phasing’ and error propagation that differs from that taken for previous similar instruments. Important new aspects of the software that implements these algorithms are also described, along with the algorithm configuration for the ‘version 1.5’ dataset. Some examples are shown from MLS in-orbit observations. [ABSTRACT FROM AUTHOR]

Deals with a study that evaluated the accuracy of the digital elevation model generated by the Jet Propulsion Laboratory TOPSAR for extracting canopy height. Description of the test site and the ground-based measurements; Analysis of the two height estimation algorithms; Conclusions.

This article provides information about extended versions of four of the best papers presented at the Eleventh Annual Conference on Computer Assurance, with the theme of "Industrial Strength Research," held at the National Institute of Standards and Technology in Gaithersburg, Maryland, in June 1996. These papers address the issue of how to apply the theory of high assurance computing to system and software development. The first paper, "An Industrial-Strength Theorem Prover for a Logic Based on Common Lisp" describes a computational logic for Applicative Common Lisp (ACL2), a reimplemented, extended version of the Boyer-Moore theorem prover. In the second paper, titled, "Comparing Verification Systems: Interactive Consistency in ACL2," researchers have developed a multitude of formal techniques for specifying and verifying computer systems. The benchmark problem exists in this type of specification is the Oral Messages algorithm, a generalization of the Byzantine Generals problem. The third paper, "Using a Protean Language to Enhance Expressiveness in Specification," introduces a Protean specification language, a generalization of process algebras that allows the user to invent his own domain-specific operators to improve abstraction and readability.

This article presents a brief information, on computer scientist Robert W. Floyd. Floyd was born on June 8, 1936, New York City. Floyd died on September 25, 2001 in Palo Alto, California. Floyd graduated from the University of Chicago, in liberal arts, in 1953. Floyd worked as a computer operator/programmer/analyser at Armour Research Foundation. He also worked at Massachusetts-based Computer Associates Inc., as a senior project scientist 1962-1965. He also served at the Carnegie Institute of Technology, as an associate professor, from 1965-1968; as associate professor at Stanford University, from 1968-70. Floyd got Guggenheim Foundation Fellowship, from 1976-77; prize from the Association for Computing Machinery: Turing Prize in 1978; IEEE Computer Pioneer Award in 1991.

The article focuses on the effort of the U.S. Food and Drug Administration to mitigate the problem of reducing drug name confusion with the use of Phonetic Orthographic Computer Analysis (POCA), a system for computationally comparing look-alike or sound-alike drug names. Greg Kondrak of the University of Alberta has developed the ALINE, an algorithm for aligning phonetic sequences, installed in POCA. The ALINE program identifies similar-sounding words represented by phonetic symbols. Its principal component is a function that calculates the similarities of two words in terms of binary or multivalued phonetic features called phonemes.