Relevant bibliographies by topics / Occurrence datasets

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Occurrence datasets'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Occurrence datasets"

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Waller, John. "Data Location Quality at GBIF." Biodiversity Information Science and Standards 3 (June 13, 2019): e35829. https://doi.org/10.3897/biss.3.35829.

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I will cover how the Global Biodiversity Information Facility (GBIF) handles data quality issues, with specific focus on coordinate location issues, such as gridded datasets (Fig. 1) and country centroids. I will highlight the challenges GBIF faces identifying potential data quality problems and what we and others (Zizka et al. 2019) are doing to discover and address them. GBIF is the largest open-data portal of biodiversity data, which is a large network of individual datasets (> 40k) from various sources and publishers. Since these datasets are variable both within themselves and dataset-
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Steeman, Roosmarijn, Wouter Vanreusel, Rutger Barendse, et al. "Waarnemingen.be – Plant occurrences in Flanders and the Brussels Capital Region, Belgium." PhytoKeys 85 (August 8, 2017): 1–10. http://dx.doi.org/10.3897/phytokeys.85.14925.

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Waarnemingen.be - Plant occurrences in Flanders and the Brussels Capital Region, Belgium is a species occurrence dataset published by Natuurpunt. The dataset contains almost 1.2 million plant occurrences of 1,222 native vascular plant species, mostly recorded by volunteers (citizen scientists), mainly since 2008. The occurrences are derived from the database http://www.waarnemingen.be, hosted by Stichting Natuurinformatie and managed by the nature conservation NGO Natuurpunt. Together with the datasets Florabank1 (Van Landuyt and Brosens 2017) and the Belgian IFBL (Instituut voor Floristiek va
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Steeman, Roosmarijn, Wouter Vanreusel, Rutger Barendse, et al. "Waarnemingen.be – Plant occurrences in Flanders and the Brussels Capital Region, Belgium." PhytoKeys 85 (August 8, 2017): 1–10. https://doi.org/10.3897/phytokeys.85.14925.

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Waarnemingen.be - Plant occurrences in Flanders and the Brussels Capital Region, Belgium is a species occurrence dataset published by Natuurpunt. The dataset contains almost 1.2 million plant occurrences of 1,222 native vascular plant species, mostly recorded by volunteers (citizen scientists), mainly since 2008. The occurrences are derived from the database http://www.waarnemingen.be, hosted by Stichting Natuurinformatie and managed by the nature conservation NGO Natuurpunt. Together with the datasets Florabank1 (Van Landuyt and Brosens 2017) and the Belgian IFBL (Instituut voor Floristiek va
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Orozco-Arias, Simon, Ana María Núñez-Rincón, Reinel Tabares-Soto, and Diana López-Álvarez. "Worldwide co-occurrence analysis of 17 species of the genus Brachypodium using data mining." PeerJ 6 (January 14, 2019): e6193. http://dx.doi.org/10.7717/peerj.6193.

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The co-occurrence of plant species is a fundamental aspect of plant ecology that contributes to understanding ecological processes, including the establishment of ecological communities and its applications in biological conservation. A priori algorithms can be used to measure the co-occurrence of species in a spatial distribution given by coordinates. We used 17 species of the genus Brachypodium, downloaded from the Global Biodiversity Information Facility data repository or obtained from bibliographical sources, to test an algorithm with the spatial points process technique used by Silva et
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Aydin, B., D. Kempton, V. Akkineni, R. Angryk, and K. G. Pillai. "Mining spatiotemporal co-occurrence patterns in solar datasets." Astronomy and Computing 13 (November 2015): 136–44. http://dx.doi.org/10.1016/j.ascom.2015.10.003.

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Šturm, Tomaž, and Tomaž Podobnikar. "A probability model for long-term forest fire occurrence in the Karst forest management area of Slovenia." International Journal of Wildland Fire 26, no. 5 (2017): 399. http://dx.doi.org/10.1071/wf15192.

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The aim of this study is to develop a long-term forest fire occurrence probability model in the Karst forest management area of Slovenia. The target area has the greatest forest fire occurrence rates and the largest burned areas in the country. To discover how the forest stand characteristics influence forest fire occurrence, we developed a long-term linear regression model. The geographically weighted regression method was applied to build the model, using forest management plans and land-based datasets as explanatory variables and a past forest fire activity dataset as a predicted variable.
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Neves, Matheus Oliveira, Hugo Cabral, Mariana Pedrozo, Vanda Lucia Ferreira, Mário Ribeiro Moura, and Diego José Santana. "Dataset of occurrences and ecological traits of amphibians from Upper Paraguay River Basin, central South America." Nature Conservation 41 (September 2, 2020): 71–89. http://dx.doi.org/10.3897/natureconservation.41.54265.

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There are many gaps in our biodiversity knowledge, especially in highly diverse regions such as the Neotropics. Basic information on species occurrence and traits are scattered throughout different literature sources, which makes it difficult to access data and ultimately delays advances in ecology, evolution, and conservation biology. We provide species occurrence and trait data for amphibian species in the Upper Paraguay River Basin, central South America. The compiled information is made available through two different datasets that hold (i) 17K species occurrence records and (ii) 30 specie
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Neves, Matheus Oliveira, Hugo Cabral, Mariana Pedrozo, Vanda Lucia Ferreira, Mário Ribeiro Moura, and Diego José Santana. "Dataset of occurrences and ecological traits of amphibians from Upper Paraguay River Basin, central South America." Nature Conservation 41 (September 2, 2020): 71–89. https://doi.org/10.3897/natureconservation.41.54265.

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There are many gaps in our biodiversity knowledge, especially in highly diverse regions such as the Neotropics. Basic information on species occurrence and traits are scattered throughout different literature sources, which makes it difficult to access data and ultimately delays advances in ecology, evolution, and conservation biology. We provide species occurrence and trait data for amphibian species in the Upper Paraguay River Basin, central South America. The compiled information is made available through two different datasets that hold (i) 17K species occurrence records and (ii) 30 specie
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Simpson, Annie, and Elizabeth Martín. "Biodiversity Information Serving Our Nation (BISON) now with more than 1/3 billion species occurrences." Biodiversity Information Science and Standards 1 (August 15, 2017): e20285. https://doi.org/10.3897/tdwgproceedings.1.20285.

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Biodiversity Information Serving Our Nation (BISON) is a web-based resource (https://bison.usgs.gov) for finding and accessing occurrence records of species found in the United States (US), its Territories and marine Exclusive Economic Zones. BISON serves as a data aggregator that compiles and standardizes species occurrence data from multiple data providers, and now contains more than 1/3 billion species occurrences. BISON uses the Integrated Taxonomic Information System (ITIS) to standardize species names in searches. It is also the US hub of the Global Biodiversity Information Facility (GBI
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Pisarenko, Olga. "Moss occurrences in Salair-Kuznetsk Region (Altai-Sayan mountain country)." Biodiversity Data Journal 9 (September 15, 2021): e72889. https://doi.org/10.3897/BDJ.9.e72889.

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In the flora of large regions, mosses comprise about a quarter of the total diversity of higher plants. However, now mosses are the least studied group of higher plants. Data on moss species distribution are fragmentary, especially in Russia with its vast expanse and low density of botanists.The author for many years has been studying the bryoflora of various areas of the Salair-Kuznetsk Region. In addition to the herbarium collection, the author's bryological relevés were organised as a Database. It stores all the assembled information for the years about the locations of the species, includi
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Dissertations / Theses on the topic "Occurrence datasets"

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David, Laurent. "Development of deep-learning approaches to discover metabolic interaction networks of environmental microbial communities from large metagenomic datasets, domain co-occurrence and protein coevolution." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS582.

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L’analyse des séquences biologiques constitue l’un des domaines majeur de la bioinformatique. En particulier, la prédiction des interactions entre protéines est une étape importante, et joue un rôle clé dans la compréhension des environnements moléculaires existant au sein de la cellule. La production des données brutes par le séquençage de nouvelle génération se fait en deux temps. A partir d’un échantillon biologique, une population de fragments d’ADN est d’abord extraite. Ces fragments sont ensuite séquencés à leurs extrémités pour produire des lectures. Le premier défi consiste à assembler
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Rodrigues, Cláudia Sofia Oliveira. "Optimization of a cetacean occurrence dataset: methods for controlling data bias, verification and validation." Master's thesis, 2021. https://hdl.handle.net/10216/136456.

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Book chapters on the topic "Occurrence datasets"

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Osmanoglu, Usame Omer. "The Use of Artificial Intelligence in the Diagnosis and Treatment of Diabetes." In Current Multidisciplinary Approach to Diabetes Mellitus Occurrence Mechanism. Nobel Tip Kitabevleri, 2023. http://dx.doi.org/10.69860/nobel.9786053359104.15.

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Artificial intelligence (AI) is increasingly transforming the landscape of diabetes diagnosis and treatment by leveraging data-driven approaches to enhance precision and efficiency in healthcare. AI algorithms analyze vast amounts of patient data, including medical records, genetic profiles, and real-time physiological metrics from wearable devices, to identify patterns and predict disease progression. In diagnostics, AI-powered systems can interpret complex datasets to facilitate early detection of diabetes and its complications, such as diabetic retinopathy and nephropathy, improving clinica
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Hashimoto, Shoji. "Overview of Radiocesium Dynamics in Forests: First Decade and Future Perspectives." In Agricultural Implications of Fukushima Nuclear Accident (IV). Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9361-9_12.

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AbstractAbout 70% of contaminated areas are covered with forests. After the occurrence of accidents, the radiocesium deposited at the time of the accident has migrated within forests, which has been well captured by many studies. Additionally, air dose rates have dropped mainly due to the decay of 134Cs. Herein, the overall radiocesium dynamics were reviewed and shown with the collated datasets. Furthermore, future perspectives of forest radiocesium were discussed with predictions and insights from modeling studies.
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Chinazzo, André, Christian De Schryver, Katharina Zweig, and Norbert Wehn. "Increasing the Sampling Efficiency for the Link Assessment Problem." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21534-6_3.

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AbstractComplex graphs are at the heart of today’s big data challenges like recommendation systems, customer behavior modeling, or incident detection systems. One reoccurring task in these fields is the extraction of network motifs, which are subgraphs that are reoccurring and statistically significant. To assess the statistical significance of their occurrence, the observed values in the real network need to be compared to their expected value in a random graph model.In this chapter, we focus on the so-called Link Assessment (LA) problem, in particular for bipartite networks. Lacking closed-f
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Rossier, Clémentine, Laura Bernardi, Marie Baersywil, Michel Oris, Marlène Sapin, and Eric Widmer. "How Family and Other Close Ties Shape Vulnerability Processes." In Withstanding Vulnerability throughout Adult Life. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-4567-0_10.

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AbstractWhile close relations include both intimate family members and close friends, the transmission of socioeconomic resource remains largely confined within families. Moreover, family-transmitted values and sociopsychological skills are incorporated during childhood, and emotional and instrumental support is still mainly assumed by family members. These overlapping exchanges mean that family ties constitute durable resource for individuals, but that families are (also) damaging in case of tie dissolution, poor relational quality or gendered family practices. In this chapter, we examine how
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Saad, Muhammad Muneeb, Mubashir Husain Rehmani, and Ruairi O’Reilly. "A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesis." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26438-2_2.

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AbstractImbalanced image datasets are commonly available in the domain of biomedical image analysis. Biomedical images contain diversified features that are significant in predicting targeted diseases. Generative Adversarial Networks (GANs) are utilized to address the data limitation problem via the generation of synthetic images. Training challenges such as mode collapse, non-convergence, and instability degrade a GAN’s performance in synthesizing diversified and high-quality images. In this work, MSG-SAGAN, an attention-guided multi-scale gradient GAN architecture is proposed to model the re
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Oswald, Julie N., Christine Erbe, William L. Gannon, Shyam Madhusudhana, and Jeanette A. Thomas. "Detection and Classification Methods for Animal Sounds." In Exploring Animal Behavior Through Sound: Volume 1. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97540-1_8.

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AbstractClassification of the acoustic repertoires of animals into sound types is a useful tool for taxonomic studies, behavioral studies, and for documenting the occurrence of animals. Classification of acoustic repertoires enables the identification of species, age, gender, and individual identity, correlations between sound types and behavior, the identification of changes in vocal behavior over time or in response to anthropogenic noise, comparisons between the repertoires of populations living in different geographic regions and environments, and the development of software tools for auto
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Musci, Mirto, and Marco Ferretti. "Mining Geometrical Motifs Co-occurrences in the CMS Dataset." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99133-7_15.

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Pathak, Debanjan, U. S. N. Raju, Sukhdev Singh, G. Naveen, and K. Anil. "Content-Based Image Retrieval Using Statistical Color Occurrence Feature on Multiresolution Dataset." In Evolution in Computational Intelligence. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5788-0_66.

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Wolters, Lisan, and Marwan Hassani. "Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_11.

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AbstractCustomer journey analysis is important for organizations to get to know as much as possible about the main behavior of their customers. This provides the basis to improve the customer experience within their organization. This paper addresses the problem of predicting the occurrence of a certain activity of interest in the remainder of the customer journey that follows the occurrence of another specific activity. For this, we propose the HIAP framework which uses process mining techniques to analyze customer journeys. Different prediction models are researched to investigate which mode
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Aryastana, Putu, Listya Dewi, Putu Ika Wahyuni, I. Nengah Sinarta, Jason Pajimola Punay, and Jackson Chang Hian Wui. "Evaluation of Double Fusion Satellite Rainfall Dataset in Establish Rainfall Thresholds for Landslide Occurrences Over Badung Regency-Bali." In Landslide: Susceptibility, Risk Assessment and Sustainability. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56591-5_22.

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Conference papers on the topic "Occurrence datasets"

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Solakov, Dimcho, Stela Simeonova, and Plamena Raykova. "PROBABILISTIC EARTHQUAKE SCENARIOS FOR THE CITY OF VARNA." In 24th SGEM International Multidisciplinary Scientific GeoConference 24. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/1.1/s05.651.

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In the present study probabilistic earthquake, scenarios for the city of Varna the third-largest earthquake-prone city in Bulgaria are presented. The probabilistic hazard for a city is obtained by integrating the effects of ground motion from earthquakes of different size occurring at different locations within different seismic source regions and with different frequencies of occurrence. The ground motion maps for the city of Varna are generated combining via GIS, source geometry, earthquake occurrence model, maximum earthquake magnitude, and the appropriate attenuation relations. The probabi
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Kreuzthaler, Markus, Bastian Pfeifer, and Stefan Schulz. "Terminology Expansion via Co-occurrence Analysis of Large Clinical Real-World Datasets." In 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI). IEEE, 2022. http://dx.doi.org/10.1109/ichi54592.2022.00124.

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Balkir, Esma, Masha Naslidnyk, Dave Palfrey, and Arpit Mittal. "Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1368.

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Ma, Chengjie, Junping Du, Meiyu Liang, and Zeli Guan. "Topic Model Based on Co-Occurrence Word Networks for Unbalanced Short Text Datasets." In 2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2023. http://dx.doi.org/10.1109/docs60977.2023.10294993.

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Du, Jing, Zhanquan Wang, and Mengfei Ye. "Research on Algorithms of Positive and Negative Co-occurrence in Spatio-temporal Datasets." In 2022 8th International Conference on Systems and Informatics (ICSAI). IEEE, 2022. http://dx.doi.org/10.1109/icsai57119.2022.10005536.

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Gramstad, Odin, Elzbieta Bitner-Gregersen, Øyvind Breivik, Anne Karin Magnusson, Magnar Reistad, and Ole Johan Aarnes. "Analysis of Rogue Waves in North-Sea In-Situ Surface Wave Data." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77858.

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The statistical properties of individual wave heights and wave crests from time series of recorded surface elevation are analyzed with a particular focus on the occurrence of extreme and rogue waves in the datasets. The datasets include surface elevation measurements from three different sensors: a wave buoy, a wave laser and a Saab wave radar — all situated at the Ekofisk field in the North-Sea and providing sea surface elevation measurements at 2Hz temporal resolution. The resulting statistical properties of wave heights and wave crests are compared with common reference statistical distribu
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Li, Chao, Qiaoyong Zhong, Di Xie, and Shiliang Pu. "Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/109.

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Skeleton-based human action recognition has recently drawn increasing attentions with the availability of large-scale skeleton datasets. The most crucial factors for this task lie in two aspects: the intra-frame representation for joint co-occurrences and the inter-frame representation for skeletons' temporal evolutions. In this paper we propose an end-to-end convolutional co-occurrence feature learning framework. The co-occurrence features are learned with a hierarchical methodology, in which different levels of contextual information are aggregated gradually. Firstly point-level information
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Bhattacharjya, Debarun, Tian Gao, and Dharmashankar Subramanian. "Order-Dependent Event Models for Agent Interactions." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/274.

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In multivariate event data, the instantaneous rate of an event's occurrence may be sensitive to the temporal sequence in which other influencing events have occurred in the history. For example, an agent’s actions are typically driven by preceding actions taken by the agent as well as those of other relevant agents in some order. We introduce a novel statistical/causal model for capturing such an order-sensitive historical dependence, where an event’s arrival rate is determined by the order in which its underlying causal events have occurred in the recent past. We propose an algorithm to disco
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Jo, Minju, Seungji Kook, and Noseong Park. "Hawkes Process Based on Controlled Differential Equations." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/239.

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Hawkes processes are a popular framework to model the occurrence of sequential events, i.e., occurrence dynamics, in several fields such as social diffusion. In real-world scenarios, the inter-arrival time among events is irregular. However, existing neural network-based Hawkes process models not only i) fail to capture such complicated irregular dynamics, but also ii) resort to heuristics to calculate the log-likelihood of events since they are mostly based on neural networks designed for regular discrete inputs. To this end, we present the concept of Hawkes process based on controlled differ
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Thumpati, Asitha, and Yan Zhang. "Towards Optimizing Performance of Machine Learning Algorithms on Unbalanced Dataset." In 10th International Conference on Artificial Intelligence & Applications. Academy & Industry Research Collaboration Center, 2023. http://dx.doi.org/10.5121/csit.2023.131914.

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Imbalanced data, a common occurrence in real-world datasets, presents a challenge for machine learning classification models. These models are typically designed with the assumption of balanced class distributions, leading to lower predictive performance when faced with imbalanced data. To address this issue, this paper employs data preprocessing techniques, including Synthetic Minority Oversampling Technique (SMOTE) for oversampling and random undersampling, on unbalanced datasets. Additionally, genetic programming is utilized for feature selection to enhance both performance and efficiency.
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Reports on the topic "Occurrence datasets"

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Turner, Paul, Alessia Baseggio Conrado, and Jennifer Quint. Using NHS Data to Monitor Trends in the Occurrence of Severe, Food-Induced Allergic Reactions Work Package 1. Food Standards Agency, 2024. http://dx.doi.org/10.46756/sci.fsa.lvn457.

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People with food allergies may experience food allergic reactions due to accidental exposure. These reactions are commonly categorised as non-severe, fatal food anaphylaxis and near-fatal food anaphylaxis. Non-severe allergic reactions to food are more common with an incidence of up to 1,000 times greater than fatal food-related anaphylaxis. However, obtaining accurate data relating to the circumstances under which these reactions occurred is challenging under the current diagnosis coding system used in the National Health Service (NHS). This project addressed two key questions: What are the t
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Bourdeau, J. E., and C. J. M. Lawley. Datasets to support prospectivity modelling for graphite deposits and occurrences in Canada. Natural Resources Canada/CMSS/Information Management, 2025. https://doi.org/10.4095/prabb6xmef.

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Guerrero Compeán, Roberto, Eduardo Zegarra Méndez, and Sergio Lacambra Ayuso. Estimating the Economic Impact of Governance in Disaster Risk Management: Theory and Evidence from Latin America and the Caribbean. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013046.

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Strengthened governance is crucial to reduce economic risks associated with disasters, but little is known about its impact. We combine a new dataset on disaster risk management governance for 26 countries from the Latin America and Caribbean region with annual information on economic losses resulting from disasters between 1980 and 2016. To account for endogenous disaster risk management (DRM) governance processes, we exploit the fact that changes in DRM regulatory frameworks affect a country's capacity for disaster risk identification and reduction to provide instrumental variable estimates
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Kingston, A. W., A. Mort, C. Deblonde, and O H Ardakani. Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329266.

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The Montney Formation is a highly productive hydrocarbon reservoir that is of great economic importance to Canada, however production is often dogged by the presence of hydrogen sulfide (H2S), a highly toxic and corrosive gas. Mapping H2S distribution across the Montney basin in the Western Canadian Sedimentary Basin (WCSB) is fundamental to understanding the processes responsible for its occurrence. We derive a Montney-specific dataset of well gas and water geochemistry from the publically available archives of the Alberta Energy Regulator (AER) and British Columbia Oil and Gas Commission (BC
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Liu, Hong, Paulo Olivas, and James Lange. An inventory study on the cigar orchid (Cyrtopodium punctatum) in Big Cypress National Preserve: Final report. National Park Service, 2024. http://dx.doi.org/10.36967/2302454.

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The cigar orchid is a Florida state-listed endangered species, made rare in southern Florida by historical over-collection for its unique beauty, in addition to habitat loss. It is largely restricted to a small number of cypress domes and freshwater sloughs in southwestern Florida, including the Big Cypress National Preserve (BICY). We established a baseline dataset on the population of cigar orchid at BICY, based on extensive field surveys within the following seven regions: Fire Prairie Trail-East, Gator Hook Trail, Florida Trail, Nobles Grade, North of Tamiami Trail (mainly the Skillet Stra
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Hannigan, P. K. A GIS dataset compilation of lead and zinc occurrences for the Targeted Geoscience Initiative project: potential for carbonate-hosted Pb-Zn (MVT) deposits in northern Alberta and southern Northwest Territories (NTS blocks 74, 84, 85). Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/221528.

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Chen, Z., S. E. Grasby, C. Deblonde, and X. Liu. AI-enabled remote sensing data interpretation for geothermal resource evaluation as applied to the Mount Meager geothermal prospective area. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330008.

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The objective of this study is to search for features and indicators from the identified geothermal resource sweet spot in the south Mount Meager area that are applicable to other volcanic complexes in the Garibaldi Volcanic Belt. A Landsat 8 multi-spectral band dataset, for a total of 57 images ranging from visible through infrared to thermal infrared frequency channels and covering different years and seasons, were selected. Specific features that are indicative of high geothermal heat flux, fractured permeable zones, and groundwater circulation, the three key elements in exploring for geoth
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Kurimo-Beechuk, Elizabeth, Michael Byrne, and Wendy Wright. Landbird community monitoring at Cumberland Island National Seashore: 2012 data summary. National Park Service, Natural Resource Stewardship and Science, 2016. https://doi.org/10.36967/2228030.

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Birds are an important component of park ecosystems. Due to their high body temperature, rapid metabolism, and high ecological position in most food webs, birds are also good indicators of the effects of local and regional ecosystem changes. Patterns in the community composition, distribution, and occurrence of breeding birds provide a metric for assessing ecological integrity and sustainability in southeastern U. S. ecosystems. Further, trends in these attributes in relation to activities occurring at Cumberland Island National Seashore (e.g., management actions, natural disturbance, invasive
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Kurimo-Beechuk, Elizabeth, Michael Byrne, and Wendy Wright. Landbird community monitoring at Fort Sumter National Monument: 2012 data summary. National Park Service, Natural Resource Stewardship and Science, 2016. https://doi.org/10.36967/2228028.

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Birds are an important component of park ecosystems. Due to their high body temperature, rapid metabolism, and high ecological position in most food webs, birds are also good indicators of the effects of local and regional ecosystem changes. Patterns in the community composition, distribution, and occurrence of breeding birds provide a metric for assessing ecological integrity and sustainability in southeastern U.S. ecosystems. Further, trends in these attributes in relation to activities occurring at Fort Sumter National Monument (e.g., management actions, natural disturbance, invasive-specie
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Harris, L. B., P. Adiban, and E. Gloaguen. The role of enigmatic deep crustal and upper mantle structures on Au and magmatic Ni-Cu-PGE-Cr mineralization in the Superior Province. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328984.

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Abstract:
Aeromagnetic and ground gravity data for the Canadian Superior Province, filtered to extract long wavelength components and converted to pseudo-gravity, highlight deep, N-S trending regional-scale, rectilinear faults and margins to discrete, competent mafic or felsic granulite blocks (i.e. at high angles to most regional mapped structures and sub-province boundaries) with little to no surface expression that are spatially associated with lode ('orogenic') Au and Ni-Cu-PGE-Cr occurrences. Statistical and machine learning analysis of the Red Lake-Stormy Lake region in the W Superior Province con
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