arXiv subjects

Arnab Bhattacharya

Publications and source records attributed to Arnab Bhattacharya.

At least 109 records · Page 6Linked to original sources

arXiv2012

INSTRUCT: Space-Efficient Structure for Indexing and Complete Query Management of String Databases

The tremendous expanse of search engines, dictionary and thesaurus storage, and other text mining applications, combined with the popularity of readily available scanning devices and optical character recognition tools, has necessitated efficient storage, retrieval and management of massive text databases for various modern applications. For such applications, we propose a novel data structure, INSTRUCT, for efficient storage and management of sequence databases. Our structure uses bit vectors for reusing the storage space for common triplets, and hence, has a very low memory requirement. INSTRUCT efficiently handles prefix and suffix search queries in addition to the exact string search operation by iteratively checking the presence of triplets. We also propose an extension of the structure to handle substring search efficiently, albeit with an increase in the space requirements. This extension is important in the context of trie-based solutions which are unable to handle such queries efficiently. We perform several experiments portraying that INSTRUCT outperforms the existing structures by nearly a factor of two in terms of space requirements, while the query times are better. The ability to handle insertion and deletion of strings in addition to supporting all kinds of queries including exact search, prefix/suffix search and substring search makes INSTRUCT a complete data structure.

cs.DB↗

arXiv2012

Mining Statistically Significant Substrings using the Chi-Square Statistic

The problem of identification of statistically significant patterns in a sequence of data has been applied to many domains such as intrusion detection systems, financial models, web-click records, automated monitoring systems, computational biology, cryptology, and text analysis. An observed pattern of events is deemed to be statistically significant if it is unlikely to have occurred due to randomness or chance alone. We use the chi-square statistic as a quantitative measure of statistical significance. Given a string of characters generated from a memoryless Bernoulli model, the problem is to identify the substring for which the empirical distribution of single letters deviates the most from the distribution expected from the generative Bernoulli model. This deviation is captured using the chi-square measure. The most significant substring (MSS) of a string is thus defined as the substring having the highest chi-square value. Till date, to the best of our knowledge, there does not exist any algorithm to find the MSS in better than O(n^2) time, where n denotes the length of the string. In this paper, we propose an algorithm to find the most significant substring, whose running time is O(n^{3/2}) with high probability. We also study some variants of this problem such as finding the top-t set, finding all substrings having chi-square greater than a fixed threshold and finding the MSS among substrings greater than a given length. We experimentally demonstrate the asymptotic behavior of the MSS on varying the string size and alphabet size. We also describe some applications of our algorithm on cryptology and real world data from finance and sports. Finally, we compare our technique with the existing heuristics for finding the MSS.

cs.DB↗

arXiv2012

Aggregate Skyline Join Queries: Skylines with Aggregate Operations over Multiple Relations

The multi-criteria decision making, which is possible with the advent of skyline queries, has been applied in many areas. Though most of the existing research is concerned with only a single relation, several real world applications require finding the skyline set of records over multiple relations. Consequently, the join operation over skylines where the preferences are local to each relation, has been proposed. In many of those cases, however, the join often involves performing aggregate operations among some of the attributes from the different relations. In this paper, we introduce such queries as "aggregate skyline join queries". Since the naive algorithm is impractical, we propose three algorithms to efficiently process such queries. The algorithms utilize certain properties of skyline sets, and processes the skylines as much as possible locally before computing the join. Experiments with real and synthetic datasets exhibit the practicality and scalability of the algorithms with respect to the cardinality and dimensionality of the relations.

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arXiv2011

High Q electromechanics with InAs nanowire quantum dots

In this report, we study electromechanical properties of a suspended InAs nanowire (NW) resonator. At low temperatures, the NW acts as the island of a single electron transistor (SET) and we observe a strong coupling between electrons and mechanical modes at resonance; the rate of electron tunneling is approximately 10 times the resonant frequency. Above and below the mechanical resonance, the magnitude of Coulomb peaks is different and we observe Fano resonance in conductance due to the interference between two contributions to potential of the SET. The quality factor ($Q$) of these devices is observed $\sim10^5$ at 100 mK.

cond-mat.mes-hall↗

arXiv2011

Polarization sensitive solar-blind detector based on a-plane AlGaN

We report polarization-sensitive solar-blind metal-semiconductor-metal UV photodetectors based on (11-20) a-plane AlGaN. The epilayer shows anisotropic optical properties confirmed by polarization-resolved transmission and photocurrent measurements, in good agreement with band structure calculations.

cond-mat.mtrl-sci↗

arXiv2011

Anisotropic structural and optical properties of a-plane (11-20) AlInN nearly-lattice-matched to GaN

We report epitaxial growth of a-plane (11-20) AlInN layers nearly-lattice-matched to GaN. Unlike for c-plane oriented epilayers, a-plane Al_{1-x}In_{x}N cannot be simultaneously lattice-matched to GaN in both in-plane directions. We study the influence of temperature on indium incorporation and obtain nearly-lattice-matched Al_{0.81}In_{0.19}N at a growth temperature of 760^{o}C. We outline a procedure to check in-plane lattice mismatch using high resolution x-ray diffraction, and evaluate the strain and critical thickness. Polarization-resolved optical transmission measurements of the Al_{0.81}In_{0.19}N epilayer reveal a difference in bandgap of ~140 meV between (electric field) E_parallel_c [0001]-axis and E_perpendicular_c conditions with room-temperature photoluminescence peaked at 3.38 eV strongly polarized with E_parallel_c, in good agreement with strain-dependent band-structure calculations.

cond-mat.mtrl-sci↗

arXiv2011

Tunable thermal conductivity in defect engineered nanowires at low temperatures

We measure the thermal conductivity ($κ$) of individual InAs nanowires (NWs), and find that it is 3 orders of magnitude smaller than the bulk value in the temperature range of 10 to 50 K. We argue that the low $κ$ arises from the strong localization of phonons in the random superlattice of twin-defects oriented perpendicular to the axis of the NW. We observe significant electronic contribution arising from the surface accumulation layer which gives rise to tunability of $κ$ with the application of electrostatic gate and magnetic field. Our devices and measurements of $κ$ at different carrier concentrations and magnetic field without introducing structural defects, offer a means to study new aspects of nanoscale thermal transport.

cond-mat.mes-hall↗

arXiv2011

Caching Stars in the Sky: A Semantic Caching Approach to Accelerate Skyline Queries

Multi-criteria decision making has been made possible with the advent of skyline queries. However, processing such queries for high dimensional datasets remains a time consuming task. Real-time applications are thus infeasible, especially for non-indexed skyline techniques where the datasets arrive online. In this paper, we propose a caching mechanism that uses the semantics of previous skyline queries to improve the processing time of a new query. In addition to exact queries, utilizing such special semantics allow accelerating related queries. We achieve this by generating partial result sets guaranteed to be in the skyline sets. We also propose an index structure for efficient organization of the cached queries. Experiments on synthetic and real datasets show the effectiveness and scalability of our proposed methods.

cs.DB↗

arXiv2011

Facile fabrication of lateral nanowire wrap-gate devices with improved performance

We present a simple fabrication technique for lateral nanowire wrap-gate devices with high capacitive coupling and field-effect mobility. Our process uses e-beam lithography with a single resist-spinning step, and does not require chemical etching. We measure, in the temperature range 1.5-250 K, a subthreshold slope of 5-54 mV/decade and mobility of 2800-2500 $cm^2/Vs$ -- significantly larger than previously reported lateral wrap-gate devices. At depletion, the barrier height due to the gated region is proportional to applied wrap-gate voltage.

cond-mat.mes-hall↗

arXiv2010

Distorted wurtzite unit cells: Determination of lattice parameters of non-polar a-plane AlGaN and estimation of solid phase Al content

Unlike c-plane nitrides, ``non-polar" nitrides grown in e.g. the a-plane or m-plane orientation encounter anisotropic in-plane strain due to the anisotropy in the lattice and thermal mismatch with the substrate or buffer layer. Such anisotropic strain results in a distortion of the wurtzite unit cell and creates difficulty in accurate determination of lattice parameters and solid phase group-III content (x_solid) in ternary alloys. In this paper we show that the lattice distortion is orthorhombic, and outline a relatively simple procedure for measurement of lattice parameters of non-polar group III-nitrides epilayers from high resolution x-ray diffraction measurements. We derive an approximate expression for x_solid taking into account the anisotropic strain. We illustrate this using data for a-plane AlGaN, where we measure the lattice parameters and estimate the solid phase Al content, and also show that this method is applicable for m-plane structures as well.

cond-mat.mtrl-sci↗

arXiv2010

Minimum Spanning Tree on Spatio-Temporal Networks

Given a spatio-temporal network (ST network) where edge properties vary with time, a time-sub-interval minimum spanning tree (TSMST) is a collection of minimum spanning trees of the ST network, where each tree is associated with a time interval. During this time interval, the total cost of tree is least among all the spanning trees. The TSMST problem aims to identify a collection of distinct minimum spanning trees and their respective time-sub-intervals under the constraint that the edge weight functions are piecewise linear. This is an important problem in ST network application domains such as wireless sensor networks (e.g., energy efficient routing). Computing TSMST is challenging because the ranking of candidate spanning trees is non-stationary over a given time interval. Existing methods such as dynamic graph algorithms and kinetic data structures assume separable edge weight functions. In contrast, we propose novel algorithms to find TSMST for large ST networks by accounting for both separable and non-separable piecewise linear edge weight functions. The algorithms are based on the ordering of edges in edge-order-intervals and intersection points of edge weight functions.

cs.DS↗

arXiv2010

Finding top-k similar pairs of objects annotated with terms from an ontology

With the growing focus on semantic searches and interpretations, an increasing number of standardized vocabularies and ontologies are being designed and used to describe data. We investigate the querying of objects described by a tree-structured ontology. Specifically, we consider the case of finding the top-k best pairs of objects that have been annotated with terms from such an ontology when the object descriptions are available only at runtime. We consider three distance measures. The first one defines the object distance as the minimum pairwise distance between the sets of terms describing them, and the second one defines the distance as the average pairwise term distance. The third and most useful distance measure, earth mover's distance, finds the best way of matching the terms and computes the distance corresponding to this best matching. We develop lower bounds that can be aggregated progressively and utilize them to speed up the search for top-k object pairs when the earth mover's distance is used. For the minimum pairwise distance, we devise an algorithm that runs in O(D + Tk log k) time, where D is the total information size and T is the total number of terms in the ontology. We also develop a novel best-first search strategy for the average pairwise distance that utilizes lower bounds generated in an ordered manner. Experiments on real and synthetic datasets demonstrate the practicality and scalability of our algorithms.

cs.DB↗

arXiv2010

Mining Statistically Significant Substrings Based on the Chi-Square Measure

Given the vast reservoirs of data stored worldwide, efficient mining of data from a large information store has emerged as a great challenge. Many databases like that of intrusion detection systems, web-click records, player statistics, texts, proteins etc., store strings or sequences. Searching for an unusual pattern within such long strings of data has emerged as a requirement for diverse applications. Given a string, the problem then is to identify the substrings that differs the most from the expected or normal behavior, i.e., the substrings that are statistically significant. In other words, these substrings are less likely to occur due to chance alone and may point to some interesting information or phenomenon that warrants further exploration. To this end, we use the chi-square measure. We propose two heuristics for retrieving the top-k substrings with the largest chi-square measure. We show that the algorithms outperform other competing algorithms in the runtime, while maintaining a high approximation ratio of more than 0.96.

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arXiv2010

Tuning mechanical modes and influence of charge screening in nanowire resonators

We probe electro-mechanical properties of InAs nanowire (diameter ~ 100 nm) resonators where the suspended nanowire (NW) is also the active channel of a field effect transistor (FET). We observe and explain the non-monotonic dispersion of the resonant frequency with DC gate voltage (VgDC). The effect of electronic screening on the properties of the resonator can be seen in the amplitude. We observe the mixing of mechanical modes with VgDC. We also experimentally probe and quantitatively explain the hysteretic non-linear properties, as a function of VgDC, of the resonator using the Duffing equation.

cond-mat.mes-hall↗

arXiv2009

On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces

Statistical distance measures have found wide applicability in information retrieval tasks that typically involve high dimensional datasets. In order to reduce the storage space and ensure efficient performance of queries, dimensionality reduction while preserving the inter-point similarity is highly desirable. In this paper, we investigate various statistical distance measures from the point of view of discovering low distortion embeddings into low-dimensional spaces. More specifically, we consider the Mahalanobis distance measure, the Bhattacharyya class of divergences and the Kullback-Leibler divergence. We present a dimensionality reduction method based on the Johnson-Lindenstrauss Lemma for the Mahalanobis measure that achieves arbitrarily low distortion. By using the Johnson-Lindenstrauss Lemma again, we further demonstrate that the Bhattacharyya distance admits dimensionality reduction with arbitrarily low additive error. We also examine the question of embeddability into metric spaces for these distance measures due to the availability of efficient indexing schemes on metric spaces. We provide explicit constructions of point sets under the Bhattacharyya and the Kullback-Leibler divergences whose embeddings into any metric space incur arbitrarily large distortions. We show that the lower bound presented for Bhattacharyya distance is nearly tight by providing an embedding that approaches the lower bound for relatively small dimensional datasets.

cs.CG↗

arXiv2009

Finding Significant Subregions in Large Image Databases

Images have become an important data source in many scientific and commercial domains. Analysis and exploration of image collections often requires the retrieval of the best subregions matching a given query. The support of such content-based retrieval requires not only the formulation of an appropriate scoring function for defining relevant subregions but also the design of new access methods that can scale to large databases. In this paper, we propose a solution to this problem of querying significant image subregions. We design a scoring scheme to measure the similarity of subregions. Our similarity measure extends to any image descriptor. All the images are tiled and each alignment of the query and a database image produces a tile score matrix. We show that the problem of finding the best connected subregion from this matrix is NP-hard and develop a dynamic programming heuristic. With this heuristic, we develop two index based scalable search strategies, TARS and SPARS, to query patterns in a large image repository. These strategies are general enough to work with other scoring schemes and heuristics. Experimental results on real image datasets show that TARS saves more than 87% query time on small queries, and SPARS saves up to 52% query time on large queries as compared to linear search. Qualitative tests on synthetic and real datasets achieve precision of more than 80%.

cs.DB↗

arXiv2009

Magnetotransport properties of individual InAs nanowires

We probe the magnetotransport properties of individual InAs nanowires in a field effect transistor geometry. In the low magnetic field regime we observe magnetoresistance that is well described by the weak localization (WL) description in diffusive conductors. The weak localization correction is modified to weak anti-localization (WAL) as the gate voltage is increased. We show that the gate voltage can be used to tune the phase coherence length ($l_ϕ$) and spin-orbit length ($l_{so}$) by a factor of $\sim$ 2. In the high field and low temperature regime we observe the mobility of devices can be modified significantly as a function of magnetic field. We argue that the role of skipping orbits and the nature of surface scattering is essential in understanding high field magnetotransport in nanowires.

cond-mat.mes-hall↗

arXiv2008

Photoluminescence from localized states in disordered indium nitride

Photoluminescence spectra from disordered InN were studied in very high magnetic fields. The samples had Gaussian spectra with low temperature emission peaks at 0.82 and 0.98eV respectively. The average spatial extent of the excitonic wave functions, inferred from the diamagnetic shift, is only 2-3nm. This shows that the recombination is from an ensemble of highly localized states within a landscape of a smooth (classical) disorder potential of strength of the order of 10meV. The anomalies in the temperature dependence of the photoluminescence peak and linewidth give further support to the picture of trapped photoexcited carriers.

cond-mat.mtrl-sci↗