Pair Of Strings Research Articles

Compression-based distance between string data and its application to literary work classification based on authorship

There are many well-known document classification/clustering algorithms. In this paper, compression-based distances between documents are focused on, in particular, the normalized compression distance (NCD). The NCD is a popular and powerful metric between strings. A new distance $$D_\alpha $$ with one parameter $$\alpha $$ between strings is designed on the basis of the NCD, and several properties of $$D_\alpha $$ are studied. It is also proved that every pair of strings $$(x,y)$$ can be plotted on the contour graphs of NCD and $$D_\alpha $$ (and some other compression-based distances) in a 2-dimensional plane. The distance $$D_\alpha (x,y)$$ is defined to take a relatively small value if a string $$x$$ is a portion of a string $$y.$$ Literary works $$x$$ and $$y$$ are usually assumed to be written by the same author(s) if $$x$$ is a portion of $$y.$$ Therefore, it may be appropriate to consider the performance of $$D_\alpha $$ for literary work classification based on authorship, as a benchmark. An algorithm to determine an appropriate value of $$\alpha $$ is presented using the contour graphs, and this algorithm does not require the knowledge of the names of the authors of each work. According to experimental results of the area under receiver operating characteristics curves and clustering, $$D_\alpha $$ with such an appropriate value of $$\alpha $$ performs somewhat better in literary work classification based on authorship.

Strings from geometric tachyon in Rindler space and black hole thermodynamics

The dynamics of a probe particle or wrapped brane moving in the two-dimensional Rindler space can be described by a time-dependent tachyon field theory. Using knowledge of tachyon condensation, we learn that the infalling brane gets thermalised and produces open string pairs at the Hagedorn temperature when entering into the near-horizon Rindler wedge. It is shown that the Hagedorn temperature of the infalling brane is equal to the Hawking temperature of the host black hole detected in the same time coordinate. The infalling brane will decay completely into closed strings, mainly massive modes, when it reaches the horizon in infinitely long time as observed by observers at spatial infinity. Preliminary estimates indicate that the degeneracy of states of the closed strings emitted from the infalling brane should be responsible for the increased entropy in the host black hole due to absorption of the brane.

Online license plate matching procedures using license-plate recognition machines and new weighted edit distance

License-plate recognition (LPR) technology has been widely applied in many different transportation applications such as enforcement, vehicle monitoring, and access control. Recently, there has been effort to exploit an LPR database for vehicle tracking using popular template matching procedures. Existing template matching procedures assume that the true reference string is always available. However, under a two-point LPR survey, a vehicle could have its plate misread at both locations generating a pair of misread strings (or templates) with no reference for matching. To compensate for LPR misreading problem, we propose a new weight function based on a probability model to match the observed outcomes of a dual LPR setup. Also, considering that reversal errors are never made in LPR machines, new editing constraints as a function of the string lengths are proposed to avoid compensation for reversal errors. These editing constraints are incorporated into the constraint edit distance formulation to improve the performance of the matching procedure. Finally, considering that previous template matching procedures do not take advantage of passage time information available in LPR databases, we present an online tracking procedure that considers the properties of probability distribution of vehicle journey times in order to increase the probability of correct matches. Experimental results show that our proposed procedure can improve the accuracy of LPR systems and achieve up to 97% of positive matches with no false matches. Further research is needed to extend the ideas proposed herein to plate-matching with multiple, i.e., more than two, LPR units.

Bounding prefix transposition distance for strings and permutations

A transposition is an operation that exchanges two adjacent substrings. Transpositions over permutations, the sequences with no repeated symbols, are related to genome rearrangements. If one of the substrings is restricted to a prefix then it is called a prefix transposition. The prefix transposition distance between a pair of strings (permutations) is the minimum number of prefix transpositions required to transform a given string (permutation) into another given string (permutation). For a permutation of length n, we improve the current prefix transposition distance upper bound of n−log8n to n−log9/2n. For arbitrary strings, we prove new prefix transposition distance upper and lower bounds. For binary strings of length n, we show that n/2 is an upper bound. We show that the prefix transposition distance problem is NP-complete for binary strings.

Unified Compression-Based Acceleration of Edit-Distance Computation

The edit distance problem is a classical fundamental problem in computer science in general, and in combinatorial pattern matching in particular. The standard dynamic programming solution for this problem computes the edit-distance between a pair of strings of total length O(N) in O(N2) time. To this date, this quadratic upper-bound has never been substantially improved for general strings. However, there are known techniques for breaking this bound in case the strings are known to compress well under a particular compression scheme. The basic idea is to first compress the strings, and then to compute the edit distance between the compressed strings. As it turns out, practically all known o(N2) edit-distance algorithms work, in some sense, under the same paradigm described above. It is therefore natural to ask whether there is a single edit-distance algorithm that works for strings which are compressed under any compression scheme. A rephrasing of this question is to ask whether a single algorithm can exploit the compressibility properties of strings under any compression method, even if each string is compressed using a different compression. In this paper we set out to answer this question by using straight line programs. These provide a generic platform for representing many popular compression schemes including the LZ-family, Run-Length Encoding, Byte-Pair Encoding, and dictionary methods. For two strings of total length N having straight-line program representations of total size n, we present an algorithm running in O(nNlg(N/n)) time for computing the edit-distance of these two strings under any rational scoring function, and an O(n2/3N4/3) time algorithm for arbitrary scoring functions. Our new result, while providing a speed up for compressible strings, does not surpass the quadratic time bound even in the worst case scenario.

Historical Linguistics and Evolutionary Genetics. Based on Symbol Frequencies in Tamil Texts and DNA Sequences

We have studied the rank frequency distribution (RFD) of letters of the alphabet in Tamil language texts. In a novel application of rank frequencies, we have defined a simple intuitive distance parameter between a pair of strings (text or DNA sequence of codons). This distance correlates well with age difference in historical linguistics and evolutionary genetics. Using a distance matrix of a set of strings, we derive evolutionary trees that are broadly in agreement with historical evidence. The method has potential for refinement and application in evolutionary studies to complement other approaches to evolution. The RFD in a single string conforms to a law called the CMPL (Cumulative Modified Power Law), which we had formulated and applied to RFD's of diverse symbol sets.

Trie-join: a trie-based method for efficient string similarity joins

A string similarity join finds similar pairs between two collections of strings. Many applications, e.g., data integration and cleaning, can significantly benefit from an efficient string-similarity-join algorithm. In this paper, we study string similarity joins with edit-distance constraints. Existing methods usually employ a filter-and-refine framework and suffer from the following limitations: (1) They are inefficient for the data sets with short strings (the average string length is not larger than 30); (2) They involve large indexes; (3) They are expensive to support dynamic update of data sets. To address these problems, we propose a novel method called trie-join, which can generate results efficiently with small indexes. We use a trie structure to index the strings and utilize the trie structure to efficiently find similar string pairs based on subtrie pruning. We devise efficient trie-join algorithms and pruning techniques to achieve high performance. Our method can be easily extended to support dynamic update of data sets efficiently. We conducted extensive experiments on four real data sets. Experimental results show that our algorithms outperform state-of-the-art methods by an order of magnitude on the data sets with short strings.

A large postoperative left ventricular hemorrhagic contusion and management by prolonged mechanical circulatory support: a case report

Dear Editor, We experienced a postoperative traumatic left ventricular hematoma that was incidentally found after establishment of rescue mechanical circulatory support (MCS) following sudden postoperative circulatory collapse in the cardiac intensive care unit (CICU). The patient successfully recovered with aggressive and prolonged mechanical circulatory support. We report this case to share a worrisome clinical experience in an intensive care unit. The 4-month-old patient weighing 6.6 kg diagnosed with tetralogy of Fallot and a small secundum atrial septal defect underwent successful total correction in the operation room. However, when he arrived at the cardiac intensive care unit (CICU), sudden bradyarrhythmia developed, leading to acute circulatory collapse. At that moment, we performed open cardiopulmonary resuscitation and established rescue extracorporeal membrane oxygenation (ECMO, Bio-Medicus , Eden Prairie, MN; PHISIO oxygenator, Dideco, Mirandola, Italy). On the 3rd postoperative day, bedside echocardiography showed an unexplained huge hematoma, which was suspected to abut the posterior wall of the left ventricle (LV) in the pericardial space in the first place. On the same day, however, while performing mediastinal irrigation to control bleeding in the operating room, the suspected intrapericardial mass was confirmed to be a swollen hemorrhagic contusion of the posterior wall of the left ventricle, which was also demonstrated in follow-up cardiac computed tomography (Fig. 1). As diffuse oozing from the LV was occurring, packed Gelfoam with thrombin was applied on the LV wall, and massive mediastinal irrigation followed. For anticoagulation, initially heparin was titrated to maintain an ACT around 160 s, followed by exclusion of heparin since LV contusion was confirmed. Packed RBCs and platelets were transfused to achieve Hb [10 g/dl and platelet counts [80,000/mm. On the 4th postoperative day, the oxygenator was changed to a new one because a thrombus had formed in the old one. The patient was weaned from ECMO on the 7th postoperative day, and the divided sternal ends were gradually pulled to the opposite side with a pair of traction strings, accommodating the huge LV. The sternal wound was finally closed on the 14th postoperative day. The patient was able to be discharged with a little motor hypotonia and then completed rehabilitation therapy. The hemorrhagic contusion of the myocardium that developed during ECMO setup was very unusual. In our case, we suspect that the huge contusional hemorrhage of the LV resulted from the procedures used during open cardiac massage and ECMO cannulation. Hemorrhagic problems and bleeding control are always cumbersome issues during ECMO setup [1, 2]. In this case in particular, the contusional wound of the myocardium kept oozing diffusely. However, packing the thrombogenic agent with Gelfoam and maintaining low ACT [2] were relatively effective and sufficient in this puzzling situation. In general, postoperative myocardial edema is decompressed by opening the sternum and covering the wound with a Gore-Tex patch or other materials [3]. However, in our case, the LV was too large to apply

Generalized median string computation by means of string embedding in vector spaces

In structural pattern recognition the median string has been established as a useful tool to represent a set of strings. However, its exact computation is complex and of high computational burden. In this paper we propose a new approach for the computation of median string based on string embedding. Strings are embedded into a vector space and the median is computed in the vector domain. We apply three different inverse transformations to go from the vector domain back to the string domain in order to obtain a final approximation of the median string. All of them are based on the weighted mean of a pair of strings. Experiments show that we succeed to compute good approximations of the median string.

Algorithmic Relative Complexity

Information content and compression are tightly related concepts that can be addressed through both classical and algorithmic information theories, on the basis of Shannon entropy and Kolmogorov complexity, respectively. The definition of several entities in Kolmogorov’s framework relies upon ideas from classical information theory, and these two approaches share many common traits. In this work, we expand the relations between these two frameworks by introducing algorithmic cross-complexity and relative complexity, counterparts of the cross-entropy and relative entropy (or Kullback-Leibler divergence) found in Shannon’s framework. We define the cross-complexity of an object x with respect to another object y as the amount of computational resources needed to specify x in terms of y, and the complexity of x related to y as the compression power which is lost when adopting such a description for x, compared to the shortest representation of x. Properties of analogous quantities in classical information theory hold for these new concepts. As these notions are incomputable, a suitable approximation based upon data compression is derived to enable the application to real data, yielding a divergence measure applicable to any pair of strings. Example applications are outlined, involving authorship attribution and satellite image classification, as well as a comparison to similar established techniques.

Capacitor energising transient limiter for mitigating capacitor switch-on transients

Capacitors are prone to two major types of energising transient phenomenon: transient overvoltage and inrush current (charging current). Energising transients will shorten the lifetime of the capacitor, and furthermore they will damage the contacts of the switching device. This study proposes a rectifier type capacitor energising transient limiter (CETL) for mitigating the isolated capacitor and back-to-back capacitor switch-on transients. The operating condition of the proposed circuit can be divided into two states: the charging suppressive mode and the steady state with its initial transient. During the charging suppressive mode, a pair of diode strings conducts automatically and then the DC reactor provides high impedance at the instant of switching on in order to suppress the capacitor energising transients. During the steady state with its initial transient, all diodes of the bridge rectifier conduct simultaneously and the limiter freewheels; therefore the limiter acts as a short circuit and has no effect. Thus, it is not necessary to increase the capacitor-rated voltage when the CETL is used. In this study, experiments and simulations are carried out to demonstrate the feasibility of the proposed limiter circuit.

Character confusion versus focus word-based correction of spelling and OCR variants in corpora

We present a new approach based on anagram hashing to handle globally the lexical variation in large and noisy text collections. Lexical variation addressed by spelling correction systems is primarily typographical variation. This is typically handled in a local fashion: given one particular text string some system of retrieving near-neighbors is applied, where near-neighbors are other text strings that differ from the particular string by a given number of characters. The difference in characters between the original string and one of its retrieved near-neighbors constitutes a particular character confusion. We present a global way of performing this action: for all possible particular character confusions given a particular edit distance, we sequentially identify all the pairs of text strings in the text collection that display a particular confusion. We work on large digitized corpora, which contain lexical variation due to both the OCR process and typographical or typesetting error and show that all these types of variation can be handled equally well in the framework we present. The character confusion-based prototype of Text-Induced Corpus Clean-up (ticcl) is compared to its focus word-based counterpart and evaluated on 6 years’ worth of digitized Dutch Parliamentary documents. The character confusion approach is shown to gain an order of magnitude in speed on its word-based counterpart on large corpora. Insights gained about the useful contribution of global corpus variation statistics are shown to also benefit the more traditional word-based approach to spelling correction. Final tests on a held-out set comprising the 1918 edition of the Dutch daily newspaper ‘Het Volk’ show that the system is not sensitive to domain variation.

SCHWINGER EFFECT IN NONPARALLEL D1-BRANES: A PATH INTEGRAL APPROACH

We study the Schwinger effect in a system of nonparallel D1-branes for the bosonic strings using the path integral formalism. We drive the string pair creation rate by calculating the one-loop vacuum amplitude of the setup in presence of the background electric field defined along one of the D1-branes. We find an angle dependent minimum value for the background field and show that the decaying of vacuum into string pairs takes place for the field above this value. It is shown that in [Formula: see text] limit the vacuum becomes stable and thus no pair creation occurs.

Trie-join

A string similarity join finds similar pairs between two collections of strings. It is an essential operation in many applications, such as data integration and cleaning, and has attracted significant attention recently. In this paper, we study string similarity joins with edit-distance constraints. Existing methods usually employ a filter-and-refine framework and have the following disadvantages: (1) They are inefficient for the data sets with short strings (the average string length is no larger than 30); (2) They involve large indexes; (3) They are expensive to support dynamic update of data sets. To address these problems, we propose a novel framework called trie-join , which can generate results efficiently with small indexes. We use a trie structure to index the strings and utilize the trie structure to efficiently find the similar string pairs based on subtrie pruning. We devise efficient trie-join algorithms and pruning techniques to achieve high performance. Our method can be easily extended to support dynamic update of data sets efficiently. Experimental results show that our algorithms outperform state-of-the-art methods by an order of magnitude on three real data sets with short strings.

Entropy Based Measurement of Text Dissimilarity for Duplicate – Detection

The problem of identifying approximate similarity between pair of strings is an essential step for data cleansing and data integration process. Most existing approaches have relied on generic or manually tuned distance metrics for estimating the similarity potential duplicate. But existing system does not produce the similarity percentage between pair of strings. In this paper we propose a method using entropy and information gain (IG) to find dissimilarity between pair of strings to increase the accuracy of data.

Shape recognition based on Kernel-edit distance

In this paper a kernel method for shape recognition is proposed. The approach is based on the edit distance between pairs of shapes after transforming them into symbol strings. The transformation of shapes into symbol strings is invariant to similarity transforms and can handle partial occlusions. Representation of shape contours uses the shape contexts and applies dynamic programming for finding the correspondence between points over shape contours. Corresponding points are then transformed into symbolic representation and the normalized edit distance computes the dissimilarity between pairs of strings in the database. Obtained distances are then transformed into suitable kernels which are classified using support vector machines. Experimental results over a variety of shape databases show that the proposed approach is suitable for shape recognition.

Modular composition predicts kinase/substrate interactions

BackgroundPhosphorylation events direct the flow of signals and metabolites along cellular protein networks. Current annotations of kinase-substrate binding events are far from complete. In this study, we scanned the entire human protein sequences using the PROSITE domain annotation tool to identify patterns of domain composition in kinases and their substrates. We identified statistically enriched pairs of strings of domains (signature pairs) in kinase-substrate couples presented in the 2006 version of the PTM database.ResultsThe signature pairs enriched in kinase - substrate binding interactions turned out to be highly specific to kinase subtypes. The resulting list of signature pairs predicted kinase-substrate interactions in validation dataset not used in learning with high statistical accuracy.ConclusionsThe method presented here produces predictions of protein phosphorylation events with high accuracy and mid-level coverage. Our method can be used in expanding the currently available drafts of cell signaling pathways and thus will be an important tool in the development of combination drug therapies targeting complex diseases.

Statistical inference of transmission fidelity of DNA methylation patterns over somatic cell divisions in mammals

We develop Bayesian inference methods for a recently-emerging type of epigenetic data to study the transmission fidelity of DNA methylation patterns over cell divisions. The data consist of parent-daughter double-stranded DNA methylation patterns with each pattern coming from a single cell and represented as an unordered pair of binary strings. The data are technically difficult and time-consuming to collect, putting a premium on an efficient inference method. Our aim is to estimate rates for the maintenance and de novo methylation events that gave rise to the observed patterns, while accounting for measurement error. We model data at multiple sites jointly, thus using whole-strand information, and considerably reduce confounding between parameters. We also adopt a hierarchical structure that allows for variation in rates across sites without an explosion in the effective number of parameters. Our context-specific priors capture the expected stationarity, or near-stationarity, of the stochastic process that generated the data analyzed here. This expected stationarity is shown to greatly increase the precision of the estimation. Applying our model to a data set collected at the human FMR1 locus, we find that measurement errors, generally ignored in similar studies, occur at a nontrivial rate (inappropriate bisulfite conversion error: 1.6$%$ with 80$%$ CI: 0.9--2.3$%$). Accounting for these errors has a substantial impact on estimates of key biological parameters. The estimated average failure of maintenance rate and daughter de novo rate decline from 0.04 to 0.024 and from 0.14 to 0.07, respectively, when errors are accounted for. Our results also provide evidence that de novo events may occur on both parent and daughter strands: the median parent and daughter de novo rates are 0.08 (80$%$ CI: 0.04--0.13) and 0.07 (80$%$ CI: 0.04--0.11), respectively.

A Note on the First Occurrence of Strings

We consider the context of a three-person game in which each player selects strings over $\{0,1\}$ and observe a series of fair coin tosses. The winner of the game is the player whose selected string appears first. Recently, Chen et al. showed that if the string length is greater and equal to three, two players can collude to attain an advantage by choosing the pair of strings $11\ldots 10$ and $00\ldots 01$. We call these two strings "complement strings", since each bit of one string is the complement bit of the corresponding bit of the other string. In this note, we further study the property of complement strings for three-person games. We prove that if the string length is greater than five and two players choose any pair of complement strings (except for the pair $11\ldots 10$ and $00\ldots 01$), then the third player can always attain an advantage by choosing a particular string.

Fast motif recognition via application of statistical thresholds

BackgroundImproving the accuracy and efficiency of motif recognition is an important computational challenge that has application to detecting transcription factor binding sites in genomic data. Closely related to motif recognition is the CONSENSUS STRING decision problem that asks, given a parameter d and a set of ℓ-length strings S = {s1, ..., sn}, whether there exists a consensus string that has Hamming distance at most d from any string in S. A set of strings S is pairwise bounded if the Hamming distance between any pair of strings in S is at most 2d. It is trivial to determine whether a set is pairwise bounded, and a set cannot have a consensus string unless it is pairwise bounded. We use CONSENSUS STRING to determine whether or not a pairwise bounded set has a consensus. Unfortunately, CONSENSUS STRING is NP-complete. The lack of an efficient method to solve the CONSENSUS STRING problem has caused it to become a computational bottleneck in MCL-WMR, a motif recognition program capable of solving difficult motif recognition problem instances.ResultsWe focus on the development of a method for solving CONSENSUS STRING quickly with a small probability of error. We apply this heuristic to develop a new motif recognition program, sMCL-WMR, which has impressive accuracy and efficiency. We demonstrate the performance of sMCL-WMR in detecting weak motifs in large data sets and in real genomic data sets, and compare the performance to other leading motif recognition programs. In our preliminary discussion of our CONSENSUS STRING algorithm we give insight into the issue of sampling pairwise bounded sets, and discuss its relevance to motif recognition.ConclusionOur novel heuristic gives birth to a state of the art program, sMCL-WMR, that is capable of detecting weak motifs in data sets with a large number of strings. sMCL-WMR is orders of magnitude faster than its predecessor MCL-WMR and is capable of solving previously unsolved synthetic motif recognition problems. Lastly, sMCL-WMR shows impressive accuracy in detecting transcription factor binding sites in the genomic data and used in the assessment of Tompa et al.