Pattern Matching Algorithm Research Articles

GRASPm: an efficient algorithm for exact pattern-matching in genomic sequences

In this paper, we propose Genomic-oriented Rapid Algorithm for String Pattern-match (GRASPm), an algorithm centred on overlapped 2-grams analysis, which introduces a novel filtering heuristic - the compatibility rule - achieving significant efficiency gain. GRASPm's foundations rely especially on a wide searching window having the central duplet as reference for fast filtering of multiple alignments. Subsequently, superfluous detailed verifications are summarily avoided by filtering the incompatible alignments using the idcd (involving duplet of central duplet) concept combined with pre-processed conditions, allowing fast parallel testing for multiple alignments. Comparative performance analysis, using diverse genomic data, shows that GRASPm is faster than its competitors.

Visual Navigation For Autonomous System For Detection And Neutralisation Of Non-Metal Mines

Abstract An idea of autonomous mobile platform for land mines detection and destruction is introduced. A visual navigation system with a simple pattern matching algorithm was proposed. A CCD camera is the system main sensor for image acquisition. A Scene Matching Area Correlation (SMAC) method based on a cross correlation technique is implemented for image processing. The system was tested both in off-line simulations and on-board of a land vehicle. The efficiency of the signal processing algorithm during the field tests confirmed efficiency of the methods developed for determination of vehicle position and velocity. A visual navigation system based on simple image processing techniques may be applied on board mobile vehicles in an autonomous way or as a component of integrated navigation system.

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

AbstractMean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.

Fast Template Matching Based on Normalized Cross Correlation With Adaptive Multilevel Winner Update

In this paper, we propose a fast pattern matching algorithm based on the normalized cross correlation (NCC) criterion by combining adaptive multilevel partition with the winner update scheme to achieve very efficient search. This winner update scheme is applied in conjunction with an upper bound for the cross correlation derived from Cauchy-Schwarz inequality. To apply the winner update scheme in an efficient way, we partition the summation of cross correlation into different levels with the partition order determined by the gradient energies of the partitioned regions in the template. Thus, this winner update scheme in conjunction with the upper bound for NCC can be employed to skip unnecessary calculation. Experimental results show the proposed algorithm is very efficient for image matching under different lighting conditions.

Abstract 707: Nonuniformity of Left Ventricular Apical-to-Basal Diastolic Lengthening in Patients with Hypertrophic Nonobstructive Cardiomyopathy

Quantification of left ventricular (LV) apex-to-base dispersion has been feasible with two-dimensional echocardiographic tissue tracking system (2DTT, Hitachi EUB7500), which based on pattern matching algorithm. Although impairment of LV relaxation was characterized in patients with hypertrophic cardiomyopathy (HCM), the behavior of LV apical and basal diastolic lengthening and its relation to LV filling are unknown. We obtained basal and apical LV short-axis views in 22 patients with non-obstructive HCM and 25 healthy volunteers (N). Eight equiangular points on endo-myocardium at end-diastole were placed in each view, and the shortening ratios of four directions were calculated and averaged by 2DTT. Then, the time-LV shortening and lengthening curves were obtained. The time intervals from the aortic valve closure to the point of the first 40% of peak lengthening (T 40 ) were measured in each view. Isovolumic relaxation time (IRT) was measured by pulsed Doppler LV in- and out-flow recordings. Although both apical and basal T 40 were similar in N (145.8±38.4 vs. 134.3±34.2msec 0.5 , ns.), the apical T 40 in HCM was longer compared to base (118.7±51.1 vs. 168.8±52.5msec 0.5 , p<0.0001). The time difference of T 40 between apex and base was related to LV IRT (r=0.59, p<0.0001). Nonuniformity of apical-to-basal left ventricular lengthening during early diastole was present in HCM. This apex-to-base dispersion, especially apical delay in timing of LV lengthening may have a physiologic importance for impairment of LV relaxation in HCM.

Structural Damage Detection Using Signal Pattern-Recognition

Deterioration significantly affects the structure performance and safety. A signal-based pattern-recognition procedure is applied for structural damage detection with a limited number of input/output signals. The method is based on extracting and selecting the sensitive features of the structure response to form a unique pattern for any particular damage scenario, and recognizing the unknown damage pattern against the known database to identify the damage location and level (severity). In this study, two types of transformation algorithms are implemented separately for feature extraction: (1) Continuous Wavelet Transform (CWT); and (2) Wavelet Packet Transform (WPT). Three pattern-matching algorithms are also implemented separately for pattern recognition: (1) correlation, (2) least square distance, and (3) Cosh spectral distance. To demonstrate the validity and accuracy of the procedure, experimental studies are conducted on a simple three-story steel structure. The results show that the features of the signal for different damage scenarios can be uniquely identified by these transformations, and correlation algorithms can best perform pattern recognition to identify the unknown damage pattern. The proposed method can also be used to possibly detect the type of damage. It is suitable for structural health monitoring, especially for online monitoring applications.

A 3D kinematic estimation of knee prosthesis using X-ray projection images: clinical assessment of the improved algorithm for fluoroscopy images

In this paper, we propose three ideas to improve a kinematic estimation algorithm for total knee arthroplasty. The first is a two-step estimation algorithm that improves estimation accuracy by excluding certain assumptions needed for the pattern matching algorithm reported by Banks and Hodge. The second is incorporating a 3D geometric articulation model into the algorithm to improve estimation accuracy substantially for the depth translation, and to introduce contact points' trajectories between the articular surfaces. The third is an algorithm to process estimation even when the silhouettes of two components overlap. To assess our algorithm's potential for clinical application, we carried out two experiments. First, we used a robot to position the prosthesis. Estimation accuracy was checked by comparing input data to the robot with the estimates from X-ray photographs. Incorporating our articulation model remarkably reduced the error in the depth translation. Next, we performed a clinical assessment by applying the algorithm and articulation model to fluoroscopy images of a patient who had recently had TKA.

A change detection method for sequential patterns

Recent trends in customer-oriented markets drive many researchers to develop sequential pattern mining algorithms to explore consumer behaviors. However, most of these studies concentrated on how to improve accuracy and efficiency of their methods, and seldom discussed how to detect sequential pattern changes between two time-periods. To help business managers understand the changing behaviors of their customers, a three-phase sequential pattern change detection framework is proposed in this paper. In phase I, two sequential pattern sets are generated respectively from two time-period databases. In phase II, the dissimilarities between all pairs of sequential patterns are evaluated using the proposed sequential pattern matching algorithm. Based on a set of judgment criteria, a sequential pattern is clarified as one of the following three change types: an emerging sequential pattern, an unexpected sequence change, or an added/perished sequential pattern. In phase III, significant change patterns are returned to managers if the degree of change for a pattern is large enough. A practical transaction database is demonstrated to show how the proposed framework helps managers to analyze their customers and make better marketing strategies.

Dynamic-template processing for passive thermograms: Applied to automotive stamping split detection

This manuscript introduces a passive thermal-vision modality to detect splits and tears in automotive stampings in real time. This system scans 3D temperature maps of high reflective steel panels, with complex geometry in addition to the drawing die, to locate abnormal temperature readings indicative of high local wrinkling pressure (cause of metal splitting). Preprocessing utilizes a coefficient-correction map to account for the emissivity dependency on part geometries, and the stamping-die changing the thermal profile. Also, a pattern-matching algorithm is used to synchronize the thermal analysis with the die location (stamping pace) through a new concept of matching thermal histograms. A new image-processing routine named “dynamic-template” is developed to retrieve the split's shape and identify its location. The template is computed through a region of interest (ROI) approach with a dynamic threshold, while accounting for spatial deviations (mainly press-line vibration). The developed hardware and software are implemented on an automotive press-line, and the real-time thermal acquisition is processed to illustrate the system performance and success; different split shapes and sizes are detected under actual operating conditions.

Multiple Pattern Matching on Chinese/English Mixed Texts

PDF HTML阅读 XML下载 导出引用 引用提醒 面向中英文混合环境的多模式匹配算法 DOI: 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: Supported by the Key Science-Technology Project of Xi'an of China under Grant No.06JK225(西安市科技攻关项且);the Research Program of the Education Department of Shannxi Province of China under Grant No.06JK225(陕西省教育厅专项科研计划) Multiple Pattern Matching on Chinese/English Mixed Texts Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:分析了中英文混合环境下多模式匹配的特点,以及已有多模式匹配算法应用于中英文混合环境时的不足,给出并证明了中英文混合环境下多模式匹配算法的性能定理,提出了一种适合于中英文混合环境的基于线索完全哈希Trie结构的多模式匹配算法.该算法扩展了标准Trie结构,以中英文字符内码为键值构造完全哈希Trie匹配机,并利用模式串之间的关系对Trie匹配机进行线索化.理论分析与实验结果表明,所提出的算法在匹配中无需复杂的哈希运算,不需要回溯匹配指针,在中英文混合环境下能够进行正确、高效的匹配,而且不存在空间膨胀问题,具有较低的空间与时间复杂度,有较大理论与应用价值. Abstract:The characteristics of multiple pattern matching in mixed Chinese and English text and the problem of the existing multiple pattern matching algorithms used for processing mixed Chinese and English text are analyzed. A theorem of multiple pattern matching in mixed Chinese and English text is discovered and proved. A novel multiple pattern matching algorithm based on the threaded trie tree is proposed, which expands the standard trie structure, constructs the hash trie matching machine with the codes of Chinese and English characters, and threads the trie tree according to the characteristic of patterns set. The proposed algorithm does not need complex hash operation, and the matching pointer does not need backdate during matching. Theoretic analysis and experimental results demonstrate that the proposed algorithm efficiently solves the space expansion problem, and process mixed Chinese and English text correctly and efficiently with lower time and space complexity. 参考文献 相似文献 引证文献

A novel location estimation based on pattern matching algorithm in underwater environments

In this paper, we present a novel approach based on pattern recognition to treat the underwater localization. The goal is to achieve underwater localization by the pattern matching algorithm. It should be noted that the reflected signals in underwater environments do not affect our location estimation. Therefore, the underwater localization in this study is straightforward and efficient by using the pattern matching algorithm. We exploit the maximum likelihood (ML) to perform our study. Initially, the underwater signals are collected by the sound receiver at some sampling locations. These signals are suitably processed by the ML models and are stored in database. The test location in real-time is estimated through the database. Experimental results show that good accuracy of positioning can be obtained by proposed schemes. The proposed localization schemes can be applied to many other applications in underwater environments.

Fast multi-pattern matching algorithm for intrusion detection

With network speed and the number of rules constantly increasing, pattern matching is becoming the bottleneck in Network Intrusion Detection System (NIDS). This paper proposed a fast Wu-Manber-like multi-pattern matching algorithm for intrusion detection, called FWM. By subdividing the pattern group into two subgroups and dealing with the two subgroups in different methods, the FWM algorithm enhanced the efficiency of pattern matching. Experimental results show that, when pattern group contains the pattern that is less than three bytes, the FWM algorithm improves average performance by 29%~44% compared to the original NIDS pattern matching algorithm.

Reagentless Detection of Mycobacteria tuberculosis H37Ra in Respiratory Effluents in Minutes

Two similar mycobacteria, Mycobacteria tuberculosis H37Ra and Mycobacteria smegmatis are rapidly detected and identified within samples containing a complex background of respiratory effluents using single-particle aerosol mass spectrometry (SPAMS). M. tuberculosis H37Ra (TBa), an avirulent strain, is used as a surrogate for virulent tuberculosis; M. smegmatis (MSm) is utilized as a near-neighbor confounder for TBa. Bovine lung surfactant and human exhaled breath condensate are used as first-order surrogates for infected human lung expirations from patients with pulmonary tuberculosis. This simulated background sputum is mixed with TBa or MSm and nebulized to produce conglomerate aerosol particles, single particles that contain a bacterium embedded within a background respiratory matrix. Mass spectra of single conglomerate particles exhibit ions associated with both respiratory effluents and mycobacteria. Spectral features distinguishing TBa from MSm in pure and conglomerate particles are shown. SPAMS pattern matching alarm algorithms are able to distinguish TBa-containing particles from background matrix and MSm for >50% of the test particles, which is sufficient to enable a high probability of detection and a low false alarm rate if an adequate number of such particles are present. These results indicate the potential usefulness of SPAMS for rapid, reagentless tuberculosis screening.

WE-C-351-06: Tracking Multiple Moving Fiducials During Treatment Based On Simultaneous Onboard KV and Treatment MV Imaging

Purpose: Intra‐fractional organ motion can limit the advantage of highly conformal dose techniques as IMRT due to target position uncertainty. A new strategy has been proposed and investigated to track implanted fiducial markers during treatment on a LINAC with an onboard kV imaging system by using simultaneous kV and treatment MV beam imaging.Method and Materials: A pelvic phantom implanted with three gold cylindrical seeds was tested on a moving platform on a Varian Trilogy. Two phantom verification plans for 3DCRT and IMRTtreatments from real patients were delivered on this phantom while the platform was moving at different speeds. A new pattern matching algorithm has been developed to locate multiple cylindrical fiducials on MV and kV images. Their 3D positions were then calculated from simultaneous orthogonal MV and kV imaging results. Results: Four issues were studied towards the clinical application of this method. 1) Multiple methods were adopted to predict marker positions and reduce search regions to achieve an analysis speed of 10 frame/second. 2) The kV and MV images were acquired while the phantom was moving at various speeds and fiducials could be successfully detected at a linear speed of 1.6 cm/s or less. 3) Varying MV field size and kV source to imager distance indicated that the detection of fiducials on kV images was not affected by the scattering from simultaneous treatment MV beams. 4) Prediction based on relative positions of fiducials was used to closely locate positions of fiducials blocked by a multileaf collimator.Conclusion: These four studies pave the way to automatically track nearly real‐time 3D positions of multiple moving fiducial markers during treatment based on simultaneous kV and MV imaging. It does not require extra hardware such as stereo kV imaging systems and utilizes the treatment beam to reduce dose.

Machine Vision Based Tracking Control of a Ball-Beam System

The dynamic behavior of a ball-beam system is highly nonlinear and its characteristic is difficult to define. In this paper we present a new ball-beam balancing control system using machine vision to feedback the beam angle and ball position on the beam. Adaptive threshold based continuously mean shift vision tracking algorithm is applied to record the ball position and the beam angle with highly captured frame-rate. The proposed vision tracking algorithm is tolerant to lighting influence, highly computing efficiency and more robust than traditional template pattern matching or edge detection algorithm under non-ideal environment. The vision tracking performance is experimentally tested on a ball-beam benchmark system, where a PD controller is applied to control the motion of the ball to maintain balance. Experimental result shows that the beam angle measurement, ball tracking and balancing control of the vision feedback system are robust, accurate and highly efficient.

Alterations in midline cortical thickness and gyrification patterns mapped in children with 22q11.2 deletions.

The 22q11.2 deletion syndrome (velocardiofacial/DiGeorge syndrome) is a neurogenetic condition associated with visuospatial deficits, as well as elevated rates of attentional disturbance, mood disorder, and psychosis. Previously, we detected pronounced cortical thinning in superior parietal and right parieto-occipital cortices in patients with this syndrome, regions critical for visuospatial processing. Here we applied cortical pattern-matching algorithms to structural magnetic resonance images obtained from 21 children with confirmed 22q11.2 deletions (ages 8-17) and 13 demographically matched comparison subjects, in order to map cortical thickness across the medial hemispheric surfaces. In addition, cortical models were remeshed in frequency space to compute their surface complexity. Cortical maps revealed a pattern of localized thinning in the ventromedial occipital-temporal cortex, critical for visuospatial representation, and the anterior cingulate, a key area for attentional control. However, children with 22q11.2DS showed significantly increased gyral complexity bilaterally in occipital cortex. Regional gray matter volumes, particularly in medial frontal cortex, were strongly correlated with both verbal and nonverbal cognitive functions. These findings suggest that aberrant parieto-occipital brain development, as evidenced by both increased complexity and cortical thinning in these regions, may be a neural substrate for the deficits in visuospatial and numerical understanding characteristic of this syndrome.

A Fast Pattern Matching Algorithm with Two Sliding Windows (TSW)

In this research, we propose a fast pattern matching algorithm: The Two Sliding Windows (TSW) algorithm. The algorithm makes use of two sliding windows, each window has a size that is equal to the pattern length. Both windows slide in parallel over the text until the first occurrence of the pattern is found or until both windows reach the middle of the text. The experimental results show that TSW algorithm is superior to other algorithms especially when the pattern occurs at the end of the text.

Evaluation of Matrix-Assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry in Comparison to 16S rRNA Gene Sequencing for Species Identification of Nonfermenting Bacteria

Nonfermenting bacteria are ubiquitous environmental opportunists that cause infections in humans, especially compromised patients. Due to their limited biochemical reactivity and different morphotypes, misidentification by classical phenotypic means occurs frequently. Therefore, we evaluated the use of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for species identification. By using 248 nonfermenting culture collection strains composed of 37 genera most relevant to human infections, a reference database was established for MALDI-TOF MS-based species identification according to the manufacturer's recommendations for microflex measurement and MALDI BioTyper software (Bruker Daltonik GmbH, Leipzig, Germany), i.e., by using a mass range of 2,000 to 20,000 Da and a new pattern-matching algorithm. To evaluate the database, 80 blind-coded clinical nonfermenting bacterial strains were analyzed. As a reference method for species designation, partial 16S rRNA gene sequencing was applied. By 16S rRNA gene sequencing, 57 of the 80 isolates produced a unique species identification (>or=99% sequence similarity); 11 further isolates gave ambiguous results at this threshold and were rated as identified to the genus level only. Ten isolates were identified to the genus level (>or=97% similarity); and two isolates had similarity values below this threshold, were counted as not identified, and were excluded from further analysis. MALDI-TOF MS identified 67 of the 78 isolates (85.9%) included, in agreement with the results of the reference method; 9 were misidentified and 2 were unidentified. The identities of 10 randomly selected strains were 100% correct when three different mass spectrometers and four different cultivation media were used. Thus, MALDI-TOF MS-based species identification of nonfermenting bacteria provided accurate and reproducible results within 10 min without any substantial costs for consumables.

Real-time application of critical dimension measurement of TFT-LCD pattern using a newly proposed 2D image-processing algorithm

A critical dimension measurement system for TFT-LCD patterns has been implemented in this study. To improve the measurement accuracy, an imaging auto-focus algorithm, fast pattern-matching algorithm, and precise edge detection algorithm with subpixel accuracy have been developed and implemented in the system. The optimum focusing position can be calculated using the image focus estimator. The two-step auto-focusing technique has been newly proposed for various LCD patterns, and various focus estimators have been compared to select a stable and accurate one. Fast pattern matching and subpixel edge detection have been developed for measurement. The new approach, called NEMC, is based on edge detection for the selection of influential points; in this approach, points having a strong edge magnitude are only used in the matching procedure. To accelerate pattern matching, point correlation and an image pyramid structure are combined. Edge detection is the most important technique in a vision inspection system. A two-stage edge detection algorithm has been introduced. In the first stage, a first order derivative operator such as the Sobel operator is used to place the edge points and to find the edge directions using a least-square estimation method with pixel accuracy. In the second stage, an eight-connected neighborhood of the estimated edge points is convolved with the LoG (Laplacian of Gaussian) operator, and the LoG-filtered image can be modeled as a continuous function using the facet model. The measurement results of the various patterns are finally presented. The developed system has been successfully used in the TFT-LCD manufacturing industry, and repeatability of less than 30 nm (3 σ) can be obtained with a very fast inspection time.

Glacial isostatic adjustment in Fennoscandia from GRACE data and comparison with geodynamical models

Abstract The Earth’s gravity field observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission shows variations due to the integral effect of mass variations in the atmosphere, hydrosphere and geosphere. Several institutions, such as the GeoForschungsZentrum (GFZ) Potsdam, the University of Texas at Austin, Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL), Pasadena, provide GRACE monthly solutions, which differ slightly due to the application of different reduction models and centre-specific processing schemes. The GRACE data are used to investigate the mass variations in Fennoscandia, an area which is strongly influenced by glacial isostatic adjustment (GIA). Hence the focus is set on the computation of secular trends. Different filters (e.g. isotropic and non-isotropic filters) are discussed for the removal of high frequency noise to permit the extraction of the GIA signal. The resulting GRACE based mass variations are compared to global hydrology models (WGHM, LaDWorld) in order to (a) separate possible hydrological signals and (b) validate the hydrology models with regard to long period and secular components. In addition, a pattern matching algorithm is applied to localise the uplift centre, and finally the GRACE signal is compared with the results from a geodynamical modelling. The GRACE data clearly show temporal gravity variations in Fennoscandia. The secular variations are in good agreement with former studies and other independent data. The uplift centre is located over the Bothnian Bay, and the whole uplift area comprises the Scandinavian Peninsula and Finland. The secular variations derived from the GFZ, CSR and JPL monthly solutions differ up to 20%, which is not statistically significant, and the largest signal of about 1.2 μ Gal/year is obtained from the GFZ solution. Besides the GIA signal, two peaks with positive trend values of about 0.8 μ Gal/year exist in central eastern Europe, which are not GIA-induced, and also not explainable by the hydrology models. This may indicate that the recent global hydrology models have to be revised with respect to long period and secular components. Finally, the GRACE uplift signal is also in quite good agreement with the results from a simple geodynamical modelling.