Relevant bibliographies by topics / Frequent pattern analysis

Academic literature on the topic 'Frequent pattern analysis'

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Published: 10 March 2023
Last updated: 11 March 2023

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Journal articles on the topic "Frequent pattern analysis"

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Giri, Ritesh, Ananta Bhatt, and Aadhya Bhatt. "Frequent Pattern Mining Algorithms Analysis." International Journal of Computer Applications 145, no. 9 (July 15, 2016): 33–36. http://dx.doi.org/10.5120/ijca2016910763.

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Stefanowitsch, Anatol. "Paradigmatic pattern analysis." Yearbook of the German Cognitive Linguistics Association 8, no. 1 (October 27, 2020): 119–40. http://dx.doi.org/10.1515/gcla-2020-0008.

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AbstractThe phrase Sprache ist der Schlüssel zur Integration (“language is the key to integration”) is found frequently in the discourse around immigration in the German-speaking countries. Based on a corpus-linguistic analysis of this phrase, this paper proposes the existence of a particular type of constructional idiom I refer to as ‘paradigmatic pattern’. Like a metaphorical pattern (in the sense of Metaphorical Pattern Analysis), a paradigmatic pattern establishes a correspondence between a word occurring in a particular slot of the idiom and another word more typical of that slot, contributing to a conceptual mapping between the domains instantiated by these words. Unlike in the case of metaphorical patterns, the domain evoked by the paradigmatic pattern is not the domain in which the pattern occurs in its literal meaning, but a domain evoked by a highly frequent collexeme in one of the slots. As in the case of metaphorical patterns, however, this collexeme contributes (aspects of) its meaning even when it is replaced by another word. I suggest a generalized version of Metaphorical Pattern Analysis, referred to as Paradigmatic Pattern Analysis, to deal with such expressions.
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Umar, Aqsa, Naeem Ahemd Mahoto, Sania Bhatti, and Sapna Rathi. "Analysis of Covid-19 Genome Sequences based on Geo-Locations." Pakistan Journal of Engineering and Technology 4, no. 4 (December 22, 2021): 41–45. http://dx.doi.org/10.51846/vol4iss4pp41-45.

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The COVID-19 pandemic has become a major worldwide serious health risk of the current 21st century. It is necessary to examine the genomic sequences of the deadly virus COVID-19 strains to fully understand the virus’s behavior, origin, and how rapidly it mutates. This paper addresses the analysis of the COVID-19 genome sequences CGS of China, Pakistan, and India. In this research, we have looked at the usage of sequential pattern mining (SPM), a closed sequential pattern technique to discover valuable information from COVID-19 genomic sequences. The analysis is performed on the three strains of genome sequences. First, the sequences data files of genome sequences are being transformed to the computer-readable corpus of CGS and then the SPM technique is applied to discover the frequent patterns of nucleotides. Second, Frequent codons of Amino acids are extracted from three strains of genome sequences. Third, we have evaluated the performance of the proposed approach in terms of time execution, the number of frequent patterns, and memory consumption. Obtained results suggest that the codon of Threonine amino acid ACA with support 1576 in Pakistan is the most frequent pattern from the other two strains of CGS. Furthermore, when the user minimum threshold value is low, the closed sequential pattern mining using sparse and vertical id-lists CloFAST algorithm performance evaluates that a high number of frequent patterns consumes more time and memory
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Vyas, Heli. "A Comparative Analysis of Frequent Pattern Mining Algorithms." International Journal for Research in Applied Science and Engineering Technology V, no. XI (November 23, 2017): 3010–12. http://dx.doi.org/10.22214/ijraset.2017.11415.

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Ożdżyński, Piotr. "USING FREQUENT PATTERN MINING ALGORITHMS IN TEXT ANALYSIS." Information System in Management 6, no. 3 (September 30, 2017): 213–22. http://dx.doi.org/10.22630/isim.2017.6.3.19.

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Ożdżyński, Piotr. "USING FREQUENT PATTERN MINING ALGORITHMS IN TEXT ANALYSIS." Information System in Management 6, no. 3 (September 30, 2017): 213–22. http://dx.doi.org/10.22630/isim.2017.6.3.5.

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Shou, Zhenyu, and Xuan Di. "Similarity analysis of frequent sequential activity pattern mining." Transportation Research Part C: Emerging Technologies 96 (November 2018): 122–43. http://dx.doi.org/10.1016/j.trc.2018.09.018.

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Santoro, Diego, Andrea Tonon, and Fabio Vandin. "Mining Sequential Patterns with VC-Dimension and Rademacher Complexity." Algorithms 13, no. 5 (May 18, 2020): 123. http://dx.doi.org/10.3390/a13050123.

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Sequential pattern mining is a fundamental data mining task with application in several domains. We study two variants of this task—the first is the extraction of frequent sequential patterns, whose frequency in a dataset of sequential transactions is higher than a user-provided threshold; the second is the mining of true frequent sequential patterns, which appear with probability above a user-defined threshold in transactions drawn from the generative process underlying the data. We present the first sampling-based algorithm to mine, with high confidence, a rigorous approximation of the frequent sequential patterns from massive datasets. We also present the first algorithms to mine approximations of the true frequent sequential patterns with rigorous guarantees on the quality of the output. Our algorithms are based on novel applications of Vapnik-Chervonenkis dimension and Rademacher complexity, advanced tools from statistical learning theory, to sequential pattern mining. Our extensive experimental evaluation shows that our algorithms provide high-quality approximations for both problems we consider.
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Lee, Gangin, Unil Yun, and Kyung-Min Lee. "Analysis of tree-based uncertain frequent pattern mining techniques without pattern losses." Journal of Supercomputing 72, no. 11 (August 19, 2016): 4296–318. http://dx.doi.org/10.1007/s11227-016-1847-z.

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Ahmad, Munir, Umar Farooq, Atta-Ur-Rahman, Abdulrahman Alqatari, Sujata Dash, and Ashish Kr Luhach. "Investigating TYPE constraint for frequent pattern mining." Journal of Discrete Mathematical Sciences and Cryptography 22, no. 4 (May 19, 2019): 605–26. http://dx.doi.org/10.1080/09720529.2019.1637158.

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Dissertations / Theses on the topic "Frequent pattern analysis"

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Pragarauskaitė, Julija. "Frequent pattern analysis for decision making in big data." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2013~D_20130701_092451-80961.

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Huge amounts of digital information are stored in the World today and the amount is increasing by quintillion bytes every day. Approximate data mining algorithms are very important to efficiently deal with such amounts of data due to the computation speed required by various real-world applications, whereas exact data mining methods tend to be slow and are best employed where the precise results are of the highest important. This thesis focuses on several data mining tasks related to analysis of big data: frequent pattern mining and visual representation. For mining frequent patterns in big data, three novel approximate methods are proposed and evaluated on real and artificial databases: • Random Sampling Method (RSM) creates a random sample from the original database and makes assumptions on the frequent and rare sequences based on the analysis results of the random sample. A significant benefit is a theoretical estimate of classification errors made by this method using standard statistical methods. • Multiple Re-sampling Method (MRM) is an improved version of RSM method with a re-sampling strategy that decreases the probability to incorrectly classify the sequences as frequent or rare. • Markov Property Based Method (MPBM) relies upon the Markov property. MPBM requires reading the original database several times (the number equals to the order of the Markov process) and then calculates the empirical frequencies using the Markov property. For visual representation... [to full text]
Didžiuliai informacijos kiekiai yra sukaupiami kiekvieną dieną pasaulyje bei jie sparčiai auga. Apytiksliai duomenų tyrybos algoritmai yra labai svarbūs analizuojant tokius didelius duomenų kiekius, nes algoritmų greitis yra ypač svarbus daugelyje sričių, tuo tarpu tikslieji metodai paprastai yra lėti bei naudojami tik uždaviniuose, kuriuose reikalingas tikslus atsakymas. Ši disertacija analizuoja kelias duomenų tyrybos sritis: dažnų sekų paiešką bei vizualizaciją sprendimų priėmimui. Dažnų sekų paieškai buvo pasiūlyti trys nauji apytiksliai metodai, kurie buvo testuojami naudojant tikras bei dirbtinai sugeneruotas duomenų bazes: • Atsitiktinės imties metodas (Random Sampling Method - RSM) formuoja pradinės duomenų bazės atsitiktinę imtį ir nustato dažnas sekas, remiantis atsitiktinės imties analizės rezultatais. Šio metodo privalumas yra teorinis paklaidų tikimybių įvertinimas, naudojantis standartiniais statistiniais metodais. • Daugybinio perskaičiavimo metodas (Multiple Re-sampling Method - MRM) yra RSM metodo patobulinimas, kuris formuoja kelias pradinės duomenų bazės atsitiktines imtis ir taip sumažina paklaidų tikimybes. • Markovo savybe besiremiantis metodas (Markov Property Based Method - MPBM) kelis kartus skaito pradinę duomenų bazę, priklausomai nuo Markovo proceso eilės, bei apskaičiuoja empirinius dažnius remdamasis Markovo savybe. Didelio duomenų kiekio vizualizavimui buvo naudojami pirkėjų internetu elgsenos duomenys, kurie analizuojami naudojant... [toliau žr. visą tekstą]
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Nunna, Shinjini. "Using Association Analysis for Medical Diagnoses." Scholarship @ Claremont, 2016. http://scholarship.claremont.edu/scripps_theses/808.

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In order to fully examine the application of association analysis to medical data for the purpose of deriving medical diagnoses, we survey classical association analysis and approaches, the current challenges faced by medical association analysis and proposed solutions, and finally culminate this knowledge in a proposition for the application of medical association analysis to the identification of food intolerance. The field of classical association analysis has been well studied since its introduction in the seminal paper on market basket research in the 1990's. While the theory itself is relatively simple, the brute force approach is prohibitively expensive and thus, creative approaches utilizing various data structures and strategies must be explored for efficiency. Medical association analysis is a burgeoning field with various focuses, including diagnosis systems and gene analysis. There are a number of challenges faced in the field, primarily stemming from characteristics of analysis of complex, voluminous and high dimensional medical data. We examine the challenges faced in the pre-processing, analysis and post-processing phases, and corresponding solutions. Additionally, we survey proposed measures for ensuring the results of medical association analysis will hold up to medical diagnosis standards. Finally, we explore how medical association analysis can be utilized to identify food intolerances. The proposed analysis system is based upon a current method of diagnosis used by medical professionals, and seeks to eliminate manual analysis, while more efficiently and intelligently identifying interesting, and less obvious patterns between patients' food consumption and symptoms to propose a food intolerance diagnosis.
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Almuhisen, Feda. "Leveraging formal concept analysis and pattern mining for moving object trajectory analysis." Thesis, Aix-Marseille, 2018. http://www.theses.fr/2018AIXM0738/document.

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Cette thèse présente un cadre de travail d'analyse de trajectoires contenant une phase de prétraitement et un processus d’extraction de trajectoires d’objets mobiles. Le cadre offre des fonctions visuelles reflétant le comportement d'évolution des motifs de trajectoires. L'originalité de l’approche est d’allier extraction de motifs fréquents, extraction de motifs émergents et analyse formelle de concepts pour analyser les trajectoires. A partir des données de trajectoires, les méthodes proposées détectent et caractérisent les comportements d'évolution des motifs. Trois contributions sont proposées : Une méthode d'analyse des trajectoires, basée sur les concepts formels fréquents, est utilisée pour détecter les différents comportements d’évolution de trajectoires dans le temps. Ces comportements sont “latents”, "emerging", "decreasing", "lost" et "jumping". Ils caractérisent la dynamique de la mobilité par rapport à l'espace urbain et le temps. Les comportements détectés sont visualisés sur des cartes générées automatiquement à différents niveaux spatio-temporels pour affiner l'analyse de la mobilité dans une zone donnée de la ville. Une deuxième méthode basée sur l'extraction de concepts formels séquentiels fréquents a également été proposée pour exploiter la direction des mouvements dans la détection de l'évolution. Enfin, une méthode de prédiction basée sur les chaînes de Markov est présentée pour prévoir le comportement d’évolution dans la future période pour une région. Ces trois méthodes sont évaluées sur ensembles de données réelles . Les résultats expérimentaux obtenus sur ces données valident la pertinence de la proposition et l'utilité des cartes produites
This dissertation presents a trajectory analysis framework, which includes both a preprocessing phase and trajectory mining process. Furthermore, the framework offers visual functions that reflect trajectory patterns evolution behavior. The originality of the mining process is to leverage frequent emergent pattern mining and formal concept analysis for moving objects trajectories. These methods detect and characterize pattern evolution behaviors bound to time in trajectory data. Three contributions are proposed: (1) a method for analyzing trajectories based on frequent formal concepts is used to detect different trajectory patterns evolution over time. These behaviors are "latent", "emerging", "decreasing", "lost" and "jumping". They characterize the dynamics of mobility related to urban spaces and time. The detected behaviors are automatically visualized on generated maps with different spatio-temporal levels to refine the analysis of mobility in a given area of the city, (2) a second trajectory analysis framework that is based on sequential concept lattice extraction is also proposed to exploit the movement direction in the evolution detection process, and (3) prediction method based on Markov chain is presented to predict the evolution behavior in the future period for a region. These three methods are evaluated on two real-world datasets. The obtained experimental results from these data show the relevance of the proposal and the utility of the generated maps
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4

Pragarauskaitė, Julija. "Dažnų sekų analizė sprendimų priėmimui labai didelėse duomenų bazėse." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2013~D_20130701_092337-79289.

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Didžiuliai informacijos kiekiai yra sukaupiami kiekvieną dieną pasaulyje bei jie sparčiai auga. Apytiksliai duomenų tyrybos algoritmai yra labai svarbūs analizuojant tokius didelius duomenų kiekius, nes algoritmų greitis yra ypač svarbus daugelyje sričių, tuo tarpu tikslieji metodai paprastai yra lėti bei naudojami tik uždaviniuose, kuriuose reikalingas tikslus atsakymas. Ši disertacija analizuoja kelias duomenų tyrybos sritis: dažnų sekų paiešką bei vizualizaciją sprendimų priėmimui. Dažnų sekų paieškai buvo pasiūlyti trys nauji apytiksliai metodai, kurie buvo testuojami naudojant tikras bei dirbtinai sugeneruotas duomenų bazes: • Atsitiktinės imties metodas (Random Sampling Method - RSM) formuoja pradinės duomenų bazės atsitiktinę imtį ir nustato dažnas sekas, remiantis atsitiktinės imties analizės rezultatais. Šio metodo privalumas yra teorinis paklaidų tikimybių įvertinimas, naudojantis standartiniais statistiniais metodais. • Daugybinio perskaičiavimo metodas (Multiple Re-sampling Method - MRM) yra RSM metodo patobulinimas, kuris formuoja kelias pradinės duomenų bazės atsitiktines imtis ir taip sumažina paklaidų tikimybes. • Markovo savybe besiremiantis metodas (Markov Property Based Method - MPBM) kelis kartus skaito pradinę duomenų bazę, priklausomai nuo Markovo proceso eilės, bei apskaičiuoja empirinius dažnius remdamasis Markovo savybe. Didelio duomenų kiekio vizualizavimui buvo naudojami pirkėjų internetu elgsenos duomenys, kurie analizuojami naudojant... [toliau žr. visą tekstą]
Huge amounts of digital information are stored in the World today and the amount is increasing by quintillion bytes every day. Approximate data mining algorithms are very important to efficiently deal with such amounts of data due to the computation speed required by various real-world applications, whereas exact data mining methods tend to be slow and are best employed where the precise results are of the highest important. This thesis focuses on several data mining tasks related to analysis of big data: frequent pattern mining and visual representation. For mining frequent patterns in big data, three novel approximate methods are proposed and evaluated on real and artificial databases: • Random Sampling Method (RSM) creates a random sample from the original database and makes assumptions on the frequent and rare sequences based on the analysis results of the random sample. A significant benefit is a theoretical estimate of classification errors made by this method using standard statistical methods. • Multiple Re-sampling Method (MRM) is an improved version of RSM method with a re-sampling strategy that decreases the probability to incorrectly classify the sequences as frequent or rare. • Markov Property Based Method (MPBM) relies upon the Markov property. MPBM requires reading the original database several times (the number equals to the order of the Markov process) and then calculates the empirical frequencies using the Markov property. For visual representation... [to full text]
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Wang, Chao. "Exploiting non-redundant local patterns and probabilistic models for analyzing structured and semi-structured data." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1199284713.

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Singh, Shailendra. "Smart Meters Big Data : Behavioral Analytics via Incremental Data Mining and Visualization." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35244.

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The big data framework applied to smart meters offers an exception platform for data-driven forecasting and decision making to achieve sustainable energy efficiency. Buying-in consumer confidence through respecting occupants' energy consumption behavior and preferences towards improved participation in various energy programs is imperative but difficult to obtain. The key elements for understanding and predicting household energy consumption are activities occupants perform, appliances and the times that appliances are used, and inter-appliance dependencies. This information can be extracted from the context rich big data from smart meters, although this is challenging because: (1) it is not trivial to mine complex interdependencies between appliances from multiple concurrent data streams; (2) it is difficult to derive accurate relationships between interval based events, where multiple appliance usage persist; (3) continuous generation of the energy consumption data can trigger changes in appliance associations with time and appliances. To overcome these challenges, we propose an unsupervised progressive incremental data mining technique using frequent pattern mining (appliance-appliance associations) and cluster analysis (appliance-time associations) coupled with a Bayesian network based prediction model. The proposed technique addresses the need to analyze temporal energy consumption patterns at the appliance level, which directly reflect consumers' behaviors and provide a basis for generalizing household energy models. Extensive experiments were performed on the model with real-world datasets and strong associations were discovered. The accuracy of the proposed model for predicting multiple appliances usage outperformed support vector machine during every stage while attaining accuracy of 81.65\%, 85.90\%, 89.58\% for 25\%, 50\% and 75\% of the training dataset size respectively. Moreover, accuracy results of 81.89\%, 75.88\%, 79.23\%, 74.74\%, and 72.81\% were obtained for short-term (hours), and long-term (day, week, month, and season) energy consumption forecasts, respectively.
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MATOS, MARCILIO CASTRO DE. "SEISMIC PATTERN RECOGNITION USING TIME-FREQUENCY ANALYSES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5081@1.

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INSTITUTO MILITAR DE ENGENHARIA
Independente da metodologia adotada para realizar análise de fácies sísmicas, a segmentação temporal e espacial da região do reservatório deve ser realizada cuidadosamente. A confiança no resultado da interpretação depende da complexidade do sistema geológico, da qualidade dos dados sísmicos, e da experiência do intérprete. Portanto, qualquer erro de interpretação pode levar a resultados incoerentes. Especialmente, a análise de fácies sísmicas utilizando formas de onda do sinal na região do reservatório é bastante sensível a ruídos de interpretação. Sabe-se que variações no conteúdo de freqüência dos traços sísmicos podem estar associadas às informações de refletividade da sub-superfície. Conseqüentemente, análises conjuntas em tempo - freqüência podem levar a formas não convencionais para a caracterização de reservatórios. Especificamente, esta tese propõe o uso das propriedades em tempo - freqüência, obtidas através do algoritmo de matching pursuit, e das singularidades detectadas e caracterizadas via transformada wavelet, como ferramenta para detecção de eventos sísmicos e para análise não supervisionada de fácies sísmicas quando associadas ao agrupamento dos mapas auto organizáveis de Kohonen.
Independent of the adopted methodology to perform the seismic facies analysis, the geological oriented spatial and temporal segmentation of the reservoir region should be carefully done. Depending on the complexity of the reservoir system, seismic data quality, and the experience of the interpreter, the level of confidence in an interpretation can vary from very high to very low. Therefore, any interpretation error could lead to wrong or noisy results. Specially, when using seismic trace shapes, defined by the values of the seismic samples along each segmented trace, as the seismic input attributes to the chosen seismic facies algorithm. These facies analysis artifacts are introduced because seismic waveform in the reservoir delimited area changes quickly as a function of the interpretation, then waveforms with almost the same shape could be assigned to different classes due only to their different phases. It is known that variations of the frequency content of a seismic trace with time carry information about the properties of the subsurface reflectivity sequence. Consequently, seismic trace time- frequency analyses could provide an unconventional way to reservoir characterization. Specifically, in this work we propose to use the time-frequency properties of the atoms obtained after the matching pursuit signal representation and the singularities identified by wavelet transform, jointly with Self Organizing Maps as an unsupervised seismic facies analyses system.
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IBARAKI, Toshihide, Endre BOROS, Mutsunori YAGIURA, and Kazuya HARAGUCHI. "A Randomness Based Analysis on the Data Size Needed for Removing Deceptive Patterns." Institute of Electronics, Information and Communication Engineers, 2008. http://hdl.handle.net/2237/15011.

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Wang, Joshua Kevin. "Identification, Analysis, and Control of Power System Events Using Wide-Area Frequency Measurements." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26250.

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The power system has long been operated in a shroud of introspection. Only recently have dynamic, wide-area time synchronized grid measurements brought to light the complex relationships between large machines thousands of miles apart. These measurements are invaluable to understanding the health of the system in real time, for disturbances to the balance between generation and load are manifest in the propagation of electromechanical waves throughout the grid. The global perspective of wide-area measurements provides a platform from which the destructive effects of these disturbances can be avoided. Virginia Tech's distributed network of low voltage frequency monitors, FNET, is able to track these waves as they travel throughout the North American interconnected grids. In contrast to other wide-area measurement systems, the ability to easily measure frequency throughout the grid provides a way to identify, locate, and analyze disturbances with high dynamic accuracy. The unique statistical properties of wide-area measurements require robust tools in order to accurately understand the nature of these events. Expert systems and data conditioning can then be used to quantify the magnitude and location of these disturbances without requiring any knowledge of the system state or topology. Adaptive application of these robust methods form the basis for real-time situational awareness and control. While automated control of the power system rarely utilize wide-area measurements, global insight into grid behavior can only improve disturbance rejection.
Ph. D.
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FURUHASHI, Takeshi, Tomohiro YOSHIKAWA, Makoto SUZUKI, 武. 古橋, 大弘 吉川, and 誠. 鈴木. "コレスポンデンス分析を用いた文書検索に関する検討." 日本感性工学会, 2013. http://hdl.handle.net/2237/20711.

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Books on the topic "Frequent pattern analysis"

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Akima, H. A model of a shaped-beam emission pattern of a satellite antenna for interference analysis. [Washington, D.C.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1986.

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Akima, H. A model of a shaped-beam emission pattern of a satellite antenna for interference analysis. [Washington, D.C.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1986.

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Aydin, Berkay, and Rafal A. Angryk. Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories. Springer, 2018.

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A model of a shaped-beam emission pattern of a satellite antenna for interference analysis. [Washington, D.C.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1986.

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Zsiga, Elizabeth C., and One Tlale Boyer. Sebirwa in Contact with Setswana. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190256340.003.0015.

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Setswana, spoken by about 4.5 million people throughout Botswana, is well-known in the literature for “post-nasal devoicing,” in which /b/ and /l/ become [p]‌ and [t] after nasals, contra the expected, phonetically-grounded pattern of post-nasal voicing. Sebirwa, in contrast, has at most 15,000 speakers concentrated in the far eastern corner of the country. Sebirwa is being overwhelmed by Setswana, and in a process of “massive Tswananization,” has borrowed some aspects of post-nasal devoicing. Our analysis, based on fieldwork in the village of Molalatau, shows that the Sebirwa pattern is doubly unexpected: only /b/ devoices, not /d/ and /g/. We attribute the asymmetry to frequency effects from Setswana, where, due to a skewed voicing inventory, the majority of lexical items that exhibit the alternation have underlying /b/. We discuss the implications of this type of borrowing, both for the typology of alternations, and for patterns of language loss.
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Bapteste, Eric, and Gemma Anderson. Intersecting Processes Are Necessary Explanantia for Evolutionary Biology, but Challenge Retrodiction. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198779636.003.0014.

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Processes are ubiquitous in biology and play a key explanatory role in evolutionary biology, where they are frequently depicted by patterns. In particular, phylogenetic trees represent divergence from a last common ancestor with a branching pattern. However, the increasingly recognized underdetermination of phylogenetic trees limits the accuracy of tree-based retrodiction. Even phylogenetic networks, which include additional processes intersecting with vertical descent, still provide incomplete descriptions of evolutionary processes, as they usually miss processes that impact unrelated lineages. Interaction networks highlight the intersection of processes that sustain biological diversity. The complex topology of all these networks further challenges retrodiction. Remarkably, when intersecting processes are involved in evolutionary transitions, they introduce new biological processes on Earth. Processes, and hence the explanantia of evolutionary biology, evolve, which challenges uniformitarian approaches to retrodiction. Despite these difficulties, a yet to be introduced typology of processes would help to analyse the (big) processual picture of life.
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Congendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.

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Event-related potentials (ERPs) can be elicited by a variety of stimuli and events in diverse conditions. This chapter covers the methodology of analyzing and quantifying ERPs in general. Basic models (additive, phase modulation and resetting, potential asymmetry) that account for the generation of ERPs are discussed. The principles and requirements of ensemble time averaging are presented, along with several univariate and multivariate methods that have been proposed to improve the averaging procedure: wavelet decomposition and denoising, spatial, temporal and spatio-temporal filtering. We emphasize basic concepts of principal component analysis, common spatial pattern, and blind source separation, including independent component analysis. We cover practical questions related to the averaging procedure: overlapping ERPs, correcting inter-sweep latency and amplitude variability, alternative averaging methods (e.g., median), and estimation of ERP onset. Some specific aspects of ERP analysis in the frequency domain are surveyed, along with topographic analysis, statistical testing, and classification methods.
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Osman, Gamaleldin M., James J. Riviello, and Lawrence J. Hirsch. EEG in the Intensive Care Unit. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0022.

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The field of continuous electroencephalographic monitoring (cEEG) in the intensive care unit has dramatically expanded over the past two decades. Expansion of cEEG programs led to recognition of the frequent occurrence of electrographic seizures, and complex rhythmic and periodic patterns in various critically ill populations. The majority of electrographic seizures are of nonconvulsive nature, hence the need for cEEG for their identification. Guidelines on when and how to perform cEEG and standardized nomenclature for description of rhythmic and periodic patterns are now available. Quantitative EEG analysis methods depict EEG data in a compressed (hours on one screen) colorful graphical representation, facilitating early identification of key events, recognition of slow, long-term trends, and timely therapeutic intervention. Integration of EEG with other invasive and noninvasive modalities of monitoring brain function provides critical information about the development of secondary neuronal injury, providing a valuable window of opportunity for intervention before irreversible damage ensues.
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Lopes da Silva, Fernando H., and Eric Halgren. Neurocognitive Processes. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0048.

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Transmembrane neuronal currents that embody cognition in the cortex produce magnetoencephalographic and electroencephalographic signals. Frequency-domain analysis reveals standard rhythms with consistent topography, frequency, and cognitive correlates. Time-domain analysis reveals average event-related potentials and field (ERP/ERF) components with consistent topography, latency, and cognitive correlates. Standard rhythms and ERP/ERF components underlie perceiving stimuli; evaluating whether stimuli match predictions, and taking appropriate action when they do not; encoding stimuli to permit semantic processing and then accessing lexical representations and assigning syntactic roles; maintaining information in primary memory; preparing to take an action; and closing processing of an event–response sequence. Sustained mental processes are associated with theta and gamma. Consolidating memories appears to occur mainly during replay of specific firing patterns during sleep spindles and slow oscillations. Biophysical, neuroanatomical, and neurophysiological factors interact to render cognitive rhythms and components particularly sensitive to the large-scale modulatory processes that sequence and integrate higher cortical processing.
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Lowe, John J. Vedic Prose. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198793571.003.0003.

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This chapter provides a detailed account of the transitive noun and adjective categories attested in Vedic Prose. Although the Vedic Prose corpus is larger than that of the Rigveda, there are considerably fewer transitive noun/adjective categories, and relatively few transitive forms. The most commonly transitive adjective category may show some degree of integration into the verbal system as a modal formation. Statistical analysis shows that the patterns found in Rigvedic Sanskrit largely carry over into Vedic Prose. Again, there is a clear correlation between transitivity and predication. As before, different formations and types, occurring with varying frequency as transitive, are carefully examined and exemplified, including again situation-oriented nouns.
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Book chapters on the topic "Frequent pattern analysis"

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Aguilar-Ruiz, Jesús, Domingo Rodríguez -Baena, and Ronnie Alves. "Gene Association Analysis, Frequent-Pattern Mining." In Encyclopedia of Systems Biology, 788–89. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_225.

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Picado Muiño, David, Iván Castro León, and Christian Borgelt. "Fuzzy Frequent Pattern Mining in Spike Trains." In Advances in Intelligent Data Analysis XI, 289–300. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34156-4_27.

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Nohuddin, Puteri N. E., Rob Christley, Frans Coenen, Yogesh Patel, Christian Setzkorn, and Shane Williams. "Frequent Pattern Trend Analysis in Social Networks." In Advanced Data Mining and Applications, 358–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17316-5_35.

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Bathoorn, Ronnie, Monique Welten, Michael Richardson, Arno Siebes, and Fons J. Verbeek. "Frequent Episode Mining to Support Pattern Analysis in Developmental Biology." In Pattern Recognition in Bioinformatics, 253–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16001-1_22.

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Lee, Gangin, and Unil Yun. "Analysis of Recent Maximal Frequent Pattern Mining Approaches." In Advances in Computer Science and Ubiquitous Computing, 873–77. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3023-9_135.

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Acosta-Mendoza, Niusvel, Annette Morales-González, Andrés Gago-Alonso, Edel B. García-Reyes, and José E. Medina-Pagola. "Image Classification Using Frequent Approximate Subgraphs." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 292–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33275-3_36.

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Mandal, Purnendu, John Vong, and Insu Song. "Indonesian Retail Market Analysis Using Frequent Pattern Data Mining." In Managing the Asian Century, 45–55. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-287-585-3_4.

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Acosta-Mendoza, Niusvel, Andrés Gago-Alonso, and José E. Medina-Pagola. "On Speeding up Frequent Approximate Subgraph Mining." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 316–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33275-3_39.

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Deville, Romain, Elisa Fromont, Baptiste Jeudy, and Christine Solnon. "Mining Frequent Patterns in 2D+t Grid Graphs for Cellular Automata Analysis." In Graph-Based Representations in Pattern Recognition, 177–86. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58961-9_16.

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Kontonasios, Kleanthis-Nikolaos, and Tijl DeBie. "Formalizing Complex Prior Information to Quantify Subjective Interestingness of Frequent Pattern Sets." In Advances in Intelligent Data Analysis XI, 161–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34156-4_16.

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Conference papers on the topic "Frequent pattern analysis"

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Cheng, Hong, Xifeng Yan, Jiawei Han, and Chih-Wei Hsu. "Discriminative Frequent Pattern Analysis for Effective Classification." In 2007 IEEE 23rd International Conference on Data Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icde.2007.367917.

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Babu, M. Vinaya, and M. Sreedevi. "Performance Analysis on Advances in Frequent Pattern Growth Algorithm." In 2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI). IEEE, 2022. http://dx.doi.org/10.1109/accai53970.2022.9752650.

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Derouiche, Abir, Abdesslem Layeb, and Zineb Habbas. "Frequent Itemsets Mining with Chemical Reaction Optimization Metaheuristic." In 2018 3rd International Conference on Pattern Analysis and Intelligent Systems (PAIS). IEEE, 2018. http://dx.doi.org/10.1109/pais.2018.8598483.

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Ma, Jun, Guanzhong Dai, and Jing Zhou. "Anomalous Payload Detection System Using Analysis of Frequent Sequential Pattern." In 2009 Fifth International Conference on Information Assurance and Security. IEEE, 2009. http://dx.doi.org/10.1109/ias.2009.34.

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Tong, Ziqi, Husheng Liao, and Xueyun Jin. "A real-time frequent pattern mining algorithm for semi structured data streams." In 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA). IEEE, 2017. http://dx.doi.org/10.1109/icbda.2017.8078822.

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Xylogiannopoulos, Konstantinos F., Reda Alhajj, and Panagiotis Karampelas. "Frequent and non-frequent pattern detection in big data streams: An experimental simulation in 1 trillion data points." In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2016. http://dx.doi.org/10.1109/asonam.2016.7752351.

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Yang, Shuo, Hui Cao, Yanbin Zhang, Longfei Luo, Yiwei Yuan, Qian Xie, and Huihui Zhang. "Variable selection based on frequent pattern tree for spectroscopy quantitative analysis." In 2017 29th Chinese Control And Decision Conference (CCDC). IEEE, 2017. http://dx.doi.org/10.1109/ccdc.2017.7978192.

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Christian, Michael Albert, Nathanael Nathanael, Annisa Mauliani, Ariani Indrawati, Lindung Parningotan Manik, and Zaenal Akbar. "Real Market Basket Analysis using Apriori and Frequent Pattern Tree Algorithm." In IC3INA 2021: The 2021 International Conference on Computer, Control, Informatics and Its Applications. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3489088.3489133.

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Yuan, Gang, Saihua Cai, and Shangbo Hao. "A Novel Weighted Frequent Pattern-Based Outlier Detection Method Applied to Data Stream." In 2019 IEEE 4th International Conference on Cloud Computing and Big Data Analysis (ICCCBDA). IEEE, 2019. http://dx.doi.org/10.1109/icccbda.2019.8725699.

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Shalini and Sanjay Kumar Jain. "A comparative analysis of frequent pattern mining algorithms used for streaming data." In 2017 International Conference on Computing, Communication and Automation (ICCCA). IEEE, 2017. http://dx.doi.org/10.1109/ccaa.2017.8229809.

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Reports on the topic "Frequent pattern analysis"

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Shekhar, Shashi, Pradeep Mohan, Dev Oliver, and Xun Zhou. Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada561517.

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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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Tait, Emma, Pia Ruisi-Besares, Matthias Sirch, Alyx Belisle, Jennifer Pontius, and Elissa Schuett. Technical Report: Monitoring and Communicating Changes in Disturbance Regimes (Version 1.0). Forest Ecosystem Monitoring Cooperative, October 2021. http://dx.doi.org/10.18125/cc0a0l.

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Shifts in disturbance patterns across the Northeast are of increasing concern as the climate continues to change. In particular, changes in patterns of frequency, severity and extent of disturbance event may have detrimental cascading impacts on forest ecosystems and human communities. To explore how changing disturbance regimes might impact future forest health and management it is necessary to understand the historical trends and impacts of disturbance in the region. Although individual types of disturbance have already been analyzed, there is a need for a consolidated overview of the current state of disturbance in northeastern forests. To address this need, the Forest Ecosystem Monitoring Cooperative (FEMC) developed the FEMC: Tracking Shifts in Disturbance Regimes web portal for users to explore changes over time of key disturbance drivers, identify important disturbance responses, and discover where monitoring is happening for both drivers and responses. In collaboration with our advisory committee, we identified key disturbance drivers—flood, high winds, fire, drought, pests—and responses—macroinvertebrates, cold-water fisheries, invasive plants—that are of particular concern in the region. For each of the drivers we identified a suitable regional dataset and analyzed changes over time in frequency, severity, and extent. We also created a structured framework to catalogue programs across the region that are monitoring for these disturbance drivers and responses. Version 1.0 of the FEMC: Tracking Shifts in Disturbance Regimes (https://uvm.edu/femc/disturbance) web portal, first released in October 2021, contains 272 data programs, 11 drivers and three responses. Through the web portal users can browse programs by state, driver type or response type, and explore where monitoring is happening across the region. Driver-specific analyses allow users to quickly see the trends in severity, frequency and extent of selected disturbances and compare the impacts in selected states to regional data. We hope that this collection of programs and the analysis of trends provide researchers and land managers with an easy way to understand the current state of disturbance in northeastern forests that enables them to analyze and plan for future impacts.
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Pradeep Kumar, Kaavya. Reporting in a Warming World: A Media Review. Indian Institute for Human Settlements, 2021. http://dx.doi.org/10.24943/rwwmr08.2021.

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The media plays a critical role in terms of shaping public perceptions, but they have a task on their hands in terms of effectively communicating a subject as vast and complex as climate change. India is among the countries most affected and yet reporting on the subject has been episodic, with peaks around the time of climate summits and in the immediate aftermath of disasters such as cyclones, heatwaves and extreme rainfall events. Through a media review, undertaken as part of the Earth Journalism Network Asia-Pacific Media Grant, we sought to understand patterns of representation in news coverage about urban drought and extreme weather events – predicted to occur more frequently and intensely in a warming world. This report details the methodology we followed, our findings and analyses them in the context of other work done as part of the evolving field of climate change communication.
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Leis, Sherry, and Mary Short. George Washington Carver National Monument plant community report: 2004–2020. Edited by Tani Hubbard. National Park Service, December 2021. http://dx.doi.org/10.36967/nrr-2288500.

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The Heartland Inventory and Monitoring Network completed its sixth year of plant community monitoring at George Washington Carver National Monument in 2020. Plant community monitoring focused on the restored prairie community. We visited seven monitoring sites in each of the six years and collected data on plant species and ground cover. In this report we also included two environmental factors—precipitation and recent fire history—to better understand the vegetation community status and trends. Since 2000, precipitation has often been below the 30-year normal. Moreover, annual precipitation was below normal for all but one of the monitoring years. We found that the drought in 2012 stood out as possibly influencing plant guild cover. Although prairies are adapted to drought, further analyses might reveal more about the role of climate change in these vegetation communities. Fire management also plays an important role in shaping plant communities. Prescribed fire occurrence became more frequent and consistent through the period of plant monitoring. Additional treatments, including herbicide and mowing, also supported a healthy prairie. The prairie plant community continues to be moderately diverse despite recent increases in tree seedlings and small saplings. Species richness in 2012 was different than in two of the six years monitored. However, diversity indices (H′ and J′) were very similar across monitored years. Species guilds (also known as functional groups) exhibited differing patterns. Woody plants, long a concern at the monument, were statistically similar across years. In 2020, grass-like species increased, but grass species appeared to have declined below prior years. Grass cover in 2004 was statistically different (greater) than in 2008 and 2020. The reasons for this are not clear. Of particular interest to the park is the status of two sumac species (Rhus glabra and R. copallinum). These species were in decline as a result of focused management actions since 2012. However, the blackberry species (Rubus spp.) seemed to be replacing the sumac in some sites. In 2020, nonnative species richness and cover were below peak levels, demonstrating management actions have been successful in maintaining low levels. The vegetation monitoring protocol experienced some changes between 2004 and 2020. A key difference was a shift from sampling twice during the field season to sampling only once in a monitoring year. Although a decline in species richness was anticipated, that pattern was not apparent. However, the abundance of grasses may have been affected by the shift in seasonality of sampling. Additionally, we remedied inconsistencies in how tree regeneration was recorded (stem tallies in some cases and cover estimates in other cases). We converted all cover data to stem tallies and density was calculated to be consistent with the protocol. The monument has had success with coordinating fire management and invasive species management. A decrease in sumac across the prairie is evidence of this success. These actions will continue to be important for maintaining the prairie in good condition into the future.
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Farahbod, A. M., and J. F. Cassidy. Temporal variations in coda Q before and after the 2017 Barrow Strait earthquake (Mw 5.9) in Nunavut and the 2012 Haida Gwaii earthquake (Mw 7.8) in British Columbia. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331095.

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In this study, we examine potential temporal changes in coda Q values for two significant Canadian earthquakes in different tectonic environments: the 2017 (Mw 5.9) Barrow Strait earthquake along Canada's northern margin and the 2012 (Mw 7.8) Haida Gwaii subduction earthquake on Canada's west coast. Waveforms from 124 earthquakes (2.0 </= M </= 4.6) for ~30 years prior to the January 8, 2017 Barrow Strait earthquake and 66 events (mainly aftershocks of M 2.0-5.3) in about 4 years after the mainshock recorded by the closest seismic station (RES) of the Canadian National Seismograph Network (CNSN) were utilized in this study. Based on our analysis, overall average of Q0 (Q at 1 Hz) decreased from 92 (before the mainshock) to 81. The most significant decrease in the frequency range between 2 and 16 Hz is observed for areas corresponding to ellipse parameter a2 of 50, 70 and 80 mainly related to aftershock activity. Precursory Q changes could not be evaluated before the mainshock due to the lack of reported seismicity within 100 km of the recording seismic station for almost 2 years from April 2015 to January 2017. Coda Q values before and after the October 28, 2012 Haida Gwaii earthquake in British Columbia show a similar pattern. Waveforms from 249 earthquakes (2.0 </= M </= 4.9) in 2 years before the mainshock and 498 events (2.5 </= M </= 6.3) in 2 years after the mainshock recorded by the three closest seismic stations of the CNSN were utilized. Overall average of Q0 decreased from 89 (before the mainshock) to 69 (station BNB), from 90 to 79 (station DIB) and from 86 to 78 (station VIB). In general, these results are in agreement with other global studies that show a decrease in Q0 following a major earthquake, likely the result of increased fracturing and fluids in the epicentral region.
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Chejanovsky, Nor, Diana Cox-Foster, Victoria Soroker, and Ron Ophir. Honeybee modulation of infection with the Israeli acute paralysis virus, in asymptomatic, acutely infected and CCD colonies. United States Department of Agriculture, December 2013. http://dx.doi.org/10.32747/2013.7594392.bard.

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Honey bee (Apis mellifera) colony losses pose a severe risk to the food chain. The IAPV (Israeli acute paralysis virus) was correlated with CCD, a particular case of colony collapse. Honey bees severely infected with IAPV show shivering wings that progress to paralysis and subsequent death. Bee viruses, including IAPV, are widely present in honey bee colonies but often there are no pathological symptoms. Infestation of the beehive with Varroa mites or exposure to stress factors leads to significant increase in viral titers and fatal infections. We hypothesized that the honey bee is regulating/controlling IAPV and viral infections in asymptomatic infections and this control is broken through "stress" leading to acute infections and/or CCD. Our aims were: 1. To discover genetic changes in IAPV that may affect tissue tropism in the host, and/or virus infectivity and pathogenicity. 2. To elucidate mechanisms used by the host to regulate/ manage the IAPV-infection in vivo and in vitro. To achieve the above objectives we first studied stress-induced virus activation. Our data indicated that some pesticides, including myclobutanil, chlorothalonil and fluvalinate, result in amplified viral titers when bees are exposed at sub lethal levels by a single feeding. Analysis of the level of immune-related bee genes indicated that CCD-colonies exhibit altered and weaker immune responses than healthy colonies. Given the important role of viral RNA interference (RNAi) in combating viral infections we investigated if CCD-colonies were able to elicit this particular antiviral response. Deep-sequencing analysis of samples from CCD-colonies from US and Israel revealed high frequency of small interfering RNAs (siRNA) perfectly matching IAPV, Kashmir bee virus and Deformed wing virus genomes. Israeli colonies showed high titers of IAPV and a conserved RNAi pattern of targeting the viral genome .Our findings were further supported by analysis of samples from colonies experimentally infected with IAPV. Following for the first time the dynamics of IAPV infection in a group of CCD colonies that we rescued from collapse, we found that IAPV conserves its potential to act as one lethal, infectious factor and that its continuous replication in CCD colonies deeply affects their health and survival. Ours is the first report on the dominant role of IAPV in CCD-colonies outside from the US under natural conditions. We concluded that CCD-colonies do exhibit a regular siRNA response that is specific against predominant viruses associated with colony losses and other immune pathways may account for their weak immune response towards virus infection. Our findings: 1. Reveal that preventive measures should be taken by the beekeepers to avoid insecticide-based stress induction of viral infections as well as to manage CCD colonies as a source of highly infectious viruses such as IAPV. 2. Contribute to identify honey bee mechanisms involved in managing viral infections.
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Peru logistics chain analysis. Population Council, 1998. http://dx.doi.org/10.31899/rh1998.1015.

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The inventory module of situation analysis, developed by the Population Council, has been adapted to help generate indicators of logistics system functioning suggested by the Evaluation Project and to provide an analytical framework that permits more accurate estimations of the frequency, location, and patterns of logistics problems. In 1996, the module was implemented in southern Peru. In 1997, the same module was implemented in the province of Santa and two provinces of Huancavelica. Comparable information was obtained from 149 service delivery points (SDPs) in four departments. Data include inventories of contraceptive supplies and materials required for safe delivery of contraception; frequency of contraceptive stockouts in the three months prior to the survey; service and distribution statistics required for calculating number of months of stock on hand; and potential or evident problems with storage practices or conditions. In this paper, data on material stockouts is cross-tabulated with the logistical framework within which each SDP is operating, based on the hypothesis that understanding problems in logistics systems functioning requires knowledge of the context in which SDPs are resupplied. An analysis of logistics systems that incorporates the supply chain may help program managers’ better tackle logistical problems in the future.
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Northern Tornadoes Project. Annual Report 2022. Western Libraries, Western University, February 2023. http://dx.doi.org/10.5206/ntpr1894.

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NTP’s fourth year of detecting, surveying and documenting tornadoes and other damaging wind events across Canada saw a return to a more familiar pattern. In 2021, only two tornadoes were recorded across the Prairies over the 60 days with the highest climatological frequency (mid-June to mid-August).In 2022, 39 tornadoes were confirmed there, with 33 of them during that peak period. However, a catastrophic spring derecho set the stage for a very different and very active season in Ontario and Québec. The May 21st derecho is now one of the most deadly and costly thunderstorm events on record in Canada. While over a billion dollars in insured losses was recorded, 12 people lost their lives and at least another 12 were injured. The storm’s damage path extended over 1,000 km across the most densely populated region in Canada. Though NTP field teams were deployed shortly after the event occurred, it took the rest of the summer to fully investigate this devastating event. Through the rest of the season, Ontario and Québec recorded 77 tornadoes, nearly double what was recorded across the entire Prairies. And the total number of tornadoes across Canada during the 2022 season is tied for the highest we’ve recorded at 117 – and closer to the 150 or so that we thought might be occurring based on statistical analysis. So, it appears that the number of 'missing tornadoes' is indeed dropping due to the efforts of NTP.
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