Hybrid Index Research Articles

Social-aware spatial keyword top-k group query

With the increasing popularity of location-based social networking services, information in social networks has become an important basis for analyzing user preferences. However, the existing spatial keyword group query only focuses on the distance constraint between the user groups, and ignores the social relationship between the user and his friends, which may affect the query results. Therefore, in order to meet the diverse query needs of user groups and improve user satisfaction based on information in social networks, this paper proposes a social-aware spatial keyword top-k group query problem. This problem aims to retrieve a set of k groups of POI objects that satisfy the preferences of multiple users, taking into account spatial proximity, social relevance, and keyword constraints. To solve this problem, we first design a rank function to measure the correlation between the query set and the candidate set. Next, in order to improve the query efficiency, we develop a novel hybrid index structure, SAIR-tree, which comprehensively considers the attributes of social, spatial, and textual. Then, we propose an approximate algorithm and an exact algorithm, combining with the pruning strategy, can efficiently search the top-k result set. Finally, experiments on real dataset confirm the efficiency and accuracy of the proposed algorithms.

Fog-Computing-Based Approximate Spatial Keyword Queries With Numeric Attributes in IoV

Due to the popularity of onboard geographic devices, a large number of spatial–textual objects are generated in the Internet of Vehicles (IoV). This development calls for approximate spatial keyword queries with numeric attributes in IoV (A2SKIV), which takes into account the locations, textual descriptions, and numeric attributes of spatial–textual objects. Considering large amounts of objects involved in the query processing, this article comes up with the idea of utilizing vehicles as fog-computing resource and proposes the network structure called FCV, and based on which the fog-based top- $k~\text{A}^{2}$ SKIV query is explored and formulated. In order to effectively support network distance pruning, textual semantic pruning, and numerical attribute pruning, simultaneously, a two-level spatial–textual hybrid index STAG-tree is designed. Based on STAG-tree, an efficient top- $k~\text{A}^{2}$ SKIV query processing algorithm is presented. The simulation results show that our STAG-based approach is about $1.87\times $ ( $17.1\times $ , resp.) faster in search time than the compared ILM (DBM, resp.) method, and our approach is scalable.

Asymptotical Stability of Logic Dynamical Systems With Random Impulsive Disturbances

This article presents an investigation of the asymptotical set stability (ASS) of logic dynamical systems (LDSs) with impulsive disturbances at random instants. Unlike ordinary probabilistic Boolean networks, such an impulsive LDS is not Markovian in general. In this article, an impulsive LDS is described by using a hybrid index model and the sequence of intervals between adjacent impulsive instants is assumed to be independent and identically distributed. Under this assumption, the subsequence of a solution obtained by sampling at impulsive instants is a Markov chain. The initial distribution, the transition probability matrix, and the reachable set of the Markovian subsequence are calculated. Calculations of different invariant subsets are discussed and a necessary and sufficient condition for the convergence of finite Markov chains to subsets is obtained. Based on these results, necessary conditions for the ASS of impulsive LDSs in the hybrid and time domains, respectively, are obtained. In addition, we prove that the necessary conditions become sufficient if the impulsive intervals and the initial impulsive instant are with bounded expectations and variances. An example is provided to show the application of the proposed results to node synchronization of logic dynamical networks.

Efficient Geo-Textual Hybrid Indexing Techniques for Moving Objects and Queries

Advancements of various Geographic Information Technologies have resulted in huge growth in Geo-Textual data. Many Indexing and searching algorithms are developed to handle this Geo-Textual data which contains spatial, textual and temporal information. In past, Indexing and searching algorithms are developed for the applications in which the object trajectory or velocity vector is known in advance and hence we can predict the future position of the objects. There are real time applications like emergency management systems, traffic monitoring, where the objects movements are unpredictable and hence future position of the objects cannot be predicted. Techniques are required to answer the geo-textual kNN query where the velocity vectors or trajectories of moving and moving queries are not known. In case of moving objects, capturing current position of the object and maintaining spatial index optimally is very much essential. The hybrid indexing techniques used earlier are based on R-tree spatial index. The nodes of the R-tree index structure are split or merged to maintain the locations of continuously moving objects, increasing the maintenance cost as compared to the grid index. In this paper a solution is proposed for creating and maintaining hybrid index for moving objects and queries based on grid and inverted list hybrid indexing techniques. The method is also proposed for finding Geo-Textual nearest neighbours for static and moving queries using hybrid index and conceptual partitioning of the grid. The overall gain reported by the experimental work using hybrid index over the non- hybrid index is 30 to 40 percent depending on the grid size chosen for mapping the data space and on the parameters of queries.

Genodive version 3.0: Easy-to-use software for the analysis of genetic data of diploids and polyploids.

genodive version 3.0 is a user‐friendly program for the analysis of population genetic data. This version presents a major update from the previous version and now offers a wide spectrum of different types of analyses. genodive has an intuitive graphical user interface that allows direct manipulation of the data through transformation, imputation of missing data, and exclusion and inclusion of individuals, population and/or loci. Furthermore, genodive seamlessly supports 15 different file formats for importing or exporting data from or to other programs. One major feature of genodive is that it supports both diploid and polyploid data, up to octaploidy (2n = 8x) for some analyses, but up to hexadecaploidy (2n = 16x) for other analyses. The different types of analyses offered by genodive include multiple statistics for estimating population differentiation (φ ST, F ST, FʹST, G ST, GʹST, GʹʹST, D est, R ST, ρ), analysis of molecular variance‐based K‐means clustering, Hardy–Weinberg equilibrium, hybrid index, population assignment, clone assignment, Mantel test, Spatial Autocorrelation, 23 ways of calculating genetic distances, and both principal components and principal coordinates analyses. A unique feature of genodive is that it can also open data sets with nongenetic variables, for example environmental data or geographical coordinates that can be included in the analysis. In addition, genodive makes it possible to run several external programs (lfmm, structure, instruct and vegan) directly from its own user interface, avoiding the need for data reformatting and use of the command line. genodive is available for computers running Mac OS X 10.7 or higher and can be downloaded freely from: http://www.patrickmeirmans.com/software.

Intolerance of Uncertainty and Social Anxiety while Utilizing a Hybrid Approach to Symptom Assessment

Intolerance of uncertainty (IU) is a dispositional characteristic wherein individuals interpret uncertainty in a negative fashion. No research has investigated the relationship between the IU subfactors, inhibitory (IU-I) and prospective (IU-P) IU, and symptoms of social anxiety disorder while utilizing a hybrid approach of symptom assessment. The current study examined the associations between IU-I and IU-P and social anxiety while utilizing a hybrid index of social anxiety, the Multidimensional Assessment of Social Anxiety (MASA). Participants (N = 684) were recruited from an outpatient psychiatric clinic. Baseline anxiety was included as a covariate for all analyses. Results found that both IU subscales were significantly associated with the MASA anhedonia and physiological arousal and avoidance subfactors. IU-I displayed specificity with the MASA functional impairment, coping with substances, and behavioral avoidance subscales. IU-P was associated with the MASA thought avoidance subfactor at trend level, whereas IU-I was not. Clinical implications and future directions are discussed.

Using aerial canopy data from UAVs to measure the effects of neighbourhood competition on individual tree growth

Unmanned aerial vehicles (UAVs) have opened new opportunities for measuring 3D canopy structure from aerial imagery. Image data collected with a UAV can be processed to generate detailed information on local canopy structure around an individual tree, which may be a useful proxy for the amount of competition that tree experiences from its neighbours. Structural indices of competition traditionally have been derived from ground-based plot data, and it is not clear whether aerial canopy data from a UAV are as effective as ground data for modelling the effects of competition on individual-tree growth. Here, we compare the relative performance of four ground-based competition indices derived from plot data, five canopy-based competition indices derived from UAV data, and one hybrid index that uses both data types, for predicting the radial growth of two northern tree species (white spruce, lodgepole pine). Ground-based and canopy-based competition indices were both represented among the top-performing models for each species, but no single index was unambiguously favoured over all others. Of the ten competition indices we considered, the mean canopy height within 15 m of a subject tree had the strongest performance across both species, including the best performance for lodgepole pine (R2 = 0.29) and third-best performance for white spruce (R2 = 0.42). Models with mean canopy height also revealed interactions between competition and soil moisture, with growth reductions from competition limited to dry sites for white spruce and to mesic sites for lodgepole pine. Although we did not identify a systematic advantage for either ground-based or canopy-based competition indices, indices that were centred on the subject tree tended to perform better than plot-based indices that were not. Overall, our comparison showed that canopy-based metrics such as mean canopy height can be at least as effective as traditional ground-based metrics for measuring the effects of local competition on tree growth. As a new research tool in forest ecology, UAVs thus offer a valuable approach for measuring neighbourhood crowding and its effects on the performance of individual trees.

Complex patterns of differentiation and gene flow underly the divergence of aposematic phenotypes in Oophaga poison frogs.

Hybridization and introgression can have complex consequences for both species evolution and conservation. Here, we investigated the origin and characteristics of a putative hybrid zone between two South American poison dart frog species, Oophaga anchicayensis and the critically endangered Oophaga lehmanni, which are heavily sought after on the illegal pet market. Using a combination of phenotypic (49 traits) and genomic (ddRADseq) data, we found that the putative hybrids are morphologically distinct from their parental species and confirmed genomic signatures of admixture in these populations. Several lines of evidence (hybrid indices, interspecific hybrid heterozygosity, genomic clines, comparisons with simulated hybrids and demographic modelling) support the conclusion that these populations are not comprised of early-generation hybrids and thus, they probably did not arise as a result of illegal translocations associated with wildlife trafficking. Instead, they probably represent an independent lineage which has persisted through isolation and has only relatively recently re-established gene flow with both parental species. Furthermore, we detected signals of differential introgression from parental species into these hybrid populations which suggest relaxed stabilizing selection on these aposematic colour morphs, potentially via context-dependent female choice. These populations thus provide a fascinating window into the role of hybridization, isolation and female choice in the diversification of South American poison dart frogs. In addition, our results underline the importance of landscape conservation measures to protect, not only known localities of nominal species, but also the phenotypic and genomic variation harbored by admixed lineages which represent crucial repositories for the impressive diversity in this system.

3\u2019Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

BackgroundThe advent of Next Generation Sequencing has allowed transcriptomes to be profiled with unprecedented accuracy, but the high costs of full-length mRNA sequencing have posed a limit on the accessibility and scalability of the technology. To address this, we developed 3’Pool-seq: a simple, cost-effective, and scalable RNA-seq method that focuses sequencing to the 3′-end of mRNA. We drew from aspects of SMART-seq, Drop-seq, and TruSeq to implement an easy workflow, and optimized parameters such as input RNA concentrations, tagmentation conditions, and read depth specifically for bulk-RNA.ResultsThorough optimization resulted in a protocol that takes less than 12 h to perform, does not require custom sequencing primers or instrumentation, and cuts over 90% of the costs associated with TruSeq, while still achieving accurate gene expression quantification (Pearson’s correlation coefficient with ERCC theoretical concentration r = 0.96) and differential gene detection (ROC analysis of 3’Pool-seq compared to TruSeq AUC = 0.921). The 3’Pool-seq dual indexing scheme was further adapted for a 96-well plate format, and ERCC spike-ins were used to correct for potential row or column pooling effects. Transcriptional profiling of troglitazone and pioglitazone treatments at multiple doses and time points in HepG2 cells was then used to show how 3’Pool-seq could distinguish the two molecules based on their molecular signatures.Conclusions3’Pool-seq can accurately detect gene expression at a level that is on par with TruSeq, at one tenth of the total cost. Furthermore, its unprecedented TruSeq/Nextera hybrid indexing scheme and streamlined workflow can be applied in several different formats, including 96-well plates, which allows users to thoroughly evaluate biological systems under several conditions and timepoints. Care must be taken regarding experimental design and plate layout such that potential pooling effects can be accounted for and corrected. Lastly, further studies using multiple sets of ERCC spike-ins may be used to simulate differential gene expression in a system with known ground-state values.

Reverse Spatial Visual Top-$k$ Query

With the wide application of mobile Internet techniques an location-based services (LBS), massive multimedia data with geo-tags has been generated and collected. In this paper, we investigate a novel type of spatial query problem, named reverse spatial visual top- $k$ query (RSVQ k ) that aims to retrieve a set of geo-images that have the query as one of the most relevant geo-images in both geographical proximity and visual similarity. Existing approaches for reverse top- $k$ queries are not suitable to address this problem because they cannot effectively process unstructured data, such as image. To this end, firstly we propose the definition of RSVQ k problem and introduce the similarity measurement. A novel hybrid index, named VR2-Tree is designed, which is a combination of visual representation of geo-image and R-Tree. Besides, an extension of VR2-Tree, called CVR2-Tree is introduced and then we discuss the calculation of lower/upper bound, and then propose the optimization technique via CVR2-Tree for further pruning. In addition, a search algorithm named RSVQ k algorithm is developed to support the efficient RSVQ k query. Comprehensive experiments are conducted on four geo-image datasets, and the results illustrate that our approach can address the RSVQ k problem effectively and efficiently.

Constructing Effective Caches of Shortest Path Queries on Road Networks

How to effectively utilize caching technology to support high-performance shortest path queries on road networks has become an important research problem since the popularization of location-based services. Most of the existing methods design a statistical model to construct the cache with the shortest paths, and mainly consider the related query frequency obtained from the historical query logs. As a result, the paths in the cache may be concentrated in a few hot-spot areas of the road network, such as the prosperous areas of a city. Additionally, queries from remote areas may never be hit in the cache, which results in the cache hit ratio is not fully optimized. To address this problem, we define an effective model to quantify the effect of cached shortest paths; the model not only considers the related query frequency in the log but also the coverage of the paths on the road network. Then, we propose an efficient cache construction method to select the cached shortest paths from the query log. Furthermore, we design a hybrid index for the shortest paths in the cache, so that the efficiency of shortest path querying is significantly improved. Finally, we conduct comprehensive experimental studies on different datasets to verify that the cache hit ratio is greatly improved by using the proposed cache construction approaches.

What nature separated, and human joined together: About a spontaneous hybridization between two allopatric dogwood species (Cornus controversa and C. alternifolia).

In this study, possible hybridization between two allopatric species, Cornus controversa and Cornus alternifolia, was explored using molecular and morphological approaches. Scanning electron microscope analyses of the adaxial and the abaxial leaf surfaces yielded a few new not yet described characters typical for the particular species and intermediate for hybrids. With the use of 14 Random Amplified Polymorphic DNA and 5 Amplified Fragment Length Polymorphism primer combinations, 44 fragments species specific to C. controversa and 51 species specific to C. alternifolia were obtained. Most of these bands were also found in putative hybrids. All clustering analyses based on binary data combined from both methods confirmed a separate and intermediate status of the hybrids. Hybrid index estimates for hybrids C1-C5 indicated that all were the first generation of offspring (F1). Chloroplast intergenic spacers (trnF-trnL and psbC-trnS) were used to infer the hybridization direction. Based on the assumption of maternal inheritance of chloroplast DNA, C. controversa seems to be the maternal parent of the hybrid. Internal transcribed spacer sequences of the five hybrids analyzed here indicated higher similarity with the sequences of C. controversa (all shared the majority of its single nucleotide polymorphisms). Sequence analysis of PI-like genes fully confirmed the hybrid origin of C1-C5 hybrids. Our results also showed that two specimens in the C. alternifolia group, A1 and A3, are not free of introgression. They are probably repeated backcrosses toward C. alternifolia. Furthermore, molecular data seem to point not only to unidirectional introgression toward C. controversa (the presence of hybrids) but to bidirectional introgression as well, since the presence of markers specific for C. controversa in the profiles of C. alternifolia specimen A3 was observed.

Is embryo abortion a post-zygotic barrier to gene flow between Littorina ecotypes?

Genetic incompatibilities contribute to reproductive isolation between many diverging populations, but it is still unclear to what extent they play a role if divergence happens with gene flow. In contact zones between the "Crab" and "Wave" ecotypes of the snail Littorina saxatilis, divergent selection forms strong barriers to gene flow, while the role of post‐zygotic barriers due to selection against hybrids remains unclear. High embryo abortion rates in this species could indicate the presence of such barriers. Post‐zygotic barriers might include genetic incompatibilities (e.g. Dobzhansky–Muller incompatibilities) but also maladaptation, both expected to be most pronounced in contact zones. In addition, embryo abortion might reflect physiological stress on females and embryos independent of any genetic stress. We examined all embryos of >500 females sampled outside and inside contact zones of three populations in Sweden. Females' clutch size ranged from 0 to 1,011 embryos (mean 130 ± 123), and abortion rates varied between 0% and 100% (mean 12%). We described female genotypes by using a hybrid index based on hundreds of SNPs differentiated between ecotypes with which we characterized female genotypes. We also calculated female SNP heterozygosity and inversion karyotype. Clutch size did not vary with female hybrid index, and abortion rates were only weakly related to hybrid index in two sites but not at all in a third site. No additional variation in abortion rate was explained by female SNP heterozygosity, but increased female inversion heterozygosity added slightly to increased abortion. Our results show only weak and probably biologically insignificant post‐zygotic barriers contributing to ecotype divergence, and the high and variable abortion rates were marginally, if at all, explained by hybrid index of females.

OFDM With Hybrid Number and Index Modulation

A novel transmission scheme is introduced for efficient data transmission by conveying additional information bits through jointly changing the index and number of active subcarriers within each orthogonal frequency division multiplexing (OFDM) subblock. The proposed scheme is different from the conventional OFDM-subcarrier number modulation (OFDM-SNM) and OFDM-index modulation (OFDM-IM), in which data bits are transmitted using either number or index of active subcarriers. The proposed modulation technique offers superior spectral and energy efficiency compared to its counterparts OFDM-SNM and OFDM-IM, especially at low modulation orders such as binary phase shift keying (BPSK) that can provide high reliability and low complexity, making it suitable for Internet of Things (IoT) applications that require better spectral and energy efficiency while enjoying high reliability and low complexity. Bit error rate (BER) performance analysis is provided for the proposed scheme, and Monte Carlo simulations are presented to prove the consistency of simulated BER with the analyzed one.

Hybrid Switch of Correlation and Squeezing Using Resonant and Off-Resonant Excitation Spectrum in Nitrogen-Vacancy Center Diamond

Optical hybrid communication is one of the key fields of quantum communications, where scientists are focusing to integrate classical and quantum system as single hybrid system. In this regard, we realized optical hybrid switch using second-order fluorescence (FL) and spontaneous parametric four-wave mixing (SPFWM). The hybrid signal contains Stokes and the FL signal which can be distinguished using power of incident beam. In addition, we investigate the resonant and off-resonant excitation spectrum of negatively charged Nitrogen-vacancy (NV−) center in diamond. The hybrid switch is realized by results obtained in time domain and intensity noise correlation. The optical hybrid switch can be controlled by power of incident beams. The hybrid index and temporal width contrast of the hybrid switch are about 4 and 90%, respectively.

An Unsupervised Learning Framework for Track Quality Index and Safety

Rail track geometry defect remains a primary cause of train accidents in the USA. With over $1 billion lost annually to geometry-related accidents, there is an urgent need to re-assess the analysis and treatment of geometry defects. The development of track quality index (TQI) takes a contracted view of track assessment by focusing only on quality without any safety consideration. Track geometry safety limits are set by Federal Railroad Administration based on raw track geometry data. Since different variations of track geometry parameters exist, there is a skepticism about the effectiveness of the current bipartite analytical approach of track quality and safety. These results into two maintenance regimes: regular and spot maintenance. This study aims to create a framework through which a hybrid index that combines both safety and quality can effectively eliminate costly spot maintenance practices. This index would be used to create a data-driven maintenance scheme that maximizes the time between two maintenance cycles and minimizes disruptions. This technical note describes the proposed framework for creating such an index using unsupervised machine learning.

Operational risk assessment of railway train based on type-2 intuitionistic fuzzy set and dynamic VIKOR approach

This paper is devoted to applying fuzzy risk-ranking analysis for the railway train operational risk assessment. Specifically, a new risk-ranking approach of dynamic VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) combined with Type-2 intuitionistic fuzzy set (Type-2 IFS) theory is proposed under different stages, which can be better employed to rank the risk of system components considering the calculation uncertainty, expert preference, and information indeterminacy based on the hybrid index system of quantitative and qualitative information. A specific case is performed to validate the proposed approach. Based on the results, a comparative analysis between the proposed approach and the static risk assessment is presented, which shows the effectiveness and feasibility of the proposed approach.

Fully-sensitive seed finding in sequence graphs using a hybrid index.

MotivationSequence graphs are versatile data structures that are, for instance, able to represent the genetic variation found in a population and to facilitate genome assembly. Read mapping to sequence graphs constitutes an important step for many applications and is usually done by first finding exact seed matches, which are then extended by alignment. Existing methods for finding seed hits prune the graph in complex regions, leading to a loss of information especially in highly polymorphic regions of the genome. While such complex graph structures can indeed lead to a combinatorial explosion of possible alleles, the query set of reads from a diploid individual realizes only two alleles per locus—a property that is not exploited by extant methods.ResultsWe present the Pan-genome Seed Index (PSI), a fully-sensitive hybrid method for seed finding, which takes full advantage of this property by combining an index over selected paths in the graph with an index over the query reads. This enables PSI to find all seeds while eliminating the need to prune the graph. We demonstrate its performance with different parameter settings on both simulated data and on a whole human genome graph constructed from variants in the 1000 Genome Project dataset. On this graph, PSI outperforms GCSA2 in terms of index size, query time and sensitivity.Availability and implementationThe C++ implementation is publicly available at: https://github.com/cartoonist/psi.

Stability analysis of state‐triggered impulsive boolean networks based on a hybrid index model

AbstractSeveral real processes, such as gene expression, operate on very different timescales. This paper suggests a hybrid index model for discrete‐time impulsive systems exhibiting both macro‐ and micro‐timescale behaviors, and applies it to a stability study of state‐triggered impulsive Boolean networks (IBNs). The model conveniently characterizes the instantaneousness of jumping and essentially differs from the conventional switched‐system model. A necessary and sufficient condition for forward completeness (a basic problem in state‐triggered IBNs) is also obtained. The necessary and sufficient conditions for stability and set stability in the time and hybrid domains are derived by a quotient mapping method and a k‐domain method, respectively. The proposal results are demonstrated in examples.

Index model based on top-down greedy splitting R-tree and three-dimensional quadtree for massive point cloud management

With the rapid development of three-dimensional (3-D) laser scanners, the correspondent point cloud accuracy and density are continuously improving. However, the point data volume becomes larger and larger, which brings new challenges for the point cloud data real-time processing on personal computers. To meet the managing requirement for real-time point cloud processing, we proposed a hybrid index model characterized by top-down greedy splitting (TGS) R-tree and 3-D quadtree, aiming at the balance improvement and the high index query efficiency. First, the large-scale point cloud data are divided into grids based on their spatial distribution, and then, the proposed TGS R-tree algorithm is applied to organize these grids. Second, a 3-D quadtree local index model is developed to manage local points in each grid. Experiments of five point cloud data scenarios are conducted to evaluate the proposed method, and the results show that the proposed model can meet the efficiency need of various 3-D point cloud managements, especially for those mainly distributed in XY plane, including the airborne LiDAR point cloud.