Academic literature on the topic 'String distance measures'
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Journal articles on the topic "String distance measures"
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Winter, Felix, Nysret Musliu, and Peter Stuckey. "Explaining Propagators for String Edit Distance Constraints." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 1676–83. http://dx.doi.org/10.1609/aaai.v34i02.5530.
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The computation of string similarity measures has been thoroughly studied in the scientific literature and has applications in a wide variety of different areas. One of the most widely used measures is the so called string edit distance which captures the number of required edit operations to transform a string into another given string. Although polynomial time algorithms are known for calculating the edit distance between two strings, there also exist NP-hard problems from practical applications like scheduling or computational biology that constrain the minimum edit distance between arrays of decision variables. In this work, we propose a novel global constraint to formulate restrictions on the minimum edit distance for such problems. Furthermore, we describe a propagation algorithm and investigate an explanation strategy for an edit distance constraint propagator that can be incorporated into state of the art lazy clause generation solvers. Experimental results show that the proposed propagator is able to significantly improve the performance of existing exact methods regarding solution quality and computation speed for benchmark problems from the literature.
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ZHANG, LILI, and F. BLANCHET-SADRI. "ALGORITHMS FOR APPROXIMATE K-COVERING OF STRINGS." International Journal of Foundations of Computer Science 16, no. 06 (December 2005): 1231–51. http://dx.doi.org/10.1142/s0129054105003789.
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Computing approximate patterns in strings or sequences has important applications in DNA sequence analysis, data compression, musical text analysis, and so on. In this paper, we introduce approximate k-covers and study them under various commonly used distance measures. We propose the following problem: "Given a string x of length n, a set U of m strings of length k, and a distance measure, compute the minimum number t such that U is a set of approximate k-covers for x with distance t". To solve this problem, we present three algorithms with time complexity O(km(n - k)), O(mn2) and O(mn2) under Hamming, Levenshtein and edit distance, respectively. A World Wide Web server interface has been established at for automated use of the programs.
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LYRAS, DIMITRIOS P., KYRIAKOS N. SGARBAS, and NIKOLAOS D. FAKOTAKIS. "APPLYING SIMILARITY MEASURES FOR AUTOMATIC LEMMATIZATION: A CASE STUDY FOR MODERN GREEK AND ENGLISH." International Journal on Artificial Intelligence Tools 17, no. 05 (October 2008): 1043–64. http://dx.doi.org/10.1142/s021821300800428x.
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This paper addresses the problem of automatic induction of the normalized form (lemma) of regular and mildly irregular words with no direct supervision using language-independent algorithms. More specifically, two string distance metric models (i.e. the Levenshtein Edit Distance algorithm and the Dice Coefficient similarity measure) were employed in order to deal with the automatic word lemmatization task by combining two alignment models based on the string similarity and the most frequent inflectional suffixes. The performance of the proposed model has been evaluated quantitatively and qualitatively. Experiments were performed for the Modern Greek and English languages and the results, which are set within the state-of-the-art, have showed that the proposed model is robust (for a variety of languages) and computationally efficient. The proposed model may be useful as a pre-processing tool to various language engineering and text mining applications such as spell-checkers, electronic dictionaries, morphological analyzers etc.
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ŠIMŮNEK, MARTIN, and BOŘIVOJ MELICHAR. "BORDERS AND FINITE AUTOMATA." International Journal of Foundations of Computer Science 18, no. 04 (August 2007): 859–71. http://dx.doi.org/10.1142/s0129054107005029.
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A border of a string is a prefix of the string that is simultaneously its suffix. It is one of the basic stringology keystones used as a part of many algorithms in pattern matching, molecular biology, computer-assisted music analysis and others. The paper offers the automata-theoretical description of Iliopoulos's ALL_BORDERS algorithm. The algorithm finds all borders of a string with don't care symbols. We show that ALL_BORDERS algorithm is an implementation of a finite state transducer of specific form. We describe how such a transducer can be constructed and what should be the input string like. The described transducer finds a set of lengths of all borders. Last but not least, we define approximate borders and show how to find all approximate borders of a string when we concern Hamming distance definition. Our solution of this problem is based on transducers again. This allows us to use analogy with automata-based pattern matching methods. Finally we discuss conditions under which the same principle can be used for other distance measures.
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Deng, Qiao, Hui Zhang, Jun Li, Xuejun Hou, and Hao Wang. "Study of Downhole Shock Loads for Ultra-Deep Well Perforation and Optimization Measures." Energies 12, no. 14 (July 17, 2019): 2743. http://dx.doi.org/10.3390/en12142743.
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Ultra-deep well perforation is an important direction for the development of unconventional oil and gas resources, the security with shock loads is a difficult technical problem. Firstly, the theoretical analysis of perforated string is carried out, the dynamics models of which are established in the directions of axial, radial and circumferential. Secondly, the process of perforating with hundreds of bullets is simulated by using the software of LS-DYNA (ANSYS, Inc, Pennsylvania, USA). The propagation attenuation model of shock loads is established, and a calculation model to predict shock loads at different positions of the tubing interval has been fitted by considering multiple factors. The dynamic response of perforated string is studied, and the vulnerable parts of which are found out. Thirdly, the optimization measures are put forward for ultra-deep well perforation by the design of shock adsorption and safety distance of the packer. Finally, the field case of an ultra-deep well shows that the research method in this paper is practical, and the optimization measures are reasonable and effective. This study can provide important guidance to reduce shock damage and improve security for ultra-deep well perforation.
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Rowe, Jonathan E. "A Normed Space of Genetic Operators with Applications to Scalability Issues." Evolutionary Computation 9, no. 1 (March 2001): 25–42. http://dx.doi.org/10.1162/10636560151075103.
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We define an abstract normed vector space where the genetic operators are elements. This is used to define the disturbance of the generational operator g as the distance between the crossover and mutation operator (combined) and the identity. This quantity appears in a bound on the variance of fixed-point populations, and in a bound on the force ‖v – g (v)‖ that applies to the optimal population v. When analyze for the case of fixed-length binary strings, a connection is shown between these measures and the size of the search space. Guides for parameter settings are given, if population convergence is required as the string length tends to infinity.
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Rakhmawati, Nur Aini, and Miftahul Jannah. "Food Ingredients Similarity Based on Conceptual and Textual Similarity." Halal Research Journal 1, no. 2 (October 27, 2021): 87–95. http://dx.doi.org/10.12962/j22759970.v1i2.107.
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Open Food Facts provides a database of food products such as product names, compositions, and additives, where everyone can contribute to add the data or reuse the existing data. The open food facts data are dirty and needs to be processed before storing the data to our system. To reduce redundancy in food ingredients data, we measure the similarity of ingredient food using two similarities: the conceptual similarity and textual similarity. The conceptual similarity measures the similarity between the two datasets by its word meaning (synonym), while the textual similarity is based on fuzzy string matching, namely Levenshtein distance, Jaro-Winkler distance, and Jaccard distance. Based on our evaluation, the combination of similarity measurements using textual and Wordnet similarity (conceptual) was the most optimal similarity method in food ingredients.
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Zhu, Jin, Dayu Cheng, Weiwei Zhang, Ci Song, Jie Chen, and Tao Pei. "A New Approach to Measuring the Similarity of Indoor Semantic Trajectories." ISPRS International Journal of Geo-Information 10, no. 2 (February 20, 2021): 90. http://dx.doi.org/10.3390/ijgi10020090.
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People spend more than 80% of their time in indoor spaces, such as shopping malls and office buildings. Indoor trajectories collected by indoor positioning devices, such as WiFi and Bluetooth devices, can reflect human movement behaviors in indoor spaces. Insightful indoor movement patterns can be discovered from indoor trajectories using various clustering methods. These methods are based on a measure that reflects the degree of similarity between indoor trajectories. Researchers have proposed many trajectory similarity measures. However, existing trajectory similarity measures ignore the indoor movement constraints imposed by the indoor space and the characteristics of indoor positioning sensors, which leads to an inaccurate measure of indoor trajectory similarity. Additionally, most of these works focus on the spatial and temporal dimensions of trajectories and pay less attention to indoor semantic information. Integrating indoor semantic information such as the indoor point of interest into the indoor trajectory similarity measurement is beneficial to discovering pedestrians having similar intentions. In this paper, we propose an accurate and reasonable indoor trajectory similarity measure called the indoor semantic trajectory similarity measure (ISTSM), which considers the features of indoor trajectories and indoor semantic information simultaneously. The ISTSM is modified from the edit distance that is a measure of the distance between string sequences. The key component of the ISTSM is an indoor navigation graph that is transformed from an indoor floor plan representing the indoor space for computing accurate indoor walking distances. The indoor walking distances and indoor semantic information are fused into the edit distance seamlessly. The ISTSM is evaluated using a synthetic dataset and real dataset for a shopping mall. The experiment with the synthetic dataset reveals that the ISTSM is more accurate and reasonable than three other popular trajectory similarities, namely the longest common subsequence (LCSS), edit distance on real sequence (EDR), and the multidimensional similarity measure (MSM). The case study of a shopping mall shows that the ISTSM effectively reveals customer movement patterns of indoor customers.
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Jiang, Hao, and Wai Ki Ching. "Physico-Chemically Weighted Kernel for SVM Protein Classification." Applied Mechanics and Materials 195-196 (August 2012): 385–90. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.385.
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In this paper, a novel kernel taking into consideration of the physico-chemical properties of amino acids as well as the motif information is proposed to tackle the problem of protein classification. Similarity matrix is constructed based on an AAindex2 substitution matrix which measures the amino acid pair distance. Together with the motif content posing importance on the protein sequences, a new kernel is constructed. Numerical examples indicate that the string-based kernel in conjunction with SVM classifier performs significantly better than the traditional spectrum kernel method.
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Koehler, Jonathan J., and Caryn A. Conley. "The “Hot Hand” Myth in Professional Basketball." Journal of Sport and Exercise Psychology 25, no. 2 (June 2003): 253–59. http://dx.doi.org/10.1123/jsep.25.2.253.
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The “hot hand” describes the belief that the performance of an athlete, typically a basketball player, temporarily improves following a string of successes. Although some earlier research failed to detect a hot hand, these studies are often criticized for using inappropriate settings and measures. The present study was designed with these criticisms in mind. It offers new evidence in a unique setting, the NBA Long Distance Shootout contest, using various measures. Traditional sequential dependency runs analyses, individual level analyses, and an analysis of spontaneous outbursts by contest announcers about players who are “on fire” fail to reveal evidence of a hot hand. We conclude that declarations of hotness in basketball are best viewed as historical commentary rather than as prophecy about future performance.
Dissertations / Theses on the topic "String distance measures"
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Liptak, Zsuzsanna. "Strings in Proteomics and Transcriptomics: Algorithmic and Combinatorial Questions in Mass Spectrometry and EST Clustering." Doctoral thesis, 2005. http://hdl.handle.net/11562/391087.
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xThis thesis treats two problem areas in bioinformatics which can both be benefi- cially formalized as string problems. The first (and larger) part deals with weighted string problems as they arise from biotechnological mass spectrometry applications. In a mass spectrometry experiment—put in a simplified manner—the molecular mass of the sample mo- lecules is determined. The aim is to identify the sample, either with or without additional information from a database, relying on the fact that the different build- ing blocks of proteins (namely, amino acids) and of DNA molecules (nucleotides) have different molecular masses. Viewing proteins and DNA molecules as strings, this leads naturally to the definition of weighted strings as strings over a finite alphabet Σ with an additional weight (or mass) function μ : Σ → R+. We develop some results in weighted string combinatorics, and then present ef- ficient algorithms for three weighted string problems which are motivated by mass spectrometry. First, the mass decomposition problem is the problem of finding all compomers whose mass equals a query mass. Here, a compomer is an integer vector specify- ing the number of occurrences of each character of Σ. A compomer abstracts from the order of characters in a string and identifies instead all strings with the same number of occurrences of each character—since these strings all have the same mass. We also present simulation results and tables detailing the number of com- pomers for different biomolecules, in the ranges appropriate for mass spectrometry applications. Next, we give several efficient algorithms for the submass problem: to test, for a given weighted string s and a query mass M, whether s has a substring with mass M; to find where such a substring occurs; and other variants. We present an algorithm for binary alphabets which runs in time logarithmic in the length of s. Furthermore, we present several algorithms for the problem where multiple masses are sought; these algorithms encode the submasses of s in a polynomial and rely for their efficiency on Fast Fourier Transform for polynomial multiplication. The third weighted string problem we discuss is de novo peptide sequencing, i.e., recovering the amino acid sequence of a sample peptide from tandem MS data, a specialized mass spectrometry experiment. We describe an algorithm which is an enhancement of a dynamic programming algorithm presented by Chen et al. in 2000. We describe our implementation and present some simulation results. The second part of the thesis deals with EST clustering. ESTs (expressed se- quence tags) are short DNA sequences which are partial copies of mRNAs; they are produced in a high-throughput manner and submitted to public databases. In EST clustering, the aim is to produce a partition of a large set of ESTs, where each cluster corresponds to a gene; thus enabling the researcher to identify which genes were being expressed. Clearly, the quality of the clustering is highly dependent on the dissimilarity measure (distance/similarity measure) for strings and on the clustering algorithm employed. We have developed a method for evaluating differ- ent string dissimilarity measures and clustering algorithms. Finally, we present simulation results for five dissimilarity measures and one clustering algorithm.
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Rebenich, Niko. "Counting prime polynomials and measuring complexity and similarity of information." Thesis, 2016. http://hdl.handle.net/1828/7251.
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This dissertation explores an analogue of the prime number theorem for polynomials over finite fields as well as its connection to the necklace factorization algorithm T-transform and the string complexity measure T-complexity. Specifically, a precise asymptotic expansion for the prime polynomial counting function is derived. The approximation given is more accurate than previous results in the literature while requiring very little computational effort. In this context asymptotic series expansions for Lerch transcendent, Eulerian polynomials, truncated polylogarithm, and polylogarithms of negative integer order are also provided. The expansion formulas developed are general and have applications in numerous areas other than the enumeration of prime polynomials.
A bijection between the equivalence classes of aperiodic necklaces and monic prime polynomials is utilized to derive an asymptotic bound on the maximal T-complexity value of a string. Furthermore, the statistical behaviour of uniform random sequences that are factored via the T-transform are investigated, and an accurate probabilistic model for short necklace factors is presented.
Finally, a T-complexity based conditional string complexity measure is proposed and used to define the normalized T-complexity distance that measures similarity between strings. The T-complexity distance is proven to not be a metric. However, the measure can be computed in linear time and space making it a suitable choice for large data sets.Graduate
0544 0984 0405
nrebenich@gmail.com
Book chapters on the topic "String distance measures"
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Ganesh, Arun, Tomasz Kociumaka, Andrea Lincoln, and Barna Saha. "How Compression and Approximation Affect Efficiency in String Distance Measures." In Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2867–919. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2022. http://dx.doi.org/10.1137/1.9781611977073.112.
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Krishnaveni, B., and S. Sridhar. "Role of Distance Measures in Approximate String Matching Algorithms for Face Recognition System." In IFIP Advances in Information and Communication Technology, 157–69. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63467-4_12.
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Nguyen, Thi Thuy Anh, and Stefan Conrad. "An Improved String Similarity Measure Based on Combining Information-Theoretic and Edit Distance Methods." In Communications in Computer and Information Science, 228–39. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25840-9_15.
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Nzengya, Daniel M., and John K. Maguta. "Gendered Vulnerability to Climate Change Impacts in Selected Counties in Kenya." In African Handbook of Climate Change Adaptation, 1–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-42091-8_169-1.
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AbstractExtreme climate change events such as frequent and prolonged droughts or floods associated with climate change can be very disruptive to peoples’ livelihoods particularly in rural settings, where people rely on the immediate environment for livelihood. Shocks in the people’s livelihoods can trigger diverse responses that include migration as a coping or adaption strategy. Migration takes many forms depending on the context and resources availability. Very few studies in Kenya have used qualitative analysis to bring up women’s voices in relation to gender, climate change, and migration, especially along hydrological gradient. This chapter presents results of qualitative research conducted from 58 participants in 2018 in three counties in Kenya, namely, Kiambu County, Machakos, and Makueni. The study sought to examine gender perceptions related to climate-induced migration, that is: whether climate change is perceived to be affecting women’s livelihood differently from that of men; examine in what ways experiences of climate induced migration differed for men and women; explore perceptions on the county government efforts to cope with climate-induced migration; and examine perceptions of the role of nongovernmental agencies in helping citizens cope with climate change. From the results obtained on ways in which climate change affected women livelihoods more than men had four themes: (1) women exerted more strain in domestic chores, child/family care, and in the farm labor; (2) women also experienced more time demands. The sources of water and firewood were getting more scarce leading to women travel long distances in search to fetch water and firewood; (3) reduced farm yields, hence inadequate food supply; and (4) the effects of time and strain demands on women was a contributory factor to women poor health and domestic conflicts. Several measures that the county government could take to assist women to cope with climate change-induced migration had five themes which include the following: (1) developing climate change mitigations, and reducing deforestation; (2) increasing water harvesting and storage; (3) develop smart agriculture through the use of drought-resistant crops and drought mitigation education; (4) encourage diversification of livelihoods; and finally (5) providing humanitarian assistance to the most vulnerable populations such as orphans and the very poor. Thirdly, the measures mentioned that NGO’s could take to assist rural communities to cope with climate change-induced migration did not vary significantly from those mentioned for county government, except probably for a new theme of increasing advocacy for climate adaption policies.
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Nzengya, Daniel M., and John Kibe Maguta. "Gendered Vulnerability to Climate Change Impacts in Selected Counties in Kenya." In African Handbook of Climate Change Adaptation, 2045–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_169.
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AbstractExtreme climate change events such as frequent and prolonged droughts or floods associated with climate change can be very disruptive to peoples’ livelihoods particularly in rural settings, where people rely on the immediate environment for livelihood. Shocks in the people’s livelihoods can trigger diverse responses that include migration as a coping or adaption strategy. Migration takes many forms depending on the context and resources availability. Very few studies in Kenya have used qualitative analysis to bring up women’s voices in relation to gender, climate change, and migration, especially along hydrological gradient. This chapter presents results of qualitative research conducted from 58 participants in 2018 in three counties in Kenya, namely, Kiambu County, Machakos, and Makueni. The study sought to examine gender perceptions related to climate-induced migration, that is: whether climate change is perceived to be affecting women’s livelihood differently from that of men; examine in what ways experiences of climate induced migration differed for men and women; explore perceptions on the county government efforts to cope with climate-induced migration; and examine perceptions of the role of nongovernmental agencies in helping citizens cope with climate change. From the results obtained on ways in which climate change affected women livelihoods more than men had four themes: (1) women exerted more strain in domestic chores, child/family care, and in the farm labor; (2) women also experienced more time demands. The sources of water and firewood were getting more scarce leading to women travel long distances in search to fetch water and firewood; (3) reduced farm yields, hence inadequate food supply; and (4) the effects of time and strain demands on women was a contributory factor to women poor health and domestic conflicts. Several measures that the county government could take to assist women to cope with climate change-induced migration had five themes which include the following: (1) developing climate change mitigations, and reducing deforestation; (2) increasing water harvesting and storage; (3) develop smart agriculture through the use of drought-resistant crops and drought mitigation education; (4) encourage diversification of livelihoods; and finally (5) providing humanitarian assistance to the most vulnerable populations such as orphans and the very poor. Thirdly, the measures mentioned that NGO’s could take to assist rural communities to cope with climate change-induced migration did not vary significantly from those mentioned for county government, except probably for a new theme of increasing advocacy for climate adaption policies.
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Hirschberg, D. S. "Serial Computations of Levenshtein Distances." In Pattern Matching Algorithms. Oxford University Press, 1997. http://dx.doi.org/10.1093/oso/9780195113679.003.0007.
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In the previous chapters, we discussed problems involving an exact match of string patterns. We now turn to problems involving similar but not necessarily exact pattern matches. There are a number of similarity or distance measures, and many of them are special cases or generalizations of the Levenshtein metric. The problem of evaluating the measure of string similarity has numerous applications, including one arising in the study of the evolution of long molecules such as proteins. In this chapter, we focus on the problem of evaluating a longest common subsequence, which is expressively equivalent to the simple form of the Levenshtein distance. The Levenshtein distance is a metric that measures the similarity of two strings. In its simple form, the Levenshtein distance, D(x , y), between strings x and y is the minimum number of character insertions and/or deletions (indels) required to transform string x into string y. A commonly used generalization of the Levenshtein distance is the minimum cost of transforming x into y when the allowable operations are character insertion, deletion, and substitution, with costs δ(λ , σ), δ(σ, λ), and δ(σ1, σ2) , that are functions of the involved character(s). There are direct correspondences between the Levenshtein distance of two strings, the length of the shortest edit sequence from one string to the other, and the length of the longest common subsequence (LCS) of those strings. If D is the simple Levenshtein distance between two strings having lengths m and n, SES is the length of the shortest edit sequence between the strings, and L is the length of an LCS of the strings, then SES = D and L = (m + n — D)/2. We will focus on the problem of determining the length of an LCS and also on the related problem of recovering an LCS. Another related problem, which will be discussed in Chapter 6, is that of approximate string matching, in which it is desired to locate all positions within string y which begin an approximation to string x containing at most D errors (insertions or deletions).
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Berkowitz, Daniel, and Karen B. Clay. "Initial Conditions and State Political Competition." In The Evolution of a Nation. Princeton University Press, 2011. http://dx.doi.org/10.23943/princeton/9780691136042.003.0003.
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This chapter investigates the relationship between five initial conditions in states—temperature, precipitation, distance to oceans, distance to rivers and lakes, and colonial legal system—and long-run levels of state political competition. State political competition is measured by examining the division of seats in the legislature between the political parties, although a number of other measures of state political competition are also examined. This chapter sketches some relationships between initial conditions and state political competition. It emphasizes the importance of state political competition, because it is thought to lead to better economic and social outcomes. In fact, there is a strong positive association between the extent of political competition and outcomes.
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Pinaire, Jessica, Etienne Chabert, Jérôme Azé, Sandra Bringay, Pascal Poncelet, and Paul Landais. "Prediction of In-Hospital Mortality from Administrative Data: A Sequential Pattern Mining Approach." In Studies in Health Technology and Informatics. IOS Press, 2021. http://dx.doi.org/10.3233/shti210167.
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Study of trajectory of care is attractive for predicting medical outcome. Models based on machine learning (ML) techniques have proven their efficiency for sequence prediction modeling compared to other models. Introducing pattern mining techniques contributed to reduce model complexity. In this respect, we explored methods for medical events’ prediction based on the extraction of sets of relevant event sequences of a national hospital discharge database. It is illustrated to predict the risk of in-hospital mortality in acute coronary syndrome (ACS). We mined sequential patterns from the French Hospital Discharge Database. We compared several predictive models using a text string distance to measure the similarity between patients’ patterns of care. We computed combinations of similarity measurements and ML models commonly used. A Support Vector Machine model coupled with edit-based distance appeared as the most effective model. Indeed discrimination ranged from 0.71 to 0.99, together with a good overall accuracy. Thus, sequential patterns mining appear motivating for event prediction in medical settings as described here for ACS.
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Andersson, Nils. "Whispers from the Big Bang." In Gravitational-Wave Astronomy, 581–624. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198568032.003.0022.
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This chapter discusses gravitational waves in the context of cosmology, starting from a summary of the standard model for cosmology—Lambda CDM. The cosmological redshift is introduced and different ways to measure distances in an expanding universe are considered, including the idea of using binary mergers as standard ‘sirens’. Different stochastic backgrounds are considered and the use of pulsar timing arrays to detect gravitational waves is introduced. The chapter ends with a discussion of cosmological backgrounds due to quantum fluctuations, phase transitions, and cosmic strings
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Syrowatka, Ania, Troy Li, Mica Curtin-Bowen, Avery Pullman, Stuart R. Lipsitz, Michael Sainlaire, Wenyu Song, et al. "Testing a Novel Inpatient Respiratory Depression Electronic Clinical Quality Measure (eCQM) for Orthopedic Practice in Two Large U.S. Health Systems." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220104.
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The objective of this study was to assess the feasibility of using an electronic clinical quality measure (eCQM) to assess inpatient respiratory depression rates following elective primary total hip or total knee arthroplasty using data routinely collected in electronic health records. Measure testing was conducted at two large urban, academic health systems – Mass General Brigham and a geographically distant system in southern U.S. The risk-adjusted inpatient respiratory depression rates were 3.83 and 2.73% for the two health systems, respectively. Clinician group rates ranged from 1.40 to 4.35%, demonstrating opportunity for improvement. Both the data and measure specifications showed strong reliability and validity to allow for calculation of accurate and comparable rates of inpatient respiratory depression.
Conference papers on the topic "String distance measures"
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Scherrer, Yves. "Adaptive string distance measures for bilingual dialect lexicon induction." In the 45th Annual Meeting of the ACL: Student Research Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2007. http://dx.doi.org/10.3115/1557835.1557847.
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Boehmer, Niclas, Piotr Faliszewski, Rolf Niedermeier, Stanisław Szufa, and Tomasz Wąs. "Understanding Distance Measures Among Elections." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/15.
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Motivated by putting empirical work based on (synthetic) election data on a more solid mathematical basis, we analyze six distances among elections, including, e.g., the challenging-to-compute but very precise swap distance and the distance used to form the so-called map of elections. Among the six, the latter seems to strike the best balance between its computational complexity and expressiveness.
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Rodriguez, Andres, Kevin Logan, James Nickles, and Greg Carlson. "Enhanced Method for Dimensional Measurement of Oilfield Tubulars to Optimize Operations and Minimize Risk Factors." In IADC/SPE International Drilling Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/208728-ms.
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Abstract Technological advances in the nondestructive evaluation of Oil Country Tubular Goods (OCTG) have brought about enhanced methods to minimize risk factors associated with the drilling or transport of oil and natural gas. This paper focuses on a multidimensional, nondestructive testing (NDT) inspection and measurement package combining wall thickness and outer diameter (OD) measurement data into a single inspection report per tubular. This method of dimensional measurement is performed on the front end of a project, providing end users with numerous benefits from a cost and time perspective, as well as the critical data needed to optimize operations. The package provides high-resolution inspection data for the manufacturer or end user, yielding higher precision burst and collapse strength predictions than previously available. Other benefits of this method include optimization of material placement in casing string design, estimation of cementing fluid volume, and downhole tool clearances among other applications. Confidence and safety levels of burst and collapse ratings are of particular interest to drilling engineers. The wall thickness variations and tubular eccentricity are measured using an automated, nondestructive ultrasonic testing system, utilizing compression wave transducers. The OD measurement is acquired using an automated, nondestructive laser-based testing system. Laser-based testing uses two laser-scan micrometers positioned horizontal to the tubular and 180° apart (Fig. 1). Each laser measures the distance between the tubular and the receiver. These two measurements are combined to calculate the tubular OD. The level of accuracy provided by this technology continues to push the industry forward with higher quality tubulars ranging from the mills to end users.
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Yang, Qinshan, Kuang Qin, Jeff Olson, and Marvin Rourke. "THROUGH-TUBING CASING DEFORMATION AND TUBING ECCENTRICITY IMAGE TOOL FOR WELL INTEGRITY MONITORING AND PLUG-ABANDONMENT." In 2021 SPWLA 62nd Annual Logging Symposium Online. Society of Petrophysicists and Well Log Analysts, 2021. http://dx.doi.org/10.30632/spwla-2021-0045.
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Casing deformation and tubing eccentricity is a concern in the oil and gas industry for safety and operational reasons. Casing deformation or tubing eccentricity originates from various sources such as well completion, corrosion, formation swelling, collapse, salt dome creep, etc. It is important to implement a well-integrity surveillance program covering all of the casing and tubing strings for the full well life-cycle from initial completion to abandonment. However, there has been no effective logging method to evaluate though-tubing the condition of the casing string for deformation and eccentricity. This paper describes a new Deformation-and-Eccentricity (DEC) tool which is based on electromagnetic technology and designed to measure casing deformation and tubing eccentricity while logging inside completion tubing. The DEC tool generates a unique compressed-and-focused magnetic field which provides increased Signal-to-Noise Ratio (SNR) and employs an array of magnetic sensors to measure the magnetic flux density distributions azimuthally around the tool. The tool’s compressed-and-focused magnetic field is designed to (1) saturate the magnetic flux of the tubing and (2) inject more magnetic flux into the first casing behind the tubing, (3) to increase signal measurement sensitivity and SNR. The sensor matrix measures flux density changes which correspond to variations in distance between tubing and casing. The high resolution azimuthal magnetic sensor matrix delivers high accuracy measurements, which are used to image the flux density changes. A finite element based forward modeling and an optimized Gaussian Processes Regression method has been developed to process the raw logging data. DEC has a built-in orientation measurement based on gyro and accelerometers that are used to align the deformation and eccentricity images and index curves, as well as the tubing thickness image. The tool specifications as 1% of eccentricity ratio and 5% of deformation ratio accuracy in the range of casing OD up to 13-3/8”. DEC technology provides an advanced answer product for through-tubing casing deformation and eccentricity measurements in downhole well-integrity and plug-abandonment applications. When combined with other well-integrity measurements such as multi-finger caliper and multi-pipe thickness log tool a complete well integrity evaluation can be achieved throughout the life cycle of a well. For example, significant casing deformation can often indicate the potentially damaged cement behind the casing. Other applications for the technology include tubing clamp location for fiber-optics cables and control lines, and the orientation of multi-string tubing completions, etc. Performances of the tool have been validated through research simulations, lab tests, and field trials. The paper includes a field case study of a deviated gas production well with tubing buckling and casing micro-dogleg.
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Park, Jungseo, Seunghwan Mun, Chungmin Hyun, Byungkwon Kang, and Kwanghee Ko. "Similarity Assessment Method for Automated Curved Plate Forming." In SNAME 5th World Maritime Technology Conference. SNAME, 2015. http://dx.doi.org/10.5957/wmtc-2015-240.
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In this paper, a novel similarity estimation method for two shapes in the automated thermal forming is proposed. One shape is given as a CAD surface, and the other is given as a set of points measured points. These two shapes are registered with respect to a reference coordinate system so that they are aligned as closely as possible using the ICP based method. Three geometric properties are considered in the method. The first property is the distance between them. At each measured point, the closest distance to the CAD surface is computed, and the defined tolerance for the distances is used as a similarity measure. The second measure is the average distance of the minimum distances to the CAD surface at the measured points. The third one is the average of the bending strain values at the measured points and at the points on the CAD surface that are orthogonal projection points of the measured ones. The proposed similarity is computed as the linear combination of the three properties with weight values, which are determined empirically. Extensive experiments show that the proposed similarity method successfully computes the similarity of a plate to its CAD shape in the forming process.
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Hill, Reginald J., and James H. Churnside. "Joint statistics of irradiance and its duration measured in strong refractive turbulence." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.fa9.
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We measured the time series of irradiance from a diverged He-Ne laser using 3- and 7-mm receiver aperture sizes that simulated the day-adapted and night-adapted human pupil. The propagation range was 1 km at a height of 2 m above flat grassland. The data are within the saturation-of-scintillation regime wherein the irradiance variance decreases with further increases of propagation distance and refractive turbulence strength.
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Xu, Chun, and Shuhui Li. "Correlation Between Strain and Exfoliating Performance of Galvannealed DP Steels." In ASME 2006 International Manufacturing Science and Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/msec2006-21021.
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The galvannealed dual-phase steels are used in automotive applications. However, galvannealed coating is often exfoliated when it is in the pressing process. Galvannealed exfoliation is examined as a function of strain state using double reserve Olsen test to simulate forming process. Distances of punch in first and second reverse Olsen tests are changed to used to generate other strain state. The circle grids are etched on sheet to measure strain. Significant exfoliating is encountered in biaxial compress strain zone while no exfoliating occurred in biaxial tensile strain zone. Exfoliating is measured at specific locations and correlated with strains in those locations. An exfoliating map is generated in strain space.
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PFINGSTL, SIMON, OLAF TUSCH, and MARKUS ZIMMERMANN. "COMPARISON OF ERROR MEASURES AND MACHINE LEARNING METHODS FOR STRAIN-BASED STRUCTURAL HEALTH MONITORING." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36289.
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The development of aircraft structures requires many fatigue tests. These tests are usually carried out to validate the corresponding finite element and damage models and to prove the expected damage-tolerant behavior. Monitoring aircraft structures requires experienced staff and is very time-consuming and expensive as the recurring inspection of the structure is a tedious task. We propose a machine learning-based approach that exploits continuous load and strain measurement data to support structural health monitoring and to shift the inspection program towards predictive maintenance. The machine learning model is used for mapping loads onto local strains. With the trained model, different error measures between current measurements and the predicted values are determined. When a specific threshold value based on an error confidence level is exceeded, an alarm is set off, and appropriate actions can be taken. The approach is applied to several fatigue tests with two different types of structures and damage mechanisms. Various error measures and models are compared. The paper shows that, first, simple error measures, such as the root mean squared error, are sufficient and even outperform more sophisticated error distances for detecting cracks with continuous strain measurements. Second, the standard deviation of strain or rather the load-strain slope is a key feature to detect cracks. And third, machine learning models enable structural health monitoring with sensors that even have only small strain values.
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Zvyagin, Petr. "On Autocorrelation of Ice Loads, Measured in Ice Tank Experiments." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54436.
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Temporal dynamics of ice loads, which are measured with high sampling rate in experiments in ice tank, usually show strong autocorrelation. At the moment it is lack of study on autocorrelation function (ACF) of ice loads time series. In this paper the stochastic processes approach will be applied to analyze autocorrelation of ice loads. Stochastic models for ice loads, developed earlier by the author, allow determining the distribution law and stationarity (in wide sense) for some of such time series in statistically confident manner. That allows conducting further study of those time series ACF. For analysis and correct sampling rate choice it is important to know the time interval, which separates two statistically independent data points in time series. The algorithm for finding of such interval for time series with normal and lognormal distribution was developed in the paper. That algorithm was applied to find independence distance for global loads records, obtained in experiments with cylindrical models in ice tank of Krylov State Research Centre (St. Petersburg). The independence distance for those time series occurred to be 0,07–0,35 sec. That distance had increased with increasing of indenter diameter. Obtained results are discussed.
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Noronha, Dauro Braga, Ricardo Rodrigues Martins, Breno Pinheiro Jacob, and Eduardo de Souza. "Some Remarks on the Strain Based Assessment of Pipeline Dents." In 2008 7th International Pipeline Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ipc2008-64136.
Full textAbstract:
In order to use the method to estimate strain in dents proposed in Appendix R of ASME B31.8 – Gas Transmission and Distribution Piping Systems – 2003 Edition, in a previous paper the authors used fourth-order B-spline curves to approximate the dent profile in both longitudinal and circumferential directions. This approach proved to be effective to estimate bending strains when the coordinates of the deepest point of the dent are known. This paper studies the impact of the distance between the closest ILI tool sensor and the dent apex on the measured dent depth and on the circumferential bending strain. The results obtained were tested against a set of nonlinear finite element analyses of dented pipelines carried out at PETROBRAS R&D Center. It was concluded that the number of sensors of the ILI tool, and consequently the maximum possible angular distance of the closest sensor in relation to the deepest point of the dent, plays a decisive role on the exactness of the results achieved. It is also mentioned that the equations to estimate the total strain in the inner and outer surface of the pipe wall presented in Appendix R contains a conceptual error and therefore shall be revised. Furthermore, longitudinal membrane strains obtained using the formula proposed in Appendix R were compared to finite element results. The comparison showed that directions on how to measure the dent length should be incorporated into the ASME B31.8 Code.
Reports on the topic "String distance measures"
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Iselin, Columbus O'Donnell. Summary of bathythermograph observations from the western North Atlantic : October 1940 - December 1941. Woods Hole Oceanographic Institution, December 2022. http://dx.doi.org/10.1575/1912/29563.
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The range of submarine detection is frequently limited by the refraction produced by vertical temperature gradients in the superficial layers of the ocean. In order to measure these temperature gradients and thus to permit predictions of the range, the bathythermograph was developed and is now being used on a considerable number of anti-submarine vessels, while a somewhat modified version of the instrument is being tried out on submarines. Some 6675 bathythermograph observations from the western North Atlantic have been examined in order to determine how frequently such observations should be made so that within practical limits and anti-submarine vessel may at all times know the assured range of its sound gear. The occurrence of the four basic types of refraction patterns is shown by a series of six charts. For all but one of these patterns the range can be rather quickly and easily estimated from simple tables; but when the so-called afternoon effect is encountered, which is on the average about 20% of the time, a more complete analysis is necessary. It is found that under the most unfavorable circumstances, that is, in mid-summer and near the edges of a strong current system, there is about one chance in three that the refraction pattern will chance significantly in a distance of four miles. At other times of year and in areas where horizontal variations in temperature are less pronounced a single bathythermograph observation can be considered representative of a much larger area. It is also shown that in the western North Atlantic about 92% of the time in summer and about 34% of the time in winter the assured range of submarine detection is limited by refraction to less than 2500 yards.
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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.
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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.