93 resultados para Search Engines
Resumo:
Many of the research institutions and universities across the world are facilitating open-access (OA) to their intellectual outputs through their respective OA institutional repositories (IRs) or through the centralized subject-based repositories. The registry of open access repositories (ROAR) lists more than 2850 such repositories across the world. The awareness about the benefits of OA to scholarly literature and OA publishing is picking up in India, too. As per the ROAR statistics, to date, there are more than 90 OA repositories in the country. India is doing particularly well in publishing open-access journals (OAJ). As per the directory of open-access journals (DOAJ), to date, India with 390 OAJs, is ranked 5th in the world in terms of numbers of OAJs being published. Much of the research done in India is reported in the journals published from India. These journals have limited readership and many of them are not being indexed by Web of Science, Scopus or other leading international abstracting and indexing databases. Consequently, research done in the country gets hidden not only from the fellow countrymen, but also from the international community. This situation can be easily overcome if all the researchers facilitate OA to their publications. One of the easiest ways to facilitate OA to scientific literature is through the institutional repositories. If every research institution and university in India set up an open-access IR and ensure that copies of the final accepted versions of all the research publications are uploaded in the IRs, then the research done in India will get far better visibility. The federation of metadata from all the distributed, interoperable OA repositories in the country will serve as a window to the research done across the country. Federation of metadata from the distributed OAI-compliant repositories can be easily achieved by setting up harvesting software like the PKP Harvester. In this paper, we share our experience in setting up a prototype metadata harvesting service using the PKP harvesting software for the OAI-compliant repositories in India.
Resumo:
The spatial search problem on regular lattice structures in integer number of dimensions d >= 2 has been studied extensively, using both coined and coinless quantum walks. The relativistic Dirac operator has been a crucial ingredient in these studies. Here, we investigate the spatial search problem on fractals of noninteger dimensions. Although the Dirac operator cannot be defined on a fractal, we construct the quantum walk on a fractal using the flip-flop operator that incorporates a Klein-Gordon mode. We find that the scaling behavior of the spatial search is determined by the spectral (and not the fractal) dimension. Our numerical results have been obtained on the well-known Sierpinski gaskets in two and three dimensions.
Resumo:
We report our search for and a possible detection of periodic radio pulses at 34.5 MHz from the Fermi Large Area Telescope pulsar J1732-3131. The candidate detection has been possible in only one of the many sessions of observations made with the low-frequency array at Gauribidanur, India, when the otherwise radio weak pulsar may have apparently brightened many folds. The candidate dispersion measure along the sight line, based on the broad periodic profiles from �20min of data, is estimated to be 15.44 ± 0.32 pccc -1. We present the details of our periodic and single-pulse search, and discuss the results and their implications relevant to both, the pulsar and the intervening medium. © 2012 RAS.
Resumo:
We show that the operation and the output power of a quantum heat engine that converts incoherent thermal energy into coherent cavity photons can be optimized by manipulating quantum coherences. The gain or loss in the efficiency at maximum power depends on the details of the output power optimization. Quantum effects tend to enhance the output power and the efficiency as the photon occupation in the cavity is decreased.
Resumo:
Protein structure comparison is essential for understanding various aspects of protein structure, function and evolution. It can be used to explore the structural diversity and evolutionary patterns of protein families. In view of the above, a new algorithm is proposed which performs faster protein structure comparison using the peptide backbone torsional angles. It is fast, robust, computationally less expensive and efficient in finding structural similarities between two different protein structures and is also capable of identifying structural repeats within the same protein molecule.
Resumo:
Our everyday visual experience frequently involves searching for objects in clutter. Why are some searches easy and others hard? It is generally believed that the time taken to find a target increases as it becomes similar to its surrounding distractors. Here, I show that while this is qualitatively true, the exact relationship is in fact not linear. In a simple search experiment, when subjects searched for a bar differing in orientation from its distractors, search time was inversely proportional to the angular difference in orientation. Thus, rather than taking search reaction time (RT) to be a measure of target-distractor similarity, we can literally turn search time on its head (i.e. take its reciprocal 1/RT) to obtain a measure of search dissimilarity that varies linearly over a large range of target-distractor differences. I show that this dissimilarity measure has the properties of a distance metric, and report two interesting insights come from this measure: First, for a large number of searches, search asymmetries are relatively rare and when they do occur, differ by a fixed distance. Second, search distances can be used to elucidate object representations that underlie search - for example, these representations are roughly invariant to three-dimensional view. Finally, search distance has a straightforward interpretation in the context of accumulator models of search, where it is proportional to the discriminative signal that is integrated to produce a response. This is consistent with recent studies that have linked this distance to neuronal discriminability in visual cortex. Thus, while search time remains the more direct measure of visual search, its reciprocal also has the potential for interesting and novel insights. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.
Resumo:
How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation.
Resumo:
This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.
Resumo:
This paper presents computational work on the biogas early phase combustion in spark ignition (SI) engines using detailed chemical kinetics. Specifically, the early phase combustion is studied to assess the effect of various ignition parameters such as spark plug location, spark energy, and number of spark plugs. An integrated version of the KIVA-3V and CHEMKIN codes was developed and used for the simulations utilizing detailed kinetics involving 325 reactions and 53 species The results show that location of the spark plug and local flow field play an important role. A central plug configuration, which is associated with higher local flow velocities in the vicinity of the spark plug, showed faster initial combustion. Although a dual plug configuration shows the highest rate of fuel consumption, it is comparable to the rate exhibited by the central plug case. The radical species important in the initiation of combustion are identified, and their concentrations are monitored during the early phase of combustion. The concentration of these radicals is also observed to correlate very well with the above-mentioned trend.Thus, the role of these radicals in promoting faster combustion has been clearly established. It is also observed that the minimum ignition energy required to initiate a self-sustained flame depends on the flow field condition in the vicinity of the spark plug.Increasing the methane content in the biogas has shown improved combustion.
Resumo:
Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.
Resumo:
In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role.
Resumo:
Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.
Resumo:
The paper addresses experiments and modeling studies on the use of producer gas, a bio-derived low energy content fuel in a spark-ignited engine. Producer gas, generated in situ, has thermo-physical properties different from those of fossil fuel(s). Experiments on naturally aspirated and turbo-charged engine operation and subsequent analysis of the cylinder pressure traces reveal significant differences in the heat release pattern within the cylinder compared with a typical fossil fuel. The heat release patterns for gasoline and producer gas compare well in the initial 50% but beyond this, producer gas combustion tends to be sluggish leading to an overall increase in the combustion duration. This is rather unexpected considering that producer gas with nearly 20% hydrogen has higher flame speeds than gasoline. The influence of hydrogen on the initial flame kernel development period and the combustion duration and hence on the overall heat release pattern is addressed. The significant deviations in the heat release profiles between conventional fuels and producer gas necessitates the estimation of producer gas-specific Wiebe coefficients. The experimental heat release profiles are used for estimating the Wiebe coefficients. Experimental evidence of lower fuel conversion efficiency based on the chemical and thermal analysis of the engine exhaust gas is used to arrive at the Wiebe coefficients. The efficiency factor a is found to be 2.4 while the shape factor m is estimated at 0.7 for 2% to 90% burn duration. The standard Wiebe coefficients for conventional fuels and fuel-specific coefficients for producer gas are used in a zero D model to predict the performance of a 6-cylinder gas engine under naturally aspirated and turbo-charged conditions. While simulation results with standard Wiebe coefficients result in excessive deviations from the experimental results, excellent match is observed when producer gas-specific coefficients are used. Predictions using the same coefficients on a 3-cylinder gas engine having different geometry and compression ratio(s) indicate close match with the experimental traces highlighting the versatility of the coefficients.
Resumo:
Experimental and simulation studies have uncovered at least two anomalous concentration regimes in water-dimethyl sulfoxide (DMSO) binary mixture whose precise origin has remained a subject of debate. In order to facilitate time domain experimental investigation of the dynamics of such binary mixtures, we explore strength or extent of influence of these anomalies in dipolar solvation dynamics by carrying out long molecular dynamics simulations over a wide range of DMSO concentration. The solvation time correlation function so calculated indeed displays strong composition dependent anomalies, reflected in pronounced non-exponential kinetics and non-monotonous composition dependence of the average solvation time constant. In particular, we find remarkable slow-down in the solvation dynamics around 10%-20% and 35%-50% mole percentage. We investigate microscopic origin of these two anomalies. The population distribution analyses of different structural morphology elucidate that these two slowing down are reflections of intriguing structural transformations in water-DMSO mixture. The structural transformations themselves can be explained in terms of a change in the relative coordination number of DMSO and water molecules, from 1DMSO:2H(2)O to 1H(2)O:1DMSO and 1H(2)O:2DMSO complex formation. Thus, while the emergence of first slow down (at 15% DMSO mole percentage) is due to the percolation among DMSO molecules supported by the water molecules (whose percolating network remains largely unaffected), the 2nd anomaly (centered on 40%-50%) is due to the formation of the network structure where the unit of 1DMSO:1H(2)O and 2DMSO:1H(2)O dominates to give rise to rich dynamical features. Through an analysis of partial solvation dynamics an interesting negative cross-correlation between water and DMSO is observed that makes an important contribution to relaxation at intermediate to longer times.