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: As part of the global response to the HIV/AIDS epidemic, the U.S. President's Emergency Plan for AIDS Relief (PEPFAR) is committed to the provision of high?quality services and ensuring testing accuracy. Two recently published papers focusing on HIV testing and misdiagnosis in sub?Saharan Africa by Kosack et al. report on evaluations of HIV rapid diagnostic tests (RDTs) and found lower than expected specificity and sensitivity on some tests when used in certain geographic locations. The magnitude of PEPFAR's global HIV response has been possible due to the extensive use of RDTs, which have made HIV diagnosis accessible all over the world. We take the opportunity to address concerns raised about the potential implications that these findings could have on real?world HIV testing accuracy. PEPFAR supported countries adhere to the normative guidance by World Health Organization (WHO) supporting algorithms which require sequential positive tests for diagnostic accuracy. An analysis of Médecins Sans Frontières (MSF) RDT site?specific data applied to PEPFAR in?country protocols demonstrate a variation in the diagnostic accuracy of the testing algorithms, but with a very small population?level effect. The data demonstrate, with the use of these algorithms, that the RDT outcomes found in the study by Kosack et al. would be largely mitigated and would not be expected to have a significant impact on diagnostic accuracy and overall programming in most countries. Avoiding any misdiagnosis is a priority for PEPFAR, and it remains vital to gain a deeper understanding of the causes and the extent of diagnostic errors and any misclassification. Extensive quality control mechanisms and continued research are essential. With a focus on epidemic control and ensuring diagnostic accuracy, PEPFAR recommends that all countries use WHO pre?qualified RDTs within the recommended strategies and algorithms for HIV testing. We also support validation of HIV testing algorithms using in?country specimens to determine optimal performance, and the reverification testing of all people diagnosed with HIV prior to starting treatment as an essential quality assurance measure., Introduction The recently published papers, Towards more accurate HIV testing in sub?Saharan Africa: a multi?site evaluation of HIV RDTs and risk factors for false positives and HIV misdiagnosis in sub?Saharan [...]

This paper discusses the tracking speed for different types of sun tracking algorithms, particularly the latitude-oriented spinning-elevation tracking mode in the solar energy application. It is found that the tracking speed of the spinning axis of a latitude-oriented type of heliostat varies drastically during solar noon around days of equinox. We analyze the time intervals during which the heliostat requires faster tracking speed and discuss the causes and possible solutions. [DOI: 10.1115/1.3142829] Keywords: tracking speed, spinning elevation, latitude oriented, heliostat, target aligned

We discuss desirable features that optimization algorithms should posses to exhibit good empirical performance when applied to solve simulation optimization problems possessing little known structure. Our framework emphasizes maintaining an […]

The formalization of music has not always covered so readily the form of music, particularly from a psychological angle that takes the listener into account. Some novel forms have been organizational by-products of the top-down application of grammars or probability distributions. Many works have utilized bottom-up generation of material ready for human arrangement, or accepted existing stylistic templates from music theories. Whilst material might be generated to fill particular sections, the relations between sections and between hierarchical layers, and particularly the control of musical tension through transition, have received far less attention. Algorithmic music often seems stuck in a static moment form, able to abruptly jump between composed sections but unable to demonstrate much real dramatic direction. In part, this is because such ebb and flow engages with seemingly unformalizable attributes of the human musical experience, with musical expectancy, memory and emotion. Nevertheless, since automated music has not been shy about formalizing other aspects of musical structure, and human beings are intimately involved in authoring musical systems, it would seem a highly productive avenue to explore further the possibilities of algorithmic musical form from a psychological angle. Keywords: Musical Form; Algorithmic Composition; Macro-structure; Large-scale Works; Musical Tension

Thispaper presents a biconjugate gradient (BiCG) method that can significantly improve the performance of the quasi-static finite-difference scheme, which has been widely used to model field induction phenomena in voxel phantoms. The proposed BiCG method offers remarkable computational advantages in terms of convergence performance and memory consumption over the conventional iterative, successive overrelaxation algorithm. The scheme has been validated against other known solutions on a lossy, multilayered ellipsoid phantom excited by an ideal coil loop. The wide application capability and computational performance of the BiCG method is demonstrated by modeling the exposure of MRI healthcare workers to fields produced by pulsed field gradients. This is an important topic of research in light of the Physical Agents Directive 2004/40/EC because a variety of realistic operator postures near the bore entrance of an MRI system are modeled. Index Terms--Biconjugate gradient (BiCG) method, MRI, quasi-static finite-difference (QSFD), successive overrelaxation (SOR).

Byline: Eliyahu Osherovich (The Computer Science Department, Technion-Israel Institute of Technology, Haifa 32000, Israel oeli@cs.technion.ac.il); Vladimir Yanovki (The Computer Science Department, Technion-Israel Institute of Technology, Haifa 32000, Israel); Israel A. [...]

ABSTRACT Scheduling problems have received ample attention in every context of manufacturing, mainly because of the optimization solutions they yield. Firms often face bottle-necks due to limited capacities and time [...]

In this paper, we present a new tree mining algorithm, DRYADEPARENT, based on the hooking principle first introduced in DRYADE. In the experiments, we demonstrate that the branching factor and depth of the frequent patterns to find are key factors of complexity for tree mining algorithms, even if often overlooked in previous work. We show that DRYADEPARENT outperforms the current fastest algorithm, CMTreeMiner, by orders of magnitude on data sets where the frequent tree patterns have a high branching factor. Index Terms--Data mining, mining methods and algorithms, mining tree structured data.

Progressively emphasizing samples that are difficult to classify correctly is the base for the recognized high performance of real Adaboost (RA) ensembles. The corresponding emphasis function can be written as a product of a factor that measures the quadratic error and a factor related to the proximity to the classification border; this fact opens the door to explore the potential advantages provided by using adjustable combined forms of these factors. In this paper, we introduce a principled procedure to select the combination parameter each time a new learner is added to the ensemble, just by maximizing the associated edge parameter, calling the resulting method the dynamically adapted weighted emphasis RA (DW-RA). A number of application examples illustrates the performance improvements obtained by DW-RA. Index Terms--Adaboost, boosting, convex combination, dynamic parameter selection, emphasis.

An innovative approach for the optimal matching of independently optimum sum and difference patterns through sub-arrayed monopulse linear arrays is presented. By exploiting the relationship between the independently optimal sum and difference excitations, the set of possible solutions is considerably reduced and the synthesis problem is recast as the search of the best solution in a noncomplete binary tree. Towards this end, a fast resolution algorithm that exploits the presence of elements more suitable to change subarray membership is presented. The results of a set of numerical experiments are reported in order to validate the proposed approach pointing out its effectiveness also in comparison with state-of-the-art optimal matching techniques. Index Terms--Linear arrays, monopulse antennas, sum and difference pattern synthesis, tree-searching algorithm.

This correspondence presents a construction of affine reflection group codes. The solution to the initial vector and nearest distance problem is presented for all irreducible affine reflection groups of rank n [greater than or equal to] 2, for varying stabilizer subgroups. We use a detailed analysis of the geometry of affine reflection groups to produce a decoding algorithm which is equivalent to the maximum-likelihood decoder, yet whose complexity depends only on the dimension of the vector space containing the codewords, and not on the number of codewords. We give several examples of the decoding algorithm, both to demonstrate its correctness and to show how, in small rank cases, it may be further streamlined by exploiting additional symmetries of the group. Index Terms--Affine reflection groups, decoding schemes, group codes, initial vector problem.

Aggregation plays a central role as a means of combining all opinions that are expressed by group members in a group decision support system (GDSS). In this paper, we propose a new [epsilon]-ASA (Aggregation based on Situation Assessment) algorithm to reflect a decision situation in the aggregation process. Although some research findings showed the importance of cultural factors in GDSS, most of them did not present how to implement cultural factors in GDSS. To handle this problem, we present a proposal for reflecting status differentials in GDSS. It may be used to reflect cultural differences in GDSS design. It is a further step toward the integration of cultural factors into existing GDSS design. Index Terms--Aggregation, cultural differences, group decision support system (GDSS), status differentials.

Diversity order is an important measure for the performance of communication systems over multiple-input-multiple-output (MIMO) fading channels. In this correspondence, we prove that in MIMO multiple-access systems (or MIMO point-to-point systems with V-BLAST transmission), lattice-reduction-aided decoding achieves the maximum receive diversity (which is equal to the number of receive antennas). Also, we prove that the naive lattice decoding (which discards the out-of-region decoded points) achieves the maximum diversity. Index Terms--Lattice decoding, LLL lattice-basis reduction, multiple-input-multiple-output (MIMO) fading channels, recieve diversity, V-BLAST.

This work focuses on the expansion properties of a Tanner Graph because they are known to be related to the performance of associated iterative message-passing algorithms over various channels. By analyzing the eigenvalues and corresponding eigenvectors of the normalized incidence matrix representing a Tanner Graph, lower bounds on these expansion properties are derived. Specifically, for the binary erasure channel, these results lead to two lower bounds on stopping distance for any given binary linear code and an upper bound on stopping redundancy for the family of difference-set codes (type-I 2-D projective geometry low-density parity-check (LDPC) codes). Index Terms--Expansion of graphs, low-density parity-check (LDPC) codes, spectral graph theory, stopping distance and stopping redundancy, Tanner graphs.

This paper demonstrates theoretically and empirically that a greedy algorithm called Orthogonal Matching Pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m ln d) random linear measurements of that signal. This is a massive improvement over previous results, which require O([m.sup.2]) measurements. The new results for OMP are comparable with recent results for another approach called Basis Pursuit (BP). In some settings, the OMP algorithm is faster and easier to implement, so it is an attractive alternative to BP for signal recovery problems. Index Terms--Algorithms, approximation, basis pursuit, compressed sensing, group testing, orthogonal matching pursuit, signal recovery, sparse approximation.

Random access is well motivated and has been widely applied when the network traffic is bursty and the expected throughput is not high. The main reason behind relatively low-throughput expectations is that collided packets are typically discarded. In this paper, we develop a novel protocol exploiting successive interference cancellation (SIC) in a tree algorithm (TA), where collided packets are reserved for reuse. Our SICTA protocol can achieve markedly higher maximum stable throughput relative to existing alternatives. Throughput performance is analyzed for general d-ary SICTA with both gated and window access. It is shown that the throughput for d-ary SICTA with gated access is about (ln d)/(d - 1), and can reach 0.693 for d = 2. This represents a 40% increase over the renowned first-come-first-serve (FCFS) 0.457 tree algorithm. Delay performance is also analyzed for SICTA with gated access, and numerical results are provided. Index Terms--Collision resolution, Markov chain, maximum stable throughput, random access, tree protocol.

We consider the class of strong-mixing probability laws with positive transitions that are defined on doubly infinite sequences in a finite alphabet A. A device called the classifier (or discriminator) observes a training sequence whose probability law Q is unknown. The classifier's task is to consider a second probability law P and decide whether P = Q, or P and Q are sufficiently different according to some appropriate criterion [DELTA](Q, P) > [DELTA]. If the classified has available an infinite amount of training data, this is a simple matter. However, here we study the case where the amount of training data is limited to N letters. We define a function [N.sub.[DELTA]](Q|P), which quantifies the minimum length sequence needed to distinguish Q and P and the class M([N.sub.[DELTA]]) of all probability laws pairs (Q, P) that satisfy [N.sub.[DELTA]](Q|P) [less than or equal to] [N.sub.[DELTA]] for some given positive number [N.sub.[DELTA]]. It is shown that every pair Q, P of probability laws that are sufficiently different according to the [DELTA] criterion is contained in M([N.sub.[DELTA]]). We demonstrate that for any universal classifier there exists some Q for which the classification probability [lambda](Q) = 1 for some N-sequence emerging from Q, for some P : (Q. P) [member of] [??]([N.sub.[DELTA]). [DELTA](Q, P) > [DELTA], if N < [N.sub.[DELTA]]. Conversely, we introduce a classification algorithm that is essentially optimal in the sense that for every (Q, P) [member of] M([N.sub.[DELTA]]), the probability of classification error [lambda](Q) is uniformly vanishing with N for every P : (Q, P) [member of] [??]([N.sub.[DELTA]]) if [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. The proposed algorithm finds the largest empirical conditional divergence for a set of contexts which appear in the tested N-sequence. The computational complexity of the classification algorithm is O([N.sup.2] [(log N).sup.3])). Also, we introduce a second simplified context classification algorithm with a computational complexity of only O(N[(log N).sup.4] that is efficient in the sense that for every pair (Q, P) [member of] M ([N.sub.[DELTA]]) the pairwise probability of classification error [lambda](Q, P) for the pair Q, P vanishes with N if [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. Conversely, [lambda](Q, P) - 1 at least for some (Q, P) [member of] M([N.sub.[DELTA]], if N < [N.sub.[DELTA]]. Index Terms--Context-tree algorithms, universal classification, universal prediction.

Novel conditions are derived that guarantee convergence of the Sum-Product Algorithm (also known as Loopy Belief Propagation or simply Belief Propagation (BP)) to a unique fixed point, irrespective of the initial messages, for parallel (synchronous) updates. The computational complexity of the conditions is polynomial in the number of variables. In contrast with previously existing conditions, our results are directly applicable to arbitrary factor graphs (with discrete variables) and are shown to be valid also in the case of factors containing zeros, under some additional conditions. The conditions are compared with existing ones, numerically and, if possible, analytically. For binary variables with pairwise interactions, sufficient conditions are derived that take into account local evidence (i.e., single-variable factors) and the type of pair interactions (attractive or repulsive). It is shown empirically that this bound outperforms existing bounds. Index Terms--Contraction, convergence, factor graphs, graphical models, loopy belief propagation, marginalization, message passing, sum-product algorithm.

This paper proposed a fast vector quantization encoding algorithm called difference pyramid search (DPS). According to the formation of the difference pyramid and partial distortion elimination, a rejection test inequality is derived to progressively reject a lot of nonclosest code words as early as possible. Experimental results show that the proposed DPS algorithm outperforms other pyramid-based fast search algorithms, including mean pyramid search, L2-norm pyramid search, and mean-variance pyramid search. Index Terms--Difference pyramid, mean pyramid, partial distortion elimination (PDE), vector quantization (VQ).

In January 2006, the Data Fusion Committee of the IEEE Geoscience and Remote Sensing Society launched a public contest for pansharpening algorithms, which aimed to identify the ones that perform best. Seven research groups worldwide participated in the contest, testing eight algorithms following different philosophies [component substitution, multiresolution analysis (MRA), detail injection, etc.]. Several complete data sets from two different sensors, namely, QuickBird and simulated Pleiades, were delivered to all participants. The fusion results were collected and evaluated, both visually and objectively. Quantitative results of pansharpening were possible owing to the availability of reference originals obtained either by simulating the data collected from the satellite sensor by means of higher resolution data from an airborne platform, in the case of the Pleiades data, or by first degrading all the available data to a coarser resolution and saving the original as the reference, in the case of the QuickBird data. The evaluation results were presented during the special session on Data Fusion at the 2006 International Geoscience and Remote Sensing Symposium in Denver, and these are discussed in further detail in this paper. Two algorithms outperform all the others, the visual analysis being confirmed by the quantitative evaluation. These two methods share the same philosophy: they basically rely on MRA and employ adaptive models for the injection of high-pass details. Index Terms--Image fusion, multispectral (MS) imagery, pansharpening, quality assessment, QuickBird (QB), simulated Pleiades data.

A central goal of chemistry is to fabricate supramolecular structures of defined function and composition. In biology, control of supramolecular synthesis is often achieved through precise control over nucleation and growth processes: A seed molecule initiates growth of a structure, but this growth is kinetically inhibited in the seed's absence. Here we show how such control can be systematically designed into self-assembling structures made of DNA tiles. These structures, 'zig-zag ribbons,' are designed to have a fixed width but can grow arbitrarily long. Under slightly supersaturated conditions, theory predicts that elongation is always favorable but that nucleation rates decrease exponentially with increasing width. We confirm experimentally that although ribbons of different widths have similar thermodynamics, nucleation rates decrease for wider ribbons. It is therefore possible to program the nucleation rate by choosing a ribbon width. The presence of a seed molecule, a stabilized version of the presumed critical nucleus, removes the kinetic barrier to nucleation of a ribbon. Thus, we demonstrate the ability to grow supramolecular structures from rationally designed seeds, while suppressing spurious nucleation. Control over DNA tile nucleation allows for proper initiation of algorithmic crystal growth, which could lead to the high-yield synthesis of micrometer-scale structures with complex programmed features. More generally, this work shows how a self-assembly subroutine can be initiated. algorithmic self-assembly | DNA nanotechnology | self-assembly | supramolecular chemistry

The Hull-White model is a one factor Markov model well known for its capability to capture the current term structure of interest rates. Analytical results are available for pricing zero-coupon [...]

Evolutionary algorithms adopt a natural-selection analogy, exploiting concepts such as population, combination, mutation, and selection to explore a diverse space of possible solutions to combinatorial optimization problems while, at the […]

The classic Bellman-Ford algorithm for calculating shortest paths can be easily adapted to a distributed environment in which the computations are performed locally by identical processors at each network node. […]

There has been significant progress in improving the performance of computer-based face recognition algorithms over the last decade. Although algorithms have been tested and compared extensively with each other, there has been remarkably little work comparing the accuracy of computer-based face recognition systems with humans. We compared seven state-of-the-art face recognition algorithms with humans on a face-matching task. Humans and algorithms determined whether pairs of face images, taken under different illumination conditions, were pictures of the same person or of different people. Three algorithms surpassed human performance matching face pairs prescreened to be "difficult" and six algorithms surpassed humans on "easy" face pairs. Although illumination variation continues to challenge face recognition algorithms, current algorithms compete favorably with humans. The superior performance of the best algorithms over humans, in light of the absolute performance levels of the algorithms, underscores the need to compare algorithms with the best current control--humans. Index Terms--Face and gesture recognition, performance evaluation of algorithms and systems, human information processing.

In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The prior distribution is based on the Probabilistic Principal Component Analysis (PPCA). We also propose a new model based on mixtures of PPCA that is useful in the case of greater variability in the shape. A criterion of global or local object specificity based on a preliminary color segmentation of the image is included into the model. The localization of a shape in an image is then viewed as minimizing the corresponding Gibbs field. We use the Exploration/Selection (E/S) stochastic algorithm in order to find the optimal deformation. This yields a new unsupervised statistical method for localization of shapes. In order to estimate the statistical parameters for the gradient vector field of the gray level, we use an Iterative Conditional Estimation (ICE) procedure. The color segmentation of the image can be computed with an Exploration/Selection/Estimation (ESE) procedure. Index Terms--Shape localization, statistical model, stochastic optimization, Exploration/Selection (E/S) algorithm, Probabilistic Principal Component Analysis (PPCA).

In this paper, based on ideas from lossy data coding and compression, we present a simple but effective technique for segmenting multivariate mixed data that are drawn from a mixture of Gaussian distributions, which are allowed to be almost degenerate. The goal is to find the optimal segmentation that minimizes the overall coding length of the segmented data, subject to a given distortion. By analyzing the coding length/rate of mixed data, we formally establish some strong connections of data segmentation to many fundamental concepts in lossy data compression and rate-distortion theory. We show that a deterministic segmentation is approximately the (asymptotically) optimal solution for compressing mixed data. We propose a very simple and effective algorithm that depends on a single parameter, the allowable distortion. At any given distortion, the algorithm automatically determines the corresponding number and dimension of the groups and does not involve any parameter estimation. Simulation results reveal intriguing phase-transition-like behaviors of the number of segments when changing the level of distortion or the amount of outliers. Finally, we demonstrate how this technique can be readily applied to segment real imagery and bioinformatic data. Index Terms--Multivariate mixed data, data segmentation, data clustering, rate distortion, lossy coding, lossy compression, image segmentation, microarray data clustering.

A variety of algorithms for the detection of landmines and discrimination between landmines and clutter objects have been presented. We discuss four quite different approaches in using data collected by a vehicle-mounted ground-penetrating radar sensor to detect landmines and distinguish them from clutter objects. One uses edge features in a hidden Markov model; the second uses geometric features in a feed-forward order-weighted average network; the third employs spectral features as its basis; and the fourth clusters edge histograms. We present the results of a large-scale cross-validation evaluation that uses a diverse set of data collected over 41 807.57 [m.sup.2] of ground, including 1593 mine encounters. Finally, we discuss the results of that ranking and what one can conclude concerning the performance of these four algorithms in various settings. Index Terms--Discrimination, ground-penetrating radar (GPR), landmine detection.

Data association which obtains relationship between radar measurements and existing tracks plays one important role in radar multiple-target tracking (MTT) systems. A new approach to data association based on the competitive Hopfield neural network (CHNN) is investigated, where the matching between radar measurements and existing target tracks is used as a criterion to achieve a global consideration. Embedded within the CHNN is a competitive learning algorithm that resolves the dilemma of occasional irrational solutions in traditional Hopfield neural networks. Additionally, it is also shown that our proposed CHNN-based network is guaranteed to converge to a stable state in performing data association and the CHNN-based data association combined with an MTT system demonstrates target tracking capability. Computer simulation results indicate that this approach successfully solves the data association problems.

We consider the problem of waveform design for multiple input/multiple output (MIMO) radars, where the transmit waveforms are adjusted based on target and clutter statistics. A model for the radar returns which incorporates the transmit waveforms is developed. The target detection problem is formulated for that model. Optimal and suboptimal algorithms are derived for designing the transmit waveforms under different assumptions regarding the statistical information available to the detector. The performance of these algorithms is illustrated by computer simulation.

By using a linear antenna array, velocity synthetic aperture radar (VSAR) can detect, focus, and locate slowly moving targets well. However, it may mis-locate fast moving targets in the azimuth (cross-range) direction. In this correspondence, we propose a synthetic aperture radar (SAR) with a nonuniform linear antenna array and give a design of the antenna arrangement. It is shown that our proposed nonuniform linear antenna array SAR (NULA-SAR) can locate both slowly and fast moving targets correctly. An integrated NULA-SAR algorithm for moving target imaging is also presented, and it is verified by some simulations.

We consider radar waveform selection algorithms for tracking accelerating targets. Tracking is handled within an interacting multiple model (IMM) framework, which produces a number of potential cost functions for minimization. The waveform library is obtained by implementing a fractional Fourier transform on a base waveform, thereby rotating its ambiguity function around its peak. This has the effect of rotating the lower bound of measurement covariance in the range-Doppler plane. Simulation results consider a number of potential cost functions, and show robustness to cases in which the target modes are not precisely known.

It is of great importance to develop a robust and fast tracking algorithm in passive localization and tracking system because of its inherent disadvantages such as weak observability and large initial errors. In this correspondence, a new algorithm referred to as the iterated unscented Kalman filter (IUKF) is proposed based on the analysis and comparison of conventional nonlinear tracking problem. The algorithm is developed from UKF but it can obtain more accurate state and covariance estimation. Compared with the traditional approaches (e.g., extended Kalman filter (EKF) and UKF) used in passive localization, the proposed method has potential advantages in robustness, convergence speed, and tracking accuracy. The correctness as well as validity of the algorithm is demonstrated through numerical simulation and experiment results.

Among target tracking algorithms using Kalman filtering-like approaches, the standard assumptions are Gaussian process and measurement noise models. Based on these assumptions, the Kalman filter is widely used in single or multiple filter versions (e.g., in an interacting multiple model (IMM) estimator). The oversimplification resulting from the above assumptions can cause degradation in tracking performance. In this paper we explore the application of Kalman-Levy filter to handle maneuvering targets. This filter assumes a heavy-tailed noise distribution known as the Levy distribution. Due to the heavy-tailed nature of the assumed distribution, the Kalman-Levy filter is more effective in the presence of large errors that can occur, for example, due to the onset of acceleration or deceleration. However, for the same reason, the performance of the Kalman-Levy filter in the nonmaneuvering portion of track is worse than that of a Kalman filter. For this reason, an IMM with one Kalman and one Kalman-Levy module is developed here. Also, the superiority of the IMM with Kalman-Levy module over only Kalman-filter-based IMM for realistic maneuvers is shown by simulation results.