Relevant bibliographies by topics / Datasety

Contents

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

Academic literature on the topic 'Datasety'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Datasety"

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Lingeswari Sivagnanam. "Enhanced Ensemble Machine Learning Technique to detect Bipolar Disorder." Journal of Information Systems Engineering and Management 10, no. 38s (2025): 610–19. https://doi.org/10.52783/jisem.v10i38s.6932.

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The study introduced a unique Enhanced Ensemble Machine Learning (EEML) method for the detection of bipolar disorder, a serious medical diagnoses problem that acquires an immediate and timely diagnosis for an effective and earlier treatment. The EEML approach combines several machine learning models with the data based on patient’s attitude on different perspectives such as real, signal based, textual and behavioural data and more. In order to train individual classifiers for identifying mental diseases, pertinent characteristics are taken from each data source using a thorough feature selecti
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Almeida, Daniela, Dany Domínguez-Pérez, Ana Matos, et al. "Data Employed in the Construction of a Composite Protein Database for Proteogenomic Analyses of Cephalopods Salivary Apparatus." Data 5, no. 4 (2020): 110. http://dx.doi.org/10.3390/data5040110.

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Here we provide all datasets and details applied in the construction of a composite protein database required for the proteogenomic analyses of the article “Putative Antimicrobial Peptides of the Posterior Salivary Glands from the Cephalopod Octopus vulgaris Revealed by Exploring a Composite Protein Database”. All data, subdivided into six datasets, are deposited at the Mendeley Data repository as follows. Dataset_1 provides our composite database “All_Databases_5950827_sequences.fasta” derived from six smaller databases composed of (i) protein sequences retrieved from public databases related
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Al-Zubaidi, Asst Prof Ehsan Ali, Furkan Rabee, and Ahmed H. Al-Sulttani. "Classification of Large-Scale Datasets of Landsat-8 Satellite Image Based on LIBLINEAR Library." Al-Salam Journal for Engineering and Technology 1, no. 2 (2022): 9–17. http://dx.doi.org/10.55145/ajest.2022.01.02.003.

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One of the most common machine learning approaches is linear classification. Multithreading used in LIBLINEAR Library has become an important research topic for processing large datasets. Working in a multithreaded environment accelerates the training of large datasets and increases classification accuracy. This study examines multiple linear support vector machine implementations for binary classification of Landsat-8 satellite image datasets to determine the optimal model. Four datasets have been created for different scenes in Iraq. Each dataset contains millions of pixels to be classified
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Kabir, Masud, Fatih Unal, Tahir Cetin Akinci, Alfredo A. Martinez-Morales, and Sami Ekici. "Revealing GLCM Metric Variations across a Plant Disease Dataset: A Comprehensive Examination and Future Prospects for Enhanced Deep Learning Applications." Electronics 13, no. 12 (2024): 2299. http://dx.doi.org/10.3390/electronics13122299.

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This study highlights the intricate relationship between Gray-Level Co-occurrence Matrix (GLCM) metrics and machine learning model performance in the context of plant disease identification. It emphasizes the importance of rigorous dataset evaluation and selection protocols to ensure reliable and generalizable classification outcomes. Through a comprehensive examination of publicly available plant disease datasets, focusing on their performance as measured by GLCM metrics, this research identified dataset_2 (D2), a database of leaf images, as the top performer across all GLCM analyses. These d
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Papadopoulos, Symeon, Giorgos Kordopatis-Zilos, Markos Zampoglou, and Olga Papadopoulou. "Dataset column: Datasets for online multimedia verification." ACM SIGMultimedia Records 11, no. 3 (2019): 1. http://dx.doi.org/10.1145/3524460.3524468.

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Li, Yiwen. "Elastic distributed dataset RDD (Resilient Distributed Datasets)." Applied and Computational Engineering 31, no. 1 (2024): 184–93. http://dx.doi.org/10.54254/2755-2721/31/20230149.

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In recent years, the amount of data to be processed has become larger and larger, and it is difficult for a single processor to handle data, so we need to work hard to develop the expansion mode of cluster mode. Mapreduce, Storm, etc. are a solution for clusters to process data. However, we still have parallel processing, user resource sharing and other issues to be addressed. RDD data model is the key to solve these problems. In this paper, RDD is applied to Spark for detailed expansion, and project experiments are carried out to study the RDD data model. The programming language used in this
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A. Adesokan, Ademola. "Covid-19 Control: Face Mask Detection Using Deep Learning for Balanced and Unbalanced Dataset." International Journal of Intelligent Systems and Applications 14, no. 6 (2022): 50–62. http://dx.doi.org/10.5815/ijisa.2022.06.05.

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Facemask wearing is becoming a norm in our daily lives to curb the spread of Covid-19. Ensuring facemasks are worn correctly is a topic of concern worldwide. It could go beyond manual human control and enforcement, leading to the spread of this deadly virus and many cases globally. The main aim of wearing a facemask is to curtail the spread of the covid-19 virus, but the biggest concern of most deep learning research is about who is wearing the mask or not, and not who is incorrectly wearing the facemask while the main objective of mask wearing is to prevent the spread of the covid-19 virus. T
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Khan, Somaiya, and Ali Khan. "SkinViT: A transformer based method for Melanoma and Nonmelanoma classification." PLOS ONE 18, no. 12 (2023): e0295151. http://dx.doi.org/10.1371/journal.pone.0295151.

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Over the past few decades, skin cancer has emerged as a major global health concern. The efficacy of skin cancer treatment greatly depends upon early diagnosis and effective treatment. The automated classification of Melanoma and Nonmelanoma is quite challenging task due to presence of high visual similarities across different classes and variabilities within each class. According to the best of our knowledge, this study represents the classification of Melanoma and Nonmelanoma utilising Basal Cell Carcinoma (BCC) and Squamous Cell Carcinoma (SCC) under the Nonmelanoma class for the first time
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Prithvi R. "Multi-Model Evaluation of Computer Vision Techniques for Fine-Grained Vehicle Recognition." Journal of Information Systems Engineering and Management 10, no. 44s (2025): 428–59. https://doi.org/10.52783/jisem.v10i44s.8612.

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Vehicle make and model recognition is a crucial component in applications such as intelligent transportation systems, law enforcement, and autonomous vehicles.This paper presents a comparative analysis of Machine Learning approaches — KNN, SVM and Decision Tree Classifier which are the first appraoch and three deep learning models—Convolutional Neural Network (CNN), YOLOv8, and Faster R-CNN— are the second approach for vehicle recognition tasks. The models were evaluated on a two datasets comprising 197 vehicle classes (dataset1) under various conditions and the other with was scrapped manuall
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Haider, S. A., and N. S. Patil. "Minimization of Datasets : Using a Master Interlinked Dataset." Indian Journal of Computer Science 3, no. 5 (2018): 20. http://dx.doi.org/10.17010/ijcs/2018/v3/i5/138778.

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Dissertations / Theses on the topic "Datasety"

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Zembjaková, Martina. "Prieskum a taxonómia sieťových forenzných nástrojov." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445488.

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Táto diplomová práca sa zaoberá prieskumom a taxonómiou sieťových forenzných nástrojov. Popisuje základné informácie o sieťovej forenznej analýze, vrátane procesných modelov, techník a zdrojov dát používaných pri forenznej analýze. Ďalej práca obsahuje prieskum existujúcich taxonómií sieťových forenzných nástrojov vrátane ich porovnania, na ktorý naväzuje prieskum sieťových forenzných nástrojov. Diskutované sieťové nástroje obsahujú okrem nástrojov spomenutých v prieskume taxonómií aj niektoré ďalšie sieťové nástroje. Následne sú v práci detailne popísané a porovnané datasety, ktoré sú podklad
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Kratochvíla, Lukáš. "Trasování objektu v reálném čase." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403748.

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Sledování obecného objektu na zařízení s omezenými prostředky v reálném čase je obtížné. Mnoho algoritmů věnujících se této problematice již existuje. V této práci se s nimi seznámíme. Různé přístupy k této problematice jsou diskutovány včetně hlubokého učení. Představeny jsou reprezentace objektu, datasety i metriky pro vyhodnocování. Mnoho sledovacích algorimů je představeno, osm z nich je implementováno a vyhodnoceno na VOT datasetu.
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Singh, Manjeet. "A Comparison of Rule Extraction Techniques with Emphasis on Heuristics for Imbalanced Datasets." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1282139633.

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Silva, Jesús, Palma Hugo Hernández, Núẽz William Niebles, David Ovallos-Gazabon, and Noel Varela. "Parallel Algorithm for Reduction of Data Processing Time in Big Data." Institute of Physics Publishing, 2020. http://hdl.handle.net/10757/652134.

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Technological advances have allowed to collect and store large volumes of data over the years. Besides, it is significant that today's applications have high performance and can analyze these large datasets effectively. Today, it remains a challenge for data mining to make its algorithms and applications equally efficient in the need of increasing data size and dimensionality [1]. To achieve this goal, many applications rely on parallelism, because it is an area that allows the reduction of cost depending on the execution time of the algorithms because it takes advantage of the characteristics
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Munyombwe, Theresa. "The harmonisation of stroke datasets : a case study of four UK datasets." Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/13511/.

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Longitudinal studies of stroke patients play a critical part in developing stroke prognostic models. Stroke longitudinal studies are often limited by small sample sizes, poor recruitment, and high attrition levels. Some of these limitations can be addressed by harmonising and pooling data from existing studies. Thus this thesis evaluated the feasibility of harmonising and pooling secondary stroke datasets to investigate the factors associated with disability after stroke. Data from the Clinical Information Management System for Stroke study (n=312), Stroke Outcome Study 1(n=448), Stroke Outcom
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YADAV, DEEPIKA. "SENTIMENT ANALYSIS ON TWITTER DATA." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2020. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18821.

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Prior to purchasing an item, individuals for the most part go to different shops in the market, question about the item, cost, and guarantee, and afterward at long last purchase the item dependent on the feelings they got on cost and nature of administration. This procedure is tedious and the odds of being cheated by the merchant are more as there is no one to direct regarding where the purchaser can get valid item and with legitimate expense. Be that as it may, presently a-days a decent number of people rely upon the upon line showcase for purchasing their necessary items. This is on the grou
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Furman, Yoel Avraham. "Forecasting with large datasets." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:69f2833b-cc53-457a-8426-37c06df85bc2.

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This thesis analyzes estimation methods and testing procedures for handling large data series. The first chapter introduces the use of the adaptive elastic net, and the penalized regression methods nested within it, for estimating sparse vector autoregressions. That chapter shows that under suitable conditions on the data generating process this estimation method satisfies an oracle property. Furthermore, it is shown that the bootstrap can be used to accurately conduct inference on the estimated parameters. These properties are used to show that structural VAR analysis can also be validly cond
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Mumtaz, Shahzad. "Visualisation of bioinformatics datasets." Thesis, Aston University, 2015. http://publications.aston.ac.uk/25261/.

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Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental importance in biology. Predicting functions of polymorphic molecules is important in order to design more effective medicines. Analysing major histocompatibility complex (MHC) polymorphism is important for mate choice, epitope-based vaccine design and transplantation rejection etc. Most of the existing exploratory approaches cannot analyse these datasets because of the large number of molecules with a high number of descriptors per molecule. This thesis develops novel methods for data projection in
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Mazumdar, Suvodeep. "Visualising large semantic datasets." Thesis, University of Sheffield, 2013. http://etheses.whiterose.ac.uk/5932/.

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This thesis aims at addressing a major issue in Semantic Web and organisational Knowledge Management: consuming large scale semantic data in a generic, scalable and pleasing manner. It proposes two solutions by de-constructing the issue into two sub problems: how can large semantic result sets be presented to users; and how can large semantic datasets be explored and queried. The first proposed solution is a dashboard-based multi-visualisation approach to present simultaneous views over different facets of the data. Challenges imposed by existing technology infrastructure resulted in the devel
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De, León Eduardo Enrique. "Medical abstract inference dataset." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/119516.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (page 35).<br>In this thesis, I built a dataset for predicting clinical outcomes from medical abstracts and their title. Medical Abstract Inference consists of 1,794 data points. Titles were filtered to include the abstract's repor
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Books on the topic "Datasety"

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Geological Survey (U.S.), ed. National elevation dataset. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Bart, Hobijn, and Harvard Business School, eds. The CHAT dataset. Harvard Business School, 2009.

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Hutchinson, T. P. The datasets from CBDEA. Rumsby Scientific Publishing, 1993.

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1942-, Ullman Jeffrey D., ed. Mining of massive datasets. Cambridge University Press, 2012.

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Geological Survey (U.S.), ed. National land cover dataset. U.S. Dept. of the Interior, U.S. Geological Survey, 2000.

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Geological Survey (U.S.), ed. The National Hydrography Dataset. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Slayton, Emma, and Julia Bauder. Who Creates Datasets, and How? SAGE Publications, Inc., 2022. http://dx.doi.org/10.4135/9781071900871.

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Sarang, Poornachandra. Clustering Small to Humongous Datasets. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49094-1.

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Milanović, Branko. Dataset - racial tension, volume 6. World Bank, 2005.

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Quiñonero-Candela, Joaquin. Dataset shift in machine learning. MIT Press, 2009.

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Book chapters on the topic "Datasety"

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Alrashed, Tarfah, Dimitris Paparas, Omar Benjelloun, Ying Sheng, and Natasha Noy. "Dataset or Not? A Study on the Veracity of Semantic Markup for Dataset Pages." In The Semantic Web – ISWC 2021. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88361-4_20.

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AbstractSemantic markup, such as , allows providers on the Web to describe content using a shared controlled vocabulary. This markup is invaluable in enabling a broad range of applications, from vertical search engines, to rich snippets in search results, to actions on emails, to many others. In this paper, we focus on semantic markup for datasets, specifically in the context of developing a vertical search engine for datasets on the Web, Google’s Dataset Search. Dataset Search relies on to identify pages that describe datasets. While was the core enabling technology for this vertical search,
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Xing, Yujie, Itishree Mohallick, Jon Atle Gulla, Özlem Özgöbek, and Lemei Zhang. "An Educational News Dataset for Recommender Systems." In ECML PKDD 2020 Workshops. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65965-3_39.

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AbstractDatasets are an integral part of contemporary research on recommender systems. However, few datasets are available for conventional recommender systems and even very limited datasets are available when it comes to contextualized (time and location-dependent) News Recommender Systems. In this paper, we introduce an educational news dataset for recommender systems. This dataset is the refined version of the earlier published Adressa dataset and intends to support the university students in the educational purpose. We discuss the structure and purpose of the refined dataset in this paper.
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Lehr, Jan, Jan Philipps, Alik Sargsyan, Martin Pape, and Jörg Krüger. "AD3: Introducing a Score for Anomaly Detection Dataset Difficulty Assessment Using VIADUCT Dataset." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-73113-6_26.

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AbstractThe field of visual Industrial Anomaly Detection (IAD) has brought forth many new semi-supervised learning methods in recent years. At the same time, there have been few new datasets for benchmarking the methods. The most popular dataset is MVTec-AD dataset, because of its diversity of categories and availability of industrial objects. But many methods already achieve AUROC scores of more than 99 % on the MVTec-AD dataset. The defects of the categories that the dataset provides appear to be easily detectable. Furthermore, there is no existing approach to statistically describe the defe
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Li, Yuezun, Pu Sun, Honggang Qi, and Siwei Lyu. "Toward the Creation and Obstruction of DeepFakes." In Handbook of Digital Face Manipulation and Detection. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87664-7_4.

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AbstractAI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information. The need to develop and evaluate DeepFake detection algorithms calls for large-scale datasets. However, current DeepFake datasets suffer from low visual quality and do not resemble DeepFake videos circulated on the Internet. We present a new large-scale challenging DeepFake video dataset, Celeb-DF, which contains 5, 639 high-quality DeepFake videos of celebrities generated using an improved synthesis process. We conduct a comprehensive evaluati
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Luo, Ling. "Datasets." In Temporal Modelling of Customer Behaviour. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18289-2_2.

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Stowell, Sarah. "Datasets." In Using R for Statistics. Apress, 2014. http://dx.doi.org/10.1007/978-1-4842-0139-8_14.

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Ahmed, Mahmuda, Sophia Karagiorgou, Dieter Pfoser, and Carola Wenk. "Datasets." In Map Construction Algorithms. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25166-0_5.

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Tripathy, Santosh Kumar, Roshan Singh, Rajeev Srivastava, Akash Kumar Bhoi, and Santosh Kumar Satapathy. "Datasets." In Advances in Human Activity Detection and Recognition (HADR) Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51660-3_3.

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Klonovs, Juris, Mohammad A. Haque, Volker Krueger, et al. "Datasets." In Distributed Computing and Monitoring Technologies for Older Patients. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27024-1_5.

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Genesereth, Michael, and Vinay K. Chaudhri. "Datasets." In Introduction to Logic Programming. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-031-01586-1_2.

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Conference papers on the topic "Datasety"

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Lebreton, Pierre, Patrick Le Callet, Neil Birkbeck, Yilin Wang, and Balu Adsumilli. "A Dataset for Understanding Open UGC Video Datasets." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10647939.

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U, Vijetha, and Geetha V. "Customized Obstacle Dataset Generation from RGB-D Datasets." In 2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies (INSPECT). IEEE, 2024. https://doi.org/10.1109/inspect63485.2024.10896178.

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Durdov, Božo, Marina Prvan, Duje Čoko, and Josip Musić. "Training Dataset Pruning Algorithm with Evaluation on Medical Datasets." In 2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). IEEE, 2024. http://dx.doi.org/10.23919/softcom62040.2024.10721725.

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Li, Pengyue, Hua Dai, Jie Sun, Sheng Wang, Wenzhe Yang, and Geng Yang. "EDSS: An Exemplar Dataset Search Service over Encrypted Spatial Datasets." In 2024 IEEE International Conference on Web Services (ICWS). IEEE, 2024. http://dx.doi.org/10.1109/icws62655.2024.00164.

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Branco, Arthur M., and Carina F. Dorneles. "Coleta e visualização de dados disponíveis em repositórios públicos referentes a produção científica de pesquisadores." In Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/dsw.2021.17418.

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Dados que refletem a produção científica de pesquisadores têm valor inestimado para diversas aplicações. Há diversos repositórios que indexam os artigos e os disponibilizam para consultas, tais como DBLP, Research Gate e Google Scholar. Apesar dos dados estarem disponíveis nos diversos repositórios públicos, a coleta e persistência local desses dados pode ser de grande utilidade para certas aplicações.Este artigo apresenta uma proposta de coletor de dados de três repositórios públicos: DBLP, Research Gate e Google Scholar, e sua posterior persistência em um banco de dados relacional. Além diss
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Azevedo, Josinaldo, André L. C. Barcellos, Amanda C. A. Mendes, Daniel de Oliveira, Paulo C. S. Vidal, and Marcos Bedo. "SAT-ESPEC: Análise e Coleta de Dados da Transmissão de Estações Terrenas de uma Rede Satélite." In Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/dsw.2021.17413.

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As redes de satélites são um complemento essencial para a infraestrutura de telecomunicações no Brasil. Em alguns casos, esta rede é o único meio de comunicação para várias localidades remotas, que são de difícil acesso geográfico. Esse trabalho tem o objetivo de disponibilizar uma base, denominado SAT-ESPEC, construída a partir do espectrograma gerado da recepção dos sinais de cinco estações terrenas, que estão instaladas e em operação na Região Norte do Brasil. Toda a coleta de dados ocorreu numa rede em produção através da Estação de Radiomonitoração e Geolocalização da Agência Nacional de
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Martins, Antônio Diogo Forte, Lucas Cabral, Pedro Jorge Chaves Mourão, Ivandro Claudino de Sá, José Maria Monteiro, and Javam Machado. "COVID19.BR: A Dataset of Misinformation about COVID-19 in Brazilian Portuguese WhatsApp Messages." In Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/dsw.2021.17422.

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Nowadays, our society suffers with a major issue that unfortunately is becoming more and more problematic, once again through social networks, that is the misinformation. The primary source of misinformation in Brazil is the messaging application WhatsApp. However, due to WhatsApp's private messaging nature, there still few misinformation data sets built specifically from this platform. In this context, building a data set of WhatsApp messages about COVID-19 in Brazilian Portuguese and label misinformation messages within it becomes a crucial challenge. In this work, we present the COVID-19.BR
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Marinho, Jeziel C., Rafael T. Anchiêta, and Raimundo S. Moura. "Essay-BR: a Brazilian Corpus of Essays." In Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/dsw.2021.17414.

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Automatic Essay Scoring (AES) is the computer technology that evaluates and scores the written essays, aiming to provide computational models to grade essays automatically or with minimal human involvement. While there are several AES studies in a variety of languages, few of them are focused on the Portuguese language. The main reason is the lack of a corpus with manually graded essays. We create a large corpus with several essays written by Brazilian high school students on an online platform in order to bridge this gap. All of the essays are argumentative and were scored across five compete
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Cardoso, Fabian Corrêa, Juan Malska, Paulo Ramiro, et al. "BovDB: A data set of stock quotes for Machine Learning on all companies from B3 between 1995 and 2020." In Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/dsw.2021.17411.

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Stock markets are responsible for the movement of huge amounts of financial resources around the world. This market generates a high volume of transaction data, which after being analyzed are very useful for many applications. In this paper we present BovDB, a data set that was built considering as source the Brazilian Stock Exchange (B3) with information related to the years between 1995 and 2020. We have approached the events’ impact on the stocks by applying a cumulative factor to correct prices. The results were compared with public data from InfoMoney and BR Investing, showing that our me
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Moreira, Pedro, Rodrigo Fonseca, Pedro Loures Alzamora, et al. "Covid Data Analytics: Repositório de Dados Provenientes de Múltiplas Fontes sobre a Pandemia de COVID-19 no Brasil." In Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/dsw.2021.17419.

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Este artigo apresenta a construção e publicação de um repositório de dados utilizados e desenvolvidos no âmbito do projeto Covid Data Analytics (CDA), executado pelo Departamento de Ciência da Computação da UFMG. O projeto visou monitorar aspectos referentes à situação social, econômica e epidemiológica da COVID-19 no Brasil a partir da análise de dados provenientes de fontes oficiais e não oficiais, de redes sociais online e da web em geral. A construção do repositório, contendo 18 atributos e 1086 registros, se baseou na coleta direta de dados das fontes selecionadas, os quais foram posterio
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Reports on the topic "Datasety"

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Libra, Jesse Madden. Behind the Numbers: A comparative analysis of international datasets on water and sanitation in Latin America and the Caribbean. Edited by Maria Eugenia De la Peña and María Pérez Urdiales. Inter-American Development Bank, 2024. https://doi.org/10.18235/0013412.

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The development of robust public water and sanitation policies requires dependable, transparent, and representative data; however, the available datasets for the region are complex with indicators that are often misinterpreted by policy professionals. It is essential that users understand the strengths and limitations of these datasets to facilitate source choice and ensure that their use results in accurate insights. This document discusses and contrasts water and sanitation access data produced by three sources: the WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygie
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Elko, Nicole, Katherine Brutsché, Quin Robertson, Michael Hartman, and Zhifei Dong. USACE Navigation Sediment Placement : An RSM Program Database (1998 – 2019). Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/44703.

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This US Army Corps of Engineers, Regional Sediment Management, technical note describes a geodatabase of federal coastal and inland navigation projects developed to determine the extent to which RSM goals have been implemented across the USACE at the project and district levels. The effort 1) quantified the volume of sediment dredged from federal navigation channels by both contract and USACE-owned dredges and 2) identified the placement type and whether sediment was placed beneficially. The majority of the dredging data used to populate the geodatabase were based on the USACE Dredging Informa
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Gagnon, Pieter. Cambium Datasets. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2437669.

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Bishnu, Pariyar. Nepal Energy Gardens Qualitative Dataset and Quantitative Survey Dataset. University of Leeds. [Dataset]. Unknown, 2015. http://dx.doi.org/10.35648/20.500.12413/11781/ii112.

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Rebucci, Alessandro, Andrés Fernández Martín, Michael W. Klein, Martin Uribe, and Martin Schindler. Capital Control Measures: A New Dataset. Inter-American Development Bank, 2015. http://dx.doi.org/10.18235/0011677.

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This paper presents and describes a new dataset of capital control restrictions on both inflows and outflows of 10 categories of assets for 100 countries over the period 1995 to 2013. Building on the data first presented in Schindler (2009) and other datasets based on the analysis of the IMF's Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER), this dataset includes additional asset categories, more countries, and a longer time period. The paper discusses the manner in which information in the AREAER is translated into a usable dataset. The paper additionally characteriz
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van de Sand, Ron, and Jörg Reiff-Stephan. FrostByte Dataset. Technische Hochschule Wildau, 2021. http://dx.doi.org/10.15771/1894.

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It is with great pleasure that we announce the release of the “Frost Byte” dataset. The dataset was collected during research on fault detection and diagnosis (FDD) approaches and their transferability to heterogeneous systems of industrial refrigeration systems at the Technical University of Applied Sciences Wildau. The data collection took place between 2018 and 2019 and is intended to supplement the ASHRAE 1043-RP dataset (Comstock &amp; Braun, 1999), which has been the only publicly available data source in this area to date. For comparison purposes, the method of data collection was chose
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Jaimovich, Dany, and Ugo Panizza. Public Debt around the World: A New Dataset of Central Government Debt. Inter-American Development Bank, 2006. http://dx.doi.org/10.18235/0010859.

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Commonly used datasets on the level of public debt provide incomplete country and period coverage. This paper presents a new dataset that includes complete series of central government debt for 89 countries over the 1991-2005 period and for seven other countries for the 1993-2005 period. The data set can be found at: http://www.iadb.org/res/pub_desc.cfm?pub_id=DBA-005
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Cleary, Summers, Michelle Kinseth, and Michelle Uchitel. Land Cover Summary Statistics for Antietam National Battlefield. National Park Service, 2023. http://dx.doi.org/10.36967/2301818.

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This technical report documents the acquisition of source data, and calculation of land cover summary statistics datasets for Antietam National Battlefield. The source data and land cover calculations are available for use within the National Park Service (NPS) Inventory &amp; Monitoring (I&amp;M) Program. Land cover summary statistics datasets can be calculated for all geographic regions within the extent of the NPS; this report includes statistics calculated for the conterminous United States. The land cover summary statistics datasets are calculated from multiple sources, including Multi-Re
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Cleary, Summers, Michelle Kinseth, and Michelle Uchitel. Land Cover Summary Statistics for Antietam National Battlefield. National Park Service, 2022. http://dx.doi.org/10.36967/2300391.

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This technical report documents the acquisition of source data, and calculation of land cover summary statistics datasets for Antietam National Battlefield. The source data and land cover calculations are available for use within the National Park Service (NPS) Inventory &amp; Monitoring (I&amp;M) Program. Land cover summary statistics datasets can be calculated for all geographic regions within the extent of the NPS; this report includes statistics calculated for the conterminous United States. The land cover summary statistics datasets are calculated from multiple sources, including Multi-Re
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Christian, Blair, Hilda Klasky, Kevin Sparks, et al. CTSA MHRI Datasets. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1862124.

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