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Novel high-throughput (Deep) sequencing technology methods have redefined the way genome sequencing is performed. They are able to produce tens of millions of short sequences (reads) in a single experiment and with a much lower cost than previous sequencing methods. In this paper, we present a new algorithm for addressing the problem of efficiently mapping millions of short reads to a reference genome. In particular, we define and solve the Massive Approximate Pattern Matching problem for mapping short sequences to a reference genome. [ABSTRACT FROM AUTHOR]

The code generator in a compiler attempts to match a subject tree against a collection of tree-shaped patterns for generating instructions. Tree-pattern matching may be considered as a generalization of string parsing. We propose a new generalized LR (GLR) parser, which extends the LR parser stack with a parser cactus. GLR explores all plausible parsing steps to find the least-cost matching. GLR is fast due to two properties: (1) duplicate parsing steps are eliminated and (2) partial parse trees that will not lead to a least-cost matching are discarded as early as possible. [ABSTRACT FROM AUTHOR]

Currently user΄s interests are expressed by XPath or XQuery queries in XML dissemination applications. These queries require a good knowledge of the structure and contents of the documents that will arrive; As well as knowledge of XQuery which few consumers will have. In some cases, where the distinction of relevant and irrelevant documents requires the consideration of a large number of features, the query may be impossible. This paper introduces a data mining approach to XML dissemination that uses a given document collection of the user to automatically learn a classifier modelling of his/her information needs. Also discussed are the corresponding optimization methods that allow a dissemination server to execute a massive number of classifiers simultaneously. The experimental evaluation of several real XML document sets demonstrates the accuracy and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

We propose a dedicated protocol for the highly motivated problem of secure two-party pattern matching: Alice holds a text t ϵ {0,1}*. of length n, while Bob has a pattern p ϵ {0,1}*. of length m. The goal is for Bob to learn where his pattern occurs in Alice΄s text. Our construction guarantees full simulation in the presence of malicious, polynomial-time adversaries (assuming that ElGamal encryption is semantically secure) and exhibits computation and communication costs of O(n + m) in a constant round complexity. In addition to the above, we propose a collection of protocols for variations of the secure pattern matching problem: The pattern may contain wildcards (O(nm) communication in O(1) rounds). The matches may be approximated, i.e., Hamming distance less than some threshold ((O(nm) communication in O(1) rounds). The length, m, of Bob΄s pattern is secret (O(nm) communication in O(1) rounds). The length, n, of Alice΄s text is secret (O(n + m) communication in O(1) rounds). [ABSTRACT FROM AUTHOR]

A major approach for palmprint recognition today is to extract feature vectors corresponding to individual palmprint images and to perform palmprint matching based on some distance metrics. One of the difficult problems in feature- based recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of image acquisition. This paper presents a palmprint recognition using Zernike moments feature extraction. Unsharp filtered palmprint images makes possible to achieve highly robust palmprint recognition. Experimental evaluation using a palmprint image database clearly demonstrates an efficient matching performance of the proposed system. [ABSTRACT FROM AUTHOR]

Chatbot is one of a technology that tried to encounter the question that popped into computer science field in 1950 which is ˵Can machines think?″ [6]. Proposed by mathematician Alan Turing, the question later becomes the pinnacle reference for researchers in artificial intelligence discipline. Turing later also introduces ˵The Imitation Game″ that now known as ˵Turing Test″ where the idea of the test is to examine whether machine can fool a judge into thinking that they are having a conversation with an actual human. The technology back then was great but in rapid evolution of computer science, it can become even better. Evolution is computer scripting language, application design model, and so on, clearly have its advantage towards enabling more complex features in developing a computer program. In this paper, we propose an enhanced algorithm of a chatbot by taking advantages of relational database model to design the whole chatbot architecture that enable several features that cannot or difficult to be done in previous state of computer science programming technique. Started with some literature of a previous developed chatbot, then a detailed description of each new enhanced algorithm together with testing and results from the implementation of these new algorithms that can be used in development of a modern chatbot. These several new algorithms will enable features that will extend chatbot capabilities in responding to the conversation. These algorithm is actually implemented in design and development of chatbot that specifically deal with Bahasa Malaysia language, but taking to account that language in chatbot is really about the data in chatbot knowledge-based, the algorithm is seems transferable wherever it fits into another human language. [ABSTRACT FROM AUTHOR]

FPGA-based PCB Pattern Matching System, which supports a Camera Link (Medium), was used to detect PCB defect patterns. For the automation of the vision inspection of the PCB production process, the system was optimized by implementing the vision library in IP, which is used to produce high speed processing FPGA-based systems and to detect defect patterns. The implemented IPs comprised of Pattern Matching IP, VGA Control IP, Memory Control IP and Single Clock Processing MAD Pattern Matching IP. Xilinx was used to process the image transmitted in high speed from Digital Camera, Vertex-4 type FPGA chip. It allowed the processing of 2352(H) * 1728(V) *8Bit image data transmitted from the camera without the need for a separate Frame Grabber Board[5] in the FPGA. In addition, it could check the image data on a PC. For pattern matching, it abstracted a 480*480 area out of the image, transmitted the image to each IP and displayed the Pattern Matching output result on a TFT-LCD. [ABSTRACT FROM AUTHOR]

Pattern matching is one of the most attractive features of functional programming languages. Recently, pattern matching has been applied to programming languages supporting the main current object oriented features. In this paper, we present a static type analysis based on the abstract interpretation framework aimed at proving the exhaustiveness of pattern matchings and the safety of type casts. The analysis is composed by two distinct abstract domains. The first domain collects information about dynamic typing, while the second one tracks the types that an object cannot be instance of. The analysis has been implemented and applied to all the Scala library. The experimental results underline that our approach scales up since it analyzes a method in 90 msec in average. In addition, the analysis is precise in practice as well, since we prove the exhaustiveness of 42% of pattern matchings and 27% of the type casts without any manual annotation on the code. [ABSTRACT FROM AUTHOR]

Regular Expression (RE) is widely used in many aspects due to its high expressiveness, flexibility and compactness, which requires a high-performance and efficient matching method. A novel approach to accelerate RE pattern matching based on Pattern-Unit (PUREM) is proposed here, in which Pattern-Unit matching is accomplished by a Reconfigurable Function Unit (RFU). The RFU can be integrated into the pipeline of CPU architecture and shares matching jobs with software, without wrecking the compatibility of applications. Compared with other works, our approach offers a flexible mechanism under which hardware does NOT need to vary with RE patterns, and it holds the scalability that can be easily extended to most RE applications and software. For validation, the PUREM HW/SW system has been implemented on the Snort v2.8 and PCRE v7.6 applications. The experimental results show a significant speedup of 3~4x compared to the software performance on a 2GHz Pentium IV machine, where our RFU logic mapped onto Xilinx Virtex-5 XC5VLX50 only takes up 17% resource. [ABSTRACT FROM AUTHOR]

Service Oriented Architecture is a promising architectural approach to solve the integration problem originated by business process integration and automation requirements. Defining the appropriate granularity and scope of services is a critical issue to allow their reuse. Architecture abstractions, such as patterns, are a medium to capture design knowledge and to allow the reuse of successful previous designs. The continual rise of abstraction in software engineering approaches have been a central driver of this work, placing the notion of patterns at business model level. In this paper we propose a set of pattern-based techniques to define the scope and granularity of services based on identified patterns in business process models. Graph-based pattern matching and pattern discovery are proposed to recommend the scope and granularity of services on process-centric description models. Matching of generalised patterns and hierarchical matching are discussed. [ABSTRACT FROM AUTHOR]

Considering the growing usage of XML for communication and data representation, the need for more advanced analytical capabilities on top of XQuery is emerging. In this regard, a pattern matching facility can be considered as a natural extension to empower XQuery. In this paper we first provide some use cases for XML pattern matching. After showing that current XQuery falls short in meeting basic requirements, we propose an extension to XQuery which imposes no changes into current model, while covering a wide range of important use cases. We also implemented our proposal into the MXQuery prototype and show through experiments that, compared to the existing pattern matching means, our extension is not only more expressive, but also more efficient. [ABSTRACT FROM AUTHOR]

This paper presents a design framework for building intelligent interfaces using e-mails to dialogue with human users in task-oriented settings. In particular, the proposed approach is pursued from the pattern matching standpoint. Human-computer interaction (HCI) is faced as a classification process where the input data is represented by the user query written in natural language and the output is represented by the most likely classes of system services with a certain degree of match. In case of partial matching, the system instantiates a dialogue with the human user, attempting to disambiguate the meaning of the written text in the context of system services. A case study is reported and preliminary results are commented. [ABSTRACT FROM AUTHOR]

We present a Curry-style second-order type system with union and intersection types for the lambda-calculus with constructors of Arbiser, Miquel and Rios, an extension of lambda-calculus with a pattern matching mechanism for variadic constructors. To prove the strong normalisation property for this system, we translate well-typed terms in an auxiliary calculus of case-normal forms using the interpretation method. We finally prove the strong normalisation property for the auxiliary calculus using the standard reducibility method. [ABSTRACT FROM AUTHOR]

Information Extraction (IE) is a type of information retrieval meant for extracting structured information. In general, the information on the web is well structured in HTML or XML format. And IE will be there to structure these documents, by using learning techniques for pattern matching in the content. A typical application of IE is to scan a set of documents written in a natural language and populate a database with the information extracted. In this paper, we have concentrated our research work to give a heuristic approach for interactive information extraction technique where the information is in Indian Regional Language. This enables any naive user to extract regional language (Indian) based document from a web document efficiently. It is just similar to a pre-programmed information extraction engine. [ABSTRACT FROM AUTHOR]

In stereotactic radiosurgery we can irradiate a targeted volume precisely with a narrow high-energy x-ray beam, and thus the motion of a targeted area may cause side effects to normal organs. This paper describes our motion detection system with three USB cameras. The motion detection of a patient was performed by tracking his/her ears and nose with three USB cameras, where a pattern matching between a predefined template image for each view and acquired images were done with an active search algorithm. The results of preliminary experiments showed that the measurement accuracy of our system was less than 1.4 mm. We designed a new attachment for its clinical application and made a user interface for the stereotactic radiosurgery. [ABSTRACT FROM AUTHOR]

The subsurface remote-sensing technology currently used in the United States for UXO decontamination is relatively crude, consisting of DC (static) magnetometry. Ultrawideband electromagnetic induction (EMI) is emerging as a technology with reasonable discrimination potential. EMI devices operate in the magneto-quasistatic (MQS) band, usually between tens of Hz and perhaps a couple hundred kHz, and engage a substantially different phenomenology than that of wave electromagnetics. Over the relevant space scales, soil, fresh water, and rock are effectively lossless in the MQS regime, which encourages EMI application. [ABSTRACT FROM AUTHOR]

In biological sequence pattern mining, pattern matching is a core component to count the matches of each candidate pattern. We consider patterns with wildcard gaps. A wildcard gap matches any subsequence with a length between predefined lower and upper bounds. Since the number of candidate patterns might be huge, the efficiency of pattern matching is critical. We study two existing pattern matching algorithms named Pattern mAtching with Independent wildcard Gaps (PAIG) and Gap Constraint Search (GCS). GCS was designed to deal with patterns with identical gaps, and we propose to revise it for the case of independent gaps. PAIG can deal with global length constraints while GCS cannot. Both algorithms have the same space complexity. In the worst case, the time complexity of GCS is lower. However, in the best case, PAIG is more efficient. We discuss appropriate selection between PAIG and GCS through theoretical analysis and experimental results on a biological sequence. [ABSTRACT FROM AUTHOR]

Pattern matching with wildcards and length constraints under the one-off condition is a challenging topic. We propose an algorithm BPBM, based on bit parallelism and the Boyer-Moore algorithm, that outputs an occurrence of a given pattern P as soon as the pattern appears in the given sequence. The experimental results show that our BPBM algorithm has an improved time performance of over 50% with the same matching results when compared with SAIL, a state-of-the-art algorithm of this matching problem. The superiority is even more remarkable when the scale of the pattern increases. [ABSTRACT FROM AUTHOR]

This paper describes an approach to indexing texts by their conceptual content using ontologies along with lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into conceptual feature structures and mapped into concepts in a generative ontology. Synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well as the documents. [ABSTRACT FROM AUTHOR]

Recognizing patterns in conceptual models is useful for a number of purposes, like revealing syntactical errors, model comparison, and identification of business process improvement potentials. In this contribution, we introduce an approach for the specification and matching of structural patterns in conceptual models. Unlike existing approaches, we do not focus on a certain application problem or a specific modeling language. Instead, our approach is generic making it applicable for any pattern matching purpose and any conceptual modeling language. In order to build sets representing structural model patterns, we define operations based on set theory, which can be applied to arbitrary sets of model elements and relationships. Besides a conceptual specification of our approach, we present a prototypical modeling tool that shows its applicability. [ABSTRACT FROM AUTHOR]

This paper presents a new cost-efficient realization scheme of pattern matching circuits in FPGA structures with embedded memory blocks (EMB). The general idea behind the proposed method is to implement combinational circuits using a net of finite state machines (FSM) instead. The application of functional decomposition method reduces the utilization of resources by implementing FSMs using both EMBs and LUT-based programmable logic blocks available in contemporary FPGAs. Experimental results for the proposed method are also shown. A comparison with another dedicated method yields extremely encouraging results: with a comparable number of EMBs, the number of logic cells has been reduced by 95%. [ABSTRACT FROM AUTHOR]

Crying is an acoustic event that contains information about the functioning of the central nervous system, and the analysis of the infant´s crying can be a support in the distinguishing diagnosis in cases like asphyxia and hyperbilirrubinemia. The classification of baby cry has been intended by the use of different types of neural networks and other recognition approaches. In this work we present a pattern classification algorithm based on fuzzy logic Type 2 with which the classification of infant cry is realized. Experiments as well as results are also shown. [ABSTRACT FROM AUTHOR]

In this paper, we propose a low cost interactive painting system, which is realized by a general camera and liquid crystal display (LCD) monitor. By using a newly-designed initialization grid and pattern matching technique, the low-cost camera can achieve a nature painting brush but further figured with many advanced features such video and image capturing, positioning, controlling, painting exiting texture and background capabilities. The proposed interactive painting system can help people to draw a painting directly on any LCD monitor to successfully achieve an edutainment system. Through nature human behaviors, the proposed system can be further advanced to any interactive multimedia educations, gaming and other entertainment applications. [ABSTRACT FROM AUTHOR]

Folksonomies offer an easy method to organize information in the current Web. This fact and their collaborative features have derived in an extensive involvement in many Social Web projects. However they present important drawbacks regarding their limited exploring and searching capabilities, in contrast with other methods as taxonomies, thesauruses and ontologies. One of these drawbacks is an effect of its flexibility for tagging, producing frequently multiple syntactic variations of a same tag. In this paper we study the application of two classical pattern matching techniques, Levenshtein distance for the imperfect string matching and Hamming distance for the perfect string matching, to identify syntactic variations of tags. [ABSTRACT FROM AUTHOR]

This paper presents a novel method of user terminal positioning in cellular networks. A pattern matching technology based on received-signal-strength (RSS) from the pilot channels of cell towers has been the most popular network-based positioning method. In response to a position request, a terminal measures RSSs of pilot channels from surrounding cell towers and then the terminal΄s RSS pattern is compared with a pattern database to find the most correlated one which indicates the position of the terminal. Although the pattern matching method can provide accurate positioning, its database construction and maintenance require a high overhead of periodic labor-intensive pattern collection. In this paper, we propose to exploit the call data records (CDRs) that are uploaded by Assisted Global Positioning System (AGPS) terminals as inputs to the pattern database, which removes or reduces the pattern collection overhead. In AGPS systems, terminals measure satellite signals and cellular network parameters (such as RSS) and relay them to the cellular infrastructure, which in turn calculates the terminal position using both that satellite and cellular network data. The proposed AGPS CDR based pattern matching method takes advantage of the increasing number of AGPS terminals in service: non-AGPS terminals can obtain more precise positioning results in areas where more AGPS calls are generated (e.g. hotspots). To do so, we analyze the characteristics of RSS patterns and AGPS CDRs. Based on the analysis, a pattern-distance metric and an AGPS CDR based pattern matching system are proposed and their performances are evaluated by examining field data of several urban downtown areas of Seoul, Korea. We obtain promising results: the position of the user terminal can be estimated with the accuracy (or, positioning error) at the level of 96.5m and 149.8m for the 67% and the 95% confidence interval, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a fast image matching algorithm based on the normalized cross correlation (NCC) by applying the winner-update strategy on the Walsh-Hadamard transform. Walsh-Hadamard transform is an orthogonal transformation that is easy to compute and has nice energy packing capability. Based on the Cauchy-Schwarz inequality, we derive a novel upper bound for the cross-correlation of image matching in the Walsh-Hadamard domain. Applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of NCC-based pattern matching. Experimental results show the proposed algorithm is very efficient for NCC-based image matching under different lighting conditions and noise levels. [ABSTRACT FROM AUTHOR]

The constant increase in link speeds and number of threats poses challenges to network intrusion detection systems (NIDS), which must cope with higher traffic throughput and perform even more complex per-packet processing. In this paper, we present an intrusion detection system based on the Snort open-source NIDS that exploits the underutilized computational power of modern graphics cards to offload the costly pattern matching operations from the CPU, and thus increase the overall processing throughput. Our prototype system, called Gnort, achieved a maximum traffic processing throughput of 2.3 Gbit/s using synthetic network traces, while when monitoring real traffic using a commodity Ethernet interface, it outperformed unmodified Snort by a factor of two. The results suggest that modern graphics cards can be used effectively to speed up intrusion detection systems, as well as other systems that involve pattern matching operations. [ABSTRACT FROM AUTHOR]

In pattern matching, scanning a given pattern in a particular order greatly influences the performance. This study investigates the effect of different pattern scan orders on natural language text and on DNA sequence data. Besides the well-known right-to-left ordering of Boyer-Moore, and from the least frequent character to most frequent one of Sunday's optimal mismatch algorithm, four alternative character search sequence orderings based on newly introduced distant n-gram statistics are proposed within this work. In all experiments, Sunday's pattern matching algorithm, where the characters of a given pattern can be scanned in any order, is used as the main framework. On natural language test data, the alternative pattern scan orders give better results in 60% of the test keywords. On genome data best ordering among the tested six approaches is the right-to-left order. [ABSTRACT FROM AUTHOR]

Registration becomes difficult when the concerned pattern, e.g., a Chinese seal pattern, is noisy and rotated. In this paper, an approach to Chinese seal registration that is widely used in many commercial applications in Chinese society is presented. For a color image, a SOM algorithm and a simple color filtering process are applied for seal segmentation. Then a contouring analysis is performed on the segmented seal to detect its principal orientation. Finally, the registration is achieved by combining the orientation difference and the center region translation vector for two seals. Experiments on seals having rotations, heavy noise, and different resolutions confirm the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

At present, network information audit system is almost based on text information filtering, Text categorization is the basic technology of text information filtering. Pattern matching algorithms are very important for the rule based information audit system. It directly influence the accuracy and real-time performance of the system. The KMP and BM algorithms are introduced in this paper. Research is carried out to improve the BM algorithm and a better BM algorithm is proposed According to the situation that the system characters group is bigger and that characters of the pat tern are less, the thesis puts forward an improved string-matching algorithm. The results of our experiments prove that it promotes the precision of text categorization. [ABSTRACT FROM AUTHOR]

We present data compression techniques hinged on the notion of a motif, interpreted here as a string of intermittently solid and wild characters that recurs more or less frequently in an input sequence or family of sequences. This notion arises originally in the analysis of sequences, particularly biomolecules, due to its multiple implications in the understanding of biological structure and function, and it has been the subject of various characterizations and study. Correspondingly, motif discovery techniques and tools have been devised. This task is made hard by the circumstance that the number of motifs identifiable in general in a sequence can be exponential in the size of that sequence. A significant gain in the direction of reducing the number of motifs is achieved through the introduction of irredundant motifs, which in intuitive terms are motifs of which the structure and list of occurrences cannot be inferred by a combination of other motifs΄ occurrences. Although suboptimal, the available procedures for the extraction of some such motifs are not prohibitively expensive. Here we show that irredundant motifs can be usefully exploited in lossy compression methods based on textual substitution and suitable for signals as well as text. Actually, once the motifs in our lossy encodings are disambiguated into corresponding lossless codebooks, they still prove capable of yielding savings over popular methods in use. Preliminary experiments with these fungible strategies at the crossroads of lossless and lossy data compression show performances that improve over popular methods (i.e. GZip) by more than 20% in lossy and 10% in lossless implementations. [ABSTRACT FROM AUTHOR]

Web usage mining aims at the discovery of interesting usage patterns from Web server log files. ˵Interestingness″ relates to the business goals of the site owner. However, business goals refer to business objects rather than the page hits and script invocations recorded by the site server. Hence, Web usage analysis requires a preparatory mechanism that incorporates the business goals, the concepts reflecting them and the expert΄s background knowledge on them into the mining process. To this purpose, we present a methodology and a mechanism for the establishment and exploitation of application-oriented concept hierarchies in Web usage analysis. We demonstrate our approach on a real data set and show how it can substantially improve both the search for interesting patterns by the mining algorithm and the interpretation of the mining results by the analyst. [ABSTRACT FROM AUTHOR]