989 resultados para sequential frequent pattern
Resumo:
Objective To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation. Design Retrospective audit. Setting The Northern Hospital, Melbourne, Australia. Participants 171,059 patients admitted between January 2001 and December 2006. Measurements The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit. Results The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation. Conclusion Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.
Resumo:
Extracting frequent subtrees from the tree structured data has important applications in Web mining. In this paper, we introduce a novel canonical form for rooted labelled unordered trees called the balanced-optimal-search canonical form (BOCF) that can handle the isomorphism problem efficiently. Using BOCF, we define a tree structure guided scheme based enumeration approach that systematically enumerates only the valid subtrees. Finally, we present the balanced optimal search tree miner (BOSTER) algorithm based on BOCF and the proposed enumeration approach, for finding frequent induced subtrees from a database of labelled rooted unordered trees. Experiments on the real datasets compare the efficiency of BOSTER over the two state-of-the-art algorithms for mining induced unordered subtrees, HybridTreeMiner and UNI3. The results are encouraging.
Resumo:
This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3.
Resumo:
Introduction Clinically, the Cobb angle method measures the overall scoliotic curve in the coronal plane but does not measure individual vertebra and disc wedging. The contributions of the vertebrae and discs in the growing scoliotic spine were measured to investigate coronal plane deformity progression with growth. Methods A 0.49mm isotropic 3D MRI technique was developed to investigate the level-by-level changes that occur in the growing spine of a group of Adolescent Idiopathic Scoliosis (AIS) patients, who received two to four sequential scans (spaced 3-12 months apart). The coronal plane wedge angles of each vertebra and disc in the major curve were measured to capture any changes that occurred during their adolescent growth phase. Results Seventeen patients had at least two scans. Mean patient age was 12.9 years (SD 1.5 years). Sixteen were classified as right-sided major thoracic Lenke Type 1 (one left sided). Mean standing Cobb angle at initial presentation was 31° (SD 12°). Six received two scans, nine three scans and two four scans, with 65% showing a Cobb angle progression of 5° or more between scans. Overall, there was no clear pattern of deformity progression of individual vertebrae and discs, nor between patients who progressed and those who didn’t. There were measurable changes in the wedging of the vertebrae and discs in all patients. In sequential scans, change in direction of wedging was also seen. In several patients there was reverse wedging in the discs that counteracted increased wedging of the vertebrae such that no change in overall Cobb angle was seen. Conclusion Sequential MRI data showed complex patterns of deformity progression. Changes to the wedging of individual vertebrae and discs may occur in patients who have no increase in Cobb angle measure; the Cobb method alone may be insufficient to capture the complex mechanisms of deformity progression.
Resumo:
INTRODUCTION. Clinically, the Cobb angle method measures the overall scoliotic curve in the coronal plane but does not measure individual vertebra and disc wedging. The contributions of the vertebrae and discs in the growing scoliotic spine were measured to investigate coronal plane deformity progression with growth. METHODS. A 0.49mm isotropic 3D MRI technique was developed to investigate the level-by-level changes that occur in the growing spine of a group of Adolescent Idiopathic Scoliosis (AIS) patients, who received two to four sequential scans (spaced 3-12 months apart). The coronal plane wedge angles of each vertebra and disc in the major curve were measured to capture any changes that occurred during their adolescent growth phase. RESULTS. Seventeen patients had at least two scans. Mean patient age was 12.9 years (SD 1.5 years). Sixteen were classified as right-sided major thoracic Lenke Type 1 (one left sided). Mean standing Cobb angle at initial presentation was 31° (SD 12°). Six received two scans, nine three scans and two four scans, with 65% showing a Cobb angle progression of 5° or more between scans. Overall, there was no clear pattern of deformity progression of individual vertebrae and discs, nor between patients who progressed and those who didn’t. There were measurable changes in the wedging of the vertebrae and discs in all patients. In sequential scans, change in direction of wedging was also seen. In several patients there was reverse wedging in the discs that counteracted increased wedging of the vertebrae such that no change in overall Cobb angle was seen. CONCLUSION. Sequential MRI data showed complex patterns of deformity progression. Changes to the wedging of individual vertebrae and discs may occur in patients who have no increase in Cobb angle measure; the Cobb method alone may be insufficient to capture the complex mechanisms of deformity progression.
Resumo:
A simple sequential thinning algorithm for peeling off pixels along contours is described. An adaptive algorithm obtained by incorporating shape adaptivity into this sequential process is also given. The distortions in the skeleton at the right-angle and acute-angle corners are minimized in the adaptive algorithm. The asymmetry of the skeleton, which is a characteristic of sequential algorithm, and is due to the presence of T-corners in some of the even-thickness pattern is eliminated. The performance (in terms of time requirements and shape preservation) is compared with that of a modern thinning algorithm.
Resumo:
Sequential firings with fixed time delays are frequently observed in simultaneous recordings from multiple neurons. Such temporal patterns are potentially indicative of underlying microcircuits and it is important to know when a repeatedly occurring pattern is statistically significant. These sequences are typically identified through correlation counts. In this paper we present a method for assessing the significance of such correlations. We specify the null hypothesis in terms of a bound on the conditional probabilities that characterize the influence of one neuron on another. This method of testing significance is more general than the currently available methods since under our null hypothesis we do not assume that the spiking processes of different neurons are independent. The structure of our null hypothesis also allows us to rank order the detected patterns. We demonstrate our method on simulated spike trains.
Resumo:
Banana bunchy top virus (BBTV; family Nanoviridae, genus Babuvirus) is a multi-component single-stranded DNA virus, which infects banana plants in many regions of the world, often resulting in large-scale crop losses. Weanalyzed 171 banana leaf samples from fourteen countries and recovered, cloned, and sequenced 855 complete BBTV components including ninety-four full genomes. Importantly, full genomes were determined from eight countries, where previously no full genomes were available (Samoa, Burundi, Republic of Congo, Democratic Republic of Congo, Egypt, Indonesia, the Philippines, and the USA [HI]). Accounting for recombination and genome component reassortment, we examined the geographic structuring of global BBTV populations to reveal that BBTV likely originated in Southeast Asia, that the current global hotspots of BBTV diversity are Southeast Asia/Far East and India, and that BBTV populations circulating elsewhere in the world have all potentially originated from infrequent introductions. Most importantly, we find that rather than the current global BBTV distribution being due to increases in human-mediated movements of bananas over the past few decades, it is more consistent with a pattern of infrequent introductions of the virus to different parts of the world over the past 1,000 years.
Resumo:
"In this study, for the first time, two distinct genetic lineages of Puumala virus (PUUV) were found within a small sampling area and within a single host genetic lineage (Ural mtDNA) at Pallasjarvi, northern Finland. Lung tissue samples of 171 bank voles (Myodes glareolus) trapped in September 1998 were screened for the presence of PUUV nucleocapsid antigen and 25 were found to be positive. Partial sequences of the PUUV small (S), medium (M) and large (L) genome segments were recovered from these samples using RT-PCR. Phylogenetic analysis revealed two genetic groups of PUUV sequences that belonged to the Finnish and north Scandinavian lineages. This presented a unique opportunity to study inter-lineage reassortment in PUUV; indeed, 32% of the studied bank voles appeared to carry reassortant virus genomes. Thus, the frequency of inter-lineage reassortment in PUUV was comparable to that of intra-lineage reassortment observed previously (Razzauti, M., Plyusnina, A., Henttonen, H. & Plyusnin, A. (2008). J Gen Virol 89, 1649-1660). Of six possible reassortant S/M/L combinations, only two were found at Pallasjarvi and, notably, in all reassortants, both S and L segments originated from the same genetic lineage, suggesting a non-random pattern for the reassortment. These findings are discussed in connection to PUUV evolution in Fermoscandia."
Resumo:
How the brain maintains perceptual continuity across eye movements that yield discontinuous snapshots of the world is still poorly understood. In this study, we adapted a framework from the dual-task paradigm, well suited to reveal bottlenecks in mental processing, to study how information is processed across sequential saccades. The pattern of RTs allowed us to distinguish among three forms of trans-saccadic processing (no trans-saccadic processing, trans-saccadic visual processing and trans-saccadic visual processing and saccade planning models). Using a cued double-step saccade task, we show that even though saccade execution is a processing bottleneck, limiting access to incoming visual information, partial visual and motor processing that occur prior to saccade execution is used to guide the next eye movement. These results provide insights into how the oculomotor system is designed to process information across multiple fixations that occur during natural scanning.
Resumo:
In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.
Resumo:
Background: Tuberculosis (TB) is an enduring health problem worldwide and the emerging threat of multidrug resistant (MDR) TB and extensively drug resistant (XDR) TB is of particular concern. A better understanding of biomarkers associated with TB will aid to guide the development of better targets for TB diagnosis and for the development of improved TB vaccines. Methods: Recombinant proteins (n = 7) and peptide pools (n = 14) from M. tuberculosis (M.tb) antigens associated with M.tb pathogenicity, modification of cell lipids or cellular metabolism, were used to compare T cell immune responses defined by IFN-gamma production using a whole blood assay (WBA) from i) patients with TB, ii) individuals recovered from TB and iii) individuals exposed to TB without evidence of clinical TB infection from Minsk, Belarus. Results: We identified differences in M.tb target peptide recognition between the test groups, i.e. a frequent recognition of antigens associated with lipid metabolism, e.g. cyclopropane fatty acyl phospholipid synthase. The pattern of peptide recognition was broader in blood from healthy individuals and those recovered from TB as compared to individuals suffering from pulmonary TB. Detection of biologically relevant M.tb targets was confirmed by staining for intracellular cytokines (IL-2, TNF-alpha and IFN-gamma) in T cells from non-human primates (NHPs) after BCG vaccination. Conclusions: PBMCs from healthy individuals and those recovered from TB recognized a broader spectrum of M.tb antigens as compared to patients with TB. The nature of the pattern recognition of a broad panel of M.tb antigens will devise better strategies to identify improved diagnostics gauging previous exposure to M.tb; it may also guide the development of improved TB-vaccines.
Resumo:
This paper presents a method to generate new melodies, based on conserving the semiotic structure of a template piece. A pattern discovery algorithm is applied to a template piece to extract significant segments: those that are repeated and those that are transposed in the piece. Two strategies are combined to describe the semiotic coherence structure of the template piece: inter-segment coherence and intra-segment coherence. Once the structure is described it is used as a template for new musical content that is generated using a statistical model created from a corpus of bertso melodies and iteratively improved using a stochastic optimization method. Results show that the method presented here effectively describes a coherence structure of a piece by discovering repetition and transposition relations between segments, and also by representing the relations among notes within the segments. For bertso generation the method correctly conserves all intra and inter-segment coherence of the template, and the optimization method produces coherent generated melodies.
Resumo:
The problem of discovering frequent poly-regions (i.e. regions of high occurrence of a set of items or patterns of a given alphabet) in a sequence is studied, and three efficient approaches are proposed to solve it. The first one is entropy-based and applies a recursive segmentation technique that produces a set of candidate segments which may potentially lead to a poly-region. The key idea of the second approach is the use of a set of sliding windows over the sequence. Each sliding window covers a sequence segment and keeps a set of statistics that mainly include the number of occurrences of each item or pattern in that segment. Combining these statistics efficiently yields the complete set of poly-regions in the given sequence. The third approach applies a technique based on the majority vote, achieving linear running time with a minimal number of false negatives. After identifying the poly-regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a poly-region). An efficient algorithm for mining frequent arrangements of intervals is applied to the converted sequence to discover frequently occurring arrangements of poly-regions in different parts of DNA, including coding regions. The proposed algorithms are tested on various DNA sequences producing results of significant biological meaning.
Resumo:
The system presented here is based on neurophysiological and electrophysiological data. It computes three types of increasingly integrated temporal and probability contexts, in a bottom-up mode. To each of these contexts corresponds an increasingly specific top-down priming effect on lower processing stages, mostly pattern recognition and discrimination. Contextual learning of time intervals, events' temporal order or sequential dependencies and events' prior probability results from the delivery of large stimuli sequences. This learning gives rise to emergent properties which closely match the experimental data.