Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Mining Unit Tests for Discovery and Migration of Math APIs

Today's programming languages are supported by powerful third-party APIs. For a given application domain, it is common to have many competing APIs that provide similar functionality. Programmer productivity therefore depends heavily on the programmer's ability to discover suitable APIs both during an initial coding phase, as well as during software maintenance. The aim of this work is to support the discovery and migration of math APIs. Math APIs are at the heart of many application domains ranging from machine learning to scientific computations. Our approach, called MATHFINDER, combines executable specifications of mathematical computations with unit tests (operational specifications) of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code comprised of API methods to compute the expression by mining unit tests of the API methods. We present a sequential version of our unit test mining algorithm and also design a more scalable data-parallel version. We perform extensive evaluation of MATHFINDER (1) for API discovery, where math algorithms are to be implemented from scratch and (2) for API migration, where client programs utilizing a math API are to be migrated to another API. We evaluated the precision and recall of MATHFINDER on a diverse collection of math expressions, culled from algorithms used in a wide range of application areas such as control systems and structural dynamics. In a user study to evaluate the productivity gains obtained by using MATHFINDER for API discovery, the programmers who used MATHFINDER finished their programming tasks twice as fast as their counterparts who used the usual techniques like web and code search, IDE code completion, and manual inspection of library documentation. For the problem of API migration, as a case study, we used MATHFINDER to migrate Weka, a popular machine learning library. Overall, our evaluation shows that MATHFINDER is easy to use, provides highly precise results across several math APIs and application domains even with a small number of unit tests per method, and scales to large collections of unit tests.

An open source massively parallel solver for Richards equation: Mechanistic modelling of water fluxes at the watershed scale

In this paper we present a massively parallel open source solver for Richards equation, named the RichardsFOAM solver. This solver has been developed in the framework of the open source generalist computational fluid dynamics tool box OpenFOAM (R) and is capable to deal with large scale problems in both space and time. The source code for RichardsFOAM may be downloaded from the CPC program library website. It exhibits good parallel performances (up to similar to 90% parallel efficiency with 1024 processors both in strong and weak scaling), and the conditions required for obtaining such performances are analysed and discussed. These performances enable the mechanistic modelling of water fluxes at the scale of experimental watersheds (up to few square kilometres of surface area), and on time scales of decades to a century. Such a solver can be useful in various applications, such as environmental engineering for long term transport of pollutants in soils, water engineering for assessing the impact of land settlement on water resources, or in the study of weathering processes on the watersheds. (C) 2014 Elsevier B.V. All rights reserved.

Ligand 5,10,15,20-Tetra(N-methyl-4-pyridyl)porphine (TMPyP4) Prefers the Parallel Propeller-Type Human Telomeric G-Quadruplex DNA over Its Other Polymorphs

The binding of ligand 5,10,15,20-tetra(N-methyl-4-pyridyl)porphine (TMPyP4) with telomeric and genomic G-quadruplex DNA has been extensively studied. However, a comparative study of interactions of TMPyP4 with different conformations of human telomeric G-quadruplex DNA, namely, parallel propeller-type (PP), antiparallel basket-type (AB), and mixed hybrid-type (MH) G-quadruplex DNA, has not been done. We considered all the possible binding sites in each of the G-quadruplex DNA structures and docked TMPyP4 to each one of them. The resultant most potent sites for binding were analyzed from the mean binding free energy of the complexes. Molecular dynamics simulations were then carried out, and analysis of the binding free energy of the TMPyP4-G-quadruplex complex showed that the binding of TMPyP4 with parallel propeller-type G-quadruplex DNA is preferred over the other two G-quadruplex DNA conformations. The results obtained from the change in solvent excluded surface area (SESA) and solvent accessible surface area (SASA) also support the more pronounced binding of the ligand with the parallel propeller-type G-quadruplex DNA.

Common-Mode Injection PWM for Parallel Converters

The ac-side terminal voltages of parallel-connected converters are different if the line reactive drops of the individual converters are different. This could result either from differences in per-phase inductances or from differences in the line currents of the converters. In such cases, the modulating signals are different for the converters. Hence, the common-mode (CM) voltages for the converters, injected by conventional space vector pulsewidth modulation (CSVPWM) to increase dc-bus utilization, are different. Consequently, significant low-frequency zero-sequence circulating currents result. This paper proposes a new modulation method for parallel-connected converters with unequal terminal voltages. This method does not cause low-frequency zero-sequence circulating currents and is comparable with CSVPWM in terms of dc-bus utilization and device power loss. Experimental results are presented at a power level of 150 kVA from a circulating-power test setup, where the differences in converter terminal voltages are quite significant.

A search for chaos in the optical light curve of a blazar: W2R 1926+42

Aims. In this work we search for the signatures of low-dimensional chaos in the temporal behavior of the Kepler-field blazar W2R 1946+42. Methods. We use a publicly available, similar to 160 000-point-long and mostly equally spaced light curve of W2R 1946+42. We apply the correlation integral method to both real datasets and phase randomized surrogates. Results. We are not able to confirm the presence of low-dimensional chaos in the light curve. This result, however, still leads to some important implications for blazar emission mechanisms, which are discussed.

A 0.5-2.0 GHz injection locked oscillator cascade for parallel wideband RF spectrum sensing

An area-efficient, wideband RF frequency synthesizer, which simultaneously generates multiple local oscillator (LO) signals, is designed. It is suitable for parallel wideband RF spectrum sensing in cognitive radios. The frequency synthesizer consists of an injection locked oscillator cascade (ILOC) where all the LO signals are derived from a single reference oscillator. The ILOC is implemented in a 130-nm technology with an active area of . It generates 4 uniformly spaced LO carrier frequencies from 500 MHz to 2 GHz. This design is the first known implementation of a CMOS based ILOC for wide-band RF spectrum sensing applications.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Three-degree-of-freedom Parallel Manipulator to Track the Sun for Concentrated Solar Power Systems

In concentrated solar power(CSP) generating stations, incident solar energy is reflected from a large number of mirrors or heliostats to a faraway receiver. In typical CSP installations, the mirror needs to be moved about two axes independently using two actuators in series with the mirror effectively mounted at a single point. A three degree-of-freedom parallel manipulator, namely the 3-RPS parallel manipulator, is proposed to track the sun. The proposed 3-RPS parallel manipulator supports the load of the mirror, structure and wind loading at three points resulting in less deflection, and thus a much larger mirror can be moved with the required tracking accuracy and without increasing the weight of the support structure. The kinematics equations to determine motion of the actuated prismatic joints in the 3-RPS parallel manipulator such that the sun's rays are reflected on to a stationary receiver are developed. Using finite element analysis, it is shown that for same sized mirror, wind loading and maximum deflection requirement, the weight of the support structure is between 15% and 60% less with the 3-RPS parallel manipulator when compared to azimuth-elevation or the target-aligned configurations.

Active learning in keyword search-based data integration

The problem of scaling up data integration, such that new sources can be quickly utilized as they are discovered, remains elusive: Global schemas for integrated data are difficult to develop and expand, and schema and record matching techniques are limited by the fact that data and metadata are often under-specified and must be disambiguated by data experts. One promising approach is to avoid using a global schema, and instead to develop keyword search-based data integration-where the system lazily discovers associations enabling it to join together matches to keywords, and return ranked results. The user is expected to understand the data domain and provide feedback about answers' quality. The system generalizes such feedback to learn how to correctly integrate data. A major open challenge is that under this model, the user only sees and offers feedback on a few ``top-'' results: This result set must be carefully selected to include answers of high relevance and answers that are highly informative when feedback is given on them. Existing systems merely focus on predicting relevance, by composing the scores of various schema and record matching algorithms. In this paper, we show how to predict the uncertainty associated with a query result's score, as well as how informative feedback is on a given result. We build upon these foundations to develop an active learning approach to keyword search-based data integration, and we validate the effectiveness of our solution over real data from several very different domains.

Efficient Protocol for Authenticated Email Search

Executing authenticated computation on outsourced data is currently an area of major interest in cryptology. Large databases are being outsourced to untrusted servers without appreciable verification mechanisms. As adversarial server could produce erroneous output, clients should not trust the server's response blindly. Primitive set operations like union, set difference, intersection etc. can be invoked on outsourced data in different concrete settings and should be verifiable by the client. One such interesting adaptation is to authenticate email search result where the untrusted mail server has to provide a proof along with the search result. Recently Ohrimenko et al. proposed a scheme for authenticating email search. We suggest significant improvements over their proposal in terms of client computation and communication resources by properly recasting it in two-party settings. In contrast to Ohrimenko et al. we are able to make the number of bilinear pairing evaluation, the costliest operation in verification procedure, independent of the result set cardinality for union operation. We also provide an analytical comparison of our scheme with their proposal which is further corroborated through experiments.

Vocal Tract Length Normalization Features for Audio Search

This paper presents speaker normalization approaches for audio search task. Conventional state-of-the-art feature set, viz., Mel Frequency Cepstral Coefficients (MFCC) is known to contain speaker-specific and linguistic information implicitly. This might create problem for speaker-independent audio search task. In this paper, universal warping-based approach is used for vocal tract length normalization in audio search. In particular, features such as scale transform and warped linear prediction are used to compensate speaker variability in audio matching. The advantage of these features over conventional feature set is that they apply universal frequency warping for both the templates to be matched during audio search. The performance of Scale Transform Cepstral Coefficients (STCC) and Warped Linear Prediction Cepstral Coefficients (WLPCC) are about 3% higher than the state-of-the-art MFCC feature sets on TIMIT database.

Status of the MSSM Higgs sector using global analysis and direct search bounds, and future prospects at the High Luminosity LHC

In this paper, we search for the regions of the phenomenological minimal supersymmetric standard model (pMSSM) parameter space where one can expect to have moderate Higgs mixing angle (alpha) with relatively light (up to 600 GeV) additional Higgses after satisfying the current LHC data. We perform a global fit analysis using most updated data (till December 2014) from the LHC and Tevatron experiments. The constraints coming from the precision measurements of the rare b-decays B-s -> mu(+)mu(-) and b -> s gamma are also considered. We find that low M-A(less than or similar to 350) and high tan beta(greater than or similar to 25) regions are disfavored by the combined effect of the global analysis and flavor data. However, regions with Higgs mixing angle alpha similar to 0.1-0.8 are still allowed by the current data. We then study the existing direct search bounds on the heavy scalar/pseudoscalar (H/A) and charged Higgs boson (H-+/-) masses and branchings at the LHC. It has been found that regions with low to moderate values of tan beta with light additional Higgses (mass <= 600 GeV) are unconstrained by the data, while the regions with tan beta > 20 are excluded considering the direct search bounds by the LHC-8 data. The possibility to probe the region with tan beta <= 20 at the high luminosity run of LHC are also discussed, giving special attention to the H -> hh, H/A -> t (t) over bar and H/A -> tau(+)tau(-) decay modes.

An efficient design of serial and parallel memory using Quantum dot cellular automata

Quantum cellular automata (QCA) is a new technology in the nanometer scale and has been considered as one of the alternative to CMOS technology. In this paper, we describe the design and layout of a serial memory and parallel memory, showing the layout of individual memory cells. Assuming that we can fabricate cells which are separated by 10nm, memory capacities of over 1.6 Gbit/cm2 can be achieved. Simulations on the proposed memories were carried out using QCADesigner, a layout and simulation tool for QCA. During the design, we have tried to reduce the number of cells as well as to reduce the area which is found to be 86.16sq mm and 0.12 nm2 area with the QCA based memory cell. We have also achieved an increase in efficiency by 40%.These circuits are the building block of nano processors and provide us to understand the nano devices of the future.