Pattern Matching Algorithm Research Articles

Point Pattern Matching algorithm based on Point Pair Topological Characteristics and Spectral Matching

Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point’s position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.

Exact pattern matching with feed-forward bloom filters

This article presents a new, memory efficient and cache-optimized algorithm for simultaneously searching for a large number of patterns in a very large corpus. This algorithm builds upon the Rabin-Karp string search algorithm and incorporates a new type of Bloom filter that we call a feed-forward Bloom filter . While it retains the asymptotic time complexity of previous multiple pattern matching algorithms, we show that this technique, along with a CPU architecture-aware design of the Bloom filter, can provide speed-ups between 2× and 30×, and memory consumption reductions as large as 50× when compared with grep. Our algorithm is also well suited for implementations on GPUs: A modern GPU can search for 3 million patterns at a rate of 580MB/s, and for 100 million patterns (a prohibitive number for traditional algorithms) at a rate of 170MB/s.

Signal Pattern Recognition for Damage Diagnosis in Structures

Abstract: A signal‐based pattern‐recognition approach is used for structural damage diagnosis with a single or limited number of input/output signals. The approach is based on extraction of the features of the structural response that present a unique pattern for each specific damage case. In this study, frequency‐based features and time–frequency‐based features were extracted from measured vibration signals by Fast Fourier Transform (FFT) and continuous wavelet transform (CWT) to form one‐dimensional or two‐dimensional patterns, respectively. Three pattern‐matching algorithms including correlation, least‐square distance, and Cosh spectral distance were investigated for pattern matching. To demonstrate the validity of the approach, numerical and experimental studies were conducted on a simple three‐story steel building. Results showed that features of the signal for different damage scenarios could be uniquely identified by these transformations, and suitable correlation algorithms could perform pattern matching that identified both damage location and damage severity. Meanwhile, statistical issues for more complex structures as well as the choice of wavelet functions are discussed.

Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps

BackgroundFor visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process.ResultsWe propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts.Conclusions Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

SU-E-J-93: Fourier Transform-Based Medical Image Registration.

To evaluate the use of a Fast Fourier Transform (FFT) based pattern-matching algorithm for two-dimensional translational and rotational medical image registration. The FFT pattern matching algorithm is based on the Fourier shift theorem. Briefly, image registration is accomplished by obtaining the Fourier Transform (FT) of two images, taking the normalized cross-correlation of the two FT, and performing an inverse FT on this correlation matrix. This results in a Dirchlet delta function that has a maximum value at a location corresponding to the translational shift between the two images. Rotational registration can also be achieved by performing this algorithm on the polar transformation of the FT images. The FT registration method was evaluated through the use of clinical images with induced translational and rotational shifts. Over a range of induced shifts of +/-10 mm in both the x and y directions, and induced rotations of +/-10 degrees, all recovered rotations were within 0.1 degree of the induced rotation, and all recovered translations were within 0.5 mm of the induced translation. The computational time of the FT registration on a 1024×1024 image was approximately 2.23 sec. An FFT based image registration algorithm is computationally efficient and provides a high degree of accuracy for two dimensional image registrations. The FFT registration approach provides a distinct analytical solution and does not rely on iterative methods to converge on a solution. In addition, the discrete nature of the FFT means that the accuracy of the solution is directly related to the size of the pixels in the images. The equivalent of sub-pixel registration can be achieved by simply resizing the image to a larger matrix (i.e. 512×512 to 1024×1024).

SODA

The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated. This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses.

Accelerating Multipattern Matching on Compressed HTTP Traffic

Current security tools, using signature-based detection, do not handle compressed traffic, whose market-share is constantly increasing. This paper focuses on compressed HTTP traffic. HTTP uses GZIP compression and requires some kind of decompression phase before performing a string matching. We present a novel algorithm, Aho-Corasick-based algorithm for Compressed HTTP (ACCH), that takes advantage of information gathered by the decompression phase in order to accelerate the commonly used Aho-Corasick pattern-matching algorithm. By analyzing real HTTP traffic and real Web application firewall signatures, we show that up to 84% of the data can be skipped in its scan. Surprisingly, we show that it is faster to perform pattern matching on the compressed data, with the penalty of decompression, than on regular traffic. As far as we know, we are the first paper that analyzes the problem of on-the-fly multipattern matching on compressed HTTP traffic and suggest a solution.

Robust and accurate pattern matching in fuzzy space for fiducial mark alignment

This paper presents a new pattern matching method for fiducial mark alignment in a fuzzy space. The membership functions of fuzzy sets are designed by distance transforms, and their levels are set in the fuzzy space for fast matching of a specific fiducial mark. After the fuzzification, a sub-pixel level translation is estimated by a fuzzy similarity measure and an interpolation using fuzzified model and target images. This paper also proposes a method of coarse-to-fine rotation estimation in sub-pixel level. Experiments show that the proposed fuzzy space pattern matching algorithm outperforms commercial pattern matching algorithms based on correlation or edge.

Utilizing CLONALPropagation Algorithm for Pattern Matching with Training Data Sets

Pattern recognition has been around for many years in the world of computer engineering and science. It's a technique of learning and matching pattern data sets through memorization. There are two main techniques being used typically by most models which are the back propagation and feed-forward network from ANN (Artificial Neural Network). Both are used simultaneously in completing a task given. Discussed together in this paper are also the features of CLON- ALNet which is a part of AIS (Artificial Immune System). CLONALNet is a technique derived from the clonal se- lection family where it is a hybrid design of CLONALG and opt-AINet used for optimization and hypermutation. Both techniques are then combined producing an- other hybrid algorithm known as CLONALPropagation build specifically for pattern rec- ognition. Several parameters are chosen for hybrid purpose in this work. For ANN the main parameters chosen are the rec- ognition rate, mse and β. As for AIS, the chosen parameters are α (mutation rate) and random population groups, Ab. The outcome of this research will be an algorithm which has a higher recognition rate with a lower or zero error rates, mse compared to the one in ANN back propagation technique.

Proteomic pattern analysis discriminates among multiple sclerosis–related disorders

To use a new, unbiased biomarker discovery strategy to obtain and assess proteomic data from cerebrospinal fluid (CSF) of patients with multiple sclerosis (MS)-related disorders. CSF protein profiles were analyzed from 107 patients with either MS-related disorders (including relapsing remitting MS [RRMS], primary progressive MS [PPMS], anti-aquaporin4 antibody seropositive-neuromyelitis optica spectrum disorder [SP-NMOSD], and seronegative-NMOSD with long cord lesions on spinal magnetic resonance imaging [SN-NMOSD]), amyotrophic lateral sclerosis (ALS), or other inflammatory neurological diseases (used as controls). CSF peptides/proteins were purified with magnetic beads, and directly measured by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The obtained spectra were analyzed with multivariate statistics and pattern matching algorithms. These analyses were replicated in an independent sample set of 84 patients composed of those with MS-related disorders or with other neurological diseases (the second cohort). MS-related disorders differed considerably in terms of CSF protein profiles. SP-NMOSD and SN-NMOSD, both of which fit within the NMO spectrum, were distinguishable from RRMS with high cross-validation accuracy on a support vector machine classifier, especially in relapse phases. Some peaks derived from samples of relapsed SP-NMOSD can discriminate RRMS with high area under curve scores (>0.95) and this was reproduced on the second cohort. The similarity of proteomic patterns between selected neurological diseases were demonstrated by pattern matching analysis. To our surprise, the spectral differences between RRMS and PPMS were much larger than those of PPMS and ALS. Our findings suggest that CSF proteomic pattern analysis can increase the accuracy of disease diagnosis of MS-related disorders and will aid physicians in appropriate therapeutic decision-making.

Comments on "Stack-based Algorithms for Pattern Matching on DAGs"

The paper "Stack-based Algorithms for Pattern Matching on DAGs" generalizes the classical holistic twig join algorithms and proposes PathStackD, TwigStackD and DagStackD to respectively evaluate path, twig and DAG pattern queries on directed acyclic graphs. In this paper, we investigate the major results of that paper, pointing out several discrepancies and proposing solutions to resolving them. We show that the original algorithms do not find particular types of query solutions that are common in practice. We also analyze the effect of an underlying assumption on the correctness of the algorithms and discuss the pre-filtering process that the original work proposes to prune redundant nodes. Our experimental study on both real and synthetic data substantiates our conclusions.

Centralized Parallel form of Pattern Matching Algorithm in Packet Inspection by Efficient Utilization of Secondary Memory in Network Processor

The Network detection engine have capable of inspecting the packet and find out increasing number of network worms and virus . The high level of network providing packet inspection in detection system and the network equipments applies the predefined pattern to identify and manage the monitor packet over the network. Therefore consequently the emerging high level network equipments need to contribute pattern matching and packet inspection. However, searching for patterns at multiple offsets in entire content of network packet requires more processing power than most general purpose processor can provide. We present a novel architecture for programmable centralized parallel pattern matching algorithm for efficient packet inspection with network processor . We mapped our centralized multi parallel pattern matching algorithm [CNMPPMA] for filter packet in parallel. The simulation result reveals that CNMPPMA significantly improves the matching performance.

Secure Authentication Using RFID

Authentication is an essential issue for any organization. Previously, automated authentication was present using punch cards system, but it had security issues. Now days, organizations prefer to have biometrics based authentication. But using biometrics applications is very costly and time consuming. We can derive a time and cost effective solution for this problem using RFID (Radio Frequency Identification). Using feature provided by RFID to detect multiple individuals with very short amount of time and provide security with image pattern matching algorithm. To implement this system, we will interface camera with RFID enabled system which will use Low Frequency (LF) RFID tags. On every detection the camera will capture photograph. Then authentication is processed by using image pattern matching algorithm. Such system will be cost and time effective. Radio Frequency Identification (RFID) is old technology but more widely used in location tracing and tracking applications, due to wider reading ranges, and larger memory capacities, making it a key contributor to the growth of the radio technology industry. Many large corporations are interested in research and development within the field of RFID due to potential growth in various RFID applications. The people management system is an application where masses data needs to be collected and managed in a short duration. But due to authentication issues with this technology makes it less effective. RFID is an automated data collection technology in which radio communication for data transfer across two entities: a reader and a tag. The tag has two sections: one for radio communication and other for data storage. The tags are broadly classified into 3 categories namely active, passive and semi passive. The active tags have an internal power source e.g. a battery, which limits the life time. A passive tag doesn't have a power source and obtain the energy from the magnetic field of the reader. These types of tags are smaller, cheaper and can be used for long time. The scope of the paper is limited to passive tags. The functionality of RFID Passive tags is very simple. When a tag comes in the vicinity of the reader, it detects the radio signals generated by the reader and start to transmit the data stored in the memory. The radio signal generated by the reader offers the power needed to function and the synchronization data for communication between two entities. RFID has emerged as a key technology for automatic data collection. Using this, one can speed up authentication process. Every individual having RFID enabled identity can be detected in very short amount of time. But problem of secured authentication comes into the picture here. One way is proceeding with camera and matching the pattern for individual's photograph.

Fragment Finder 2.0: a computing server to identify structurally similar fragments

Fragment Finder 2.0is a web-based interactive computing server which can be used to retrieve structurally similar protein fragments from 25 and 90% nonredundant data sets. The computing server identifies structurally similar fragments using the protein backbone Cα angles. In addition, the identified fragments can be superimposed using either of the two structural superposition programs,STAMPandPROFIT, provided in the server. The freely available Java plug-inJmolhas been interfaced with the server for the visualization of the query and superposed fragments. The server is the updated version of a previously developed search engine and employs an in-house-developed fast pattern matching algorithm. This server can be accessed freely over the World Wide Web through the URL http://cluster.physics.iisc.ernet.in/ff/.

Multi-Threading and Suffix Grouping on Massive Multiple Pattern Matching Algorithm

The widely used multiple pattern matching algorithms experience severe performance degradation when the number of patterns to match increases. In light of this fact, this paper presents a multi-threaded multiple pattern matching algorithm to overcome the performance degradation; this algorithm presents two additional improvements on the original Wu–Manber algorithm. First, the proposed algorithm employs a multi-threaded execution model to parallelize the pattern matching operation on multi-core processors. Second, the patterns to be searched are distributed over multiple threads according to the pattern similarity. For this purpose, the proposed algorithm groups the target patterns on the basis of their suffixes and distributes the patterns over multiple threads. Through experiments and performance analysis, our algorithm shows a significant performance gain as compared with the original Wu–Manber algorithm and the previously proposed multi-threaded pattern matching on massive pattern sets of size exceeding 5000. The results obtained from the pattern matching operation using eight cores show much improved execution time, which is nearly 14.9 times faster on average than that of the conventional Wu–Manber algorithm. It is demonstrated that the proposed idea improves the overall performance by reducing the amount of workload on a single thread through multi-threading and an efficient data distribution policy.

Mechanisms of Symptomatic Spinal Cord Ischemia After TEVAR: Insights From the European Registry of Endovascular Aortic Repair Complications (EuREC)

To test the hypothesis that simultaneous closure of at least 2 independent vascular territories supplying the spinal cord and/or prolonged hypotension may be associated with symptomatic spinal cord ischemia (SCI) after thoracic endovascular aortic repair (TEVAR). A pattern matching algorithm was used to develop a risk model for symptomatic SCI using a prospective 63-patient single-center cohort to test the positive predictive value (PPV) of prolonged intraoperative hypotension and/or simultaneous closure of at least 2 of 4 the vascular territories supplying the spinal cord (left subclavian, intercostal, lumbar, and hypogastric arteries). This risk model was then applied to data extracted from the multicenter European Registry on Endovascular Aortic Repair Complications (EuREC). Between 2002 and 2010, the 19 centers participating in EuREC reported 38 (1.7%) cases of symptomatic spinal cord ischemia among the 2235 patients in the database. In the single-center cohort, direct correlations were seen between the occurrence of symptomatic SCI and both prolonged intraoperative hypotension (PPV 1.00, 95% CI 0.22 to 1.00, p=0.04) and simultaneous closure of at least 2 independent spinal cord vascular territories (PPV 0.67, 95% CI 0.24 to 0.91, p=0.005). Previous closure of a single vascular territory was not associated with an increased risk of symptomatic spinal cord ischemia (PPV 0.07, 95% CI 0.01 to 0.16, p=0.56). The combination of prolonged hypotension and simultaneous closure of at least 2 territories exhibited the strongest association (PPV 0.75, 95% CI 0.38 to 0.75, p<0.0001). Applying the model to the entire EuREC cohort found an almost perfect agreement between the predicted and observed risk factors (kappa 0.77, 95% CI 0.65 to 0.90). Extensive coverage of intercostal arteries alone by a thoracic stent-graft is not associated with symptomatic SCI; however, simultaneous closure of at least 2 vascular territories supplying the spinal cord is highly relevant, especially in combination with prolonged intraoperative hypotension. As such, these results further emphasize the need to preserve the left subclavian artery during TEVAR.

Research on an Single Pattern Matching Algorithm

The design of exact single pattern string matching algorithm with high performance is the basis of all string matching problems. To overcome the defects of low efficiency of pattern matching, this paper improves one of the fastest exact single pattern matching algorithms known on English text, which is SBNDM2。The simplest form of the BNDM core loop is obtained, in which there are only 5 instructions per-character read by amending the relationship between position in the pattern and bit in the bit mask. And a cross-border protection method is added to the algorithm in order to reduce the cost of cross-border inspection. Two algorithms named S2BNDM and S2BNDM′ are presented. The experimental results indicate that both S2BNDM and S2BNDM′are faster than SBNDM2 in any case.

An Efficient AC Algorithm with GPU

Pattern matching algorithm is the basis of information biology as well as information retrieval research field. As far as the current computing capability of CPU is concerned, it may hardly satisfy the demand in terms of system realtime when faced by a large amount of data. Due to the enormous computing potential of GPU, various efforts have been made for the computing task migration to GPU with given application programs. In this paper, we present an AC Multi-pattern matching algorithm based on GPU with the parallelization of traditional algorithm based on CPU, and the matching efficiency may be significantly improved due to the high performance parallel processing capability of GPU. Experimental results show our proposed scheme achieved a better speed-up compared to the original one.

Wireless Communication Simulation Model for Traffic Monitoring Systems Based on Dynamic Cellular Handoffs

Technology for tracking with handoff-based cellular probes is one of the most important modern methods of traffic monitoring. Some simulation frameworks have been proposed to investigate the key issues in such systems. However, most existing simulation approaches rely on assumptions of cell boundaries and handoff points; these assumptions may lead to inaccurate predictions of the performance of real systems. The proposed model incorporated the actual communication mechanism for cell phone signals used in real-world cellular networks. In the proposed simulation framework, cell boundaries were dynamic, cell sizes varied, and the handoff process was controlled by actual protocols for cellular communication. An algorithm for handoff pattern matching is also presented. The algorithm deals with the dynamic handoff sequence for the purposes of traffic detection. The approach was verified with a calibrated simulation road network. The impacts of two important factors, call duration and probe penetration, were also investigated. The results showed that the proposed simulation platform for wireless communication could produce more reliable results and gain deeper insights into the performance of the handoff-based cellular traffic monitoring systems than had been achieved through the traditional simulation approaches.

Efficiency of TreeMatch Algorithm in XML Tree Pattern Matching

In Recent days exchange XML data more often in organizations and business sectors, so there is an increasing need for effective and efficient processing of queries on XML data. This paper presents a wide analysis to identify the efficiency of XML tree pattern matching algorithms. Previous years many methods have been proposed to match XML tree queries efficiently. In particularly TwigStack, OrderedTJ, TJFast and TreeMatch algorithms. All algorithms to achieve something through these own ways like structural relationship including Parent - Child (P-C) relationship (denoted as '/') and Ancestor-Descendent (A-D) relationships (denoted as '//') and more. Finally, we report our results to show that which algorithm is superior to previous approaches in terms of the performance. Keywords - Efficient TPQ, Efficiency of Tree pattern, XML Tree pattern