Relevant bibliographies by topics / Pre-processing data

Contents

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

Academic literature on the topic 'Pre-processing data'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Pre-processing data"

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Kavitha, M., and M. Kasthuri. "Enco – Standardization Data Pre-Processing Technique in Autism Spectrum Disorder Detection." Indian Journal Of Science And Technology 16, no. 45 (2023): 4156–63. http://dx.doi.org/10.17485/ijst/v16i45.1781.

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Mashuri, Mashuri, Albertus Eka Putra Haryanto, Yola Argatha Manik, Dinar Sukma Dewi, and Tegar Primadana Putra. "Dashboard Pre-Processing Data (DPD) as Data Analysis System with Technological Innovation to Perform Pre-Processing Quantitative Data." IPTEK The Journal of Engineering 9, no. 1 (2023): 35. http://dx.doi.org/10.12962/j23378557.v9i1.a13050.

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Jarolímek, Jan, Jan Pavlík, Jana Kholova, and Swarna Ronanki. "Data Pre-processing for Agricultural Simulations." Agris on-line Papers in Economics and Informatics 11, no. 01 (2019): 49–53. http://dx.doi.org/10.7160/aol.2019.110105.

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S, Vishesh, Manu Srinath, Akshatha C. Kumar, and Nandan A.S. "Data Warehousing Architecture and Pre-Processing." IJARCCE 6, no. 5 (2017): 13–18. http://dx.doi.org/10.17148/ijarcce.2017.6503.

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Wei, Bo, Kai Li, Chengwen Luo, Weitao Xu, Jin Zhang, and Kuan Zhang. "No Need of Data Pre-processing." ACM Transactions on Internet of Things 2, no. 4 (2021): 1–26. http://dx.doi.org/10.1145/3467980.

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Device-free context awareness is important to many applications. There are two broadly used approaches for device-free context awareness, i.e., video-based and radio-based. Video-based approaches can deliver good performance, but privacy is a serious concern. Radio-based context awareness applications have drawn researchers' attention instead, because it does not violate privacy and radio signal can penetrate obstacles. The existing works design explicit methods for each radio-based application. Furthermore, they use one additional step to extract features before conducting classification and
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Bilalli, Besim, Alberto Abelló, Tomàs Aluja-Banet, and Robert Wrembel. "Intelligent assistance for data pre-processing." Computer Standards & Interfaces 57 (March 2018): 101–9. http://dx.doi.org/10.1016/j.csi.2017.05.004.

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Garcia de la Nava, J., S. van Hijum, and O. Trelles. "PreP: gene expression data pre-processing." Bioinformatics 19, no. 17 (2003): 2328–29. http://dx.doi.org/10.1093/bioinformatics/btg318.

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Ashwini Tuppad and Shantala Devi Patil. "Data Pre-processing Issues in Medical Data Classification." Journal of Advanced Zoology 44, S6 (2023): 1079–84. http://dx.doi.org/10.17762/jaz.v44is6.2361.

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With digitalization of data and the rise of World Wide Web, access to information has been very easy and affordable. Especially the Web and the Internet have boosted research activities by facilitating access to large, publicly available medical datasets under open access scheme. These developments have resulted in explosive amounts of data being generated varying in volume, variety and velocity thus referred to as big data. Availability of such medical big data has catalyzed the research in medical predictive analytics. However, the true value of such data can be derived only after subjecting
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Martens, Harald, Martin Høy, Barry M. Wise, Rasmus Bro, and Per B. Brockhoff. "Pre-whitening of data by covariance-weighted pre-processing." Journal of Chemometrics 17, no. 3 (2003): 153–65. http://dx.doi.org/10.1002/cem.780.

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K., Dharani* &. Dr. G. Abel Thangaraja**. "BIG DATA PREPROCESSING USING ENHANCED DATA QUALITY RULES DISCOVERY MODEL (EDQRM)." International Journal of Engineering Research and Modern Education (IJERME) 8, no. 2 (2023): 33–41. https://doi.org/10.5281/zenodo.8428545.

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In the Big Data Era, data is the center for any governmental, institutional, and private organization. Endeavors were equipped towards extricating profoundly important bits of knowledge that can't occur assuming data is of low quality. Hence, data quality (DQ) is considered as a vital component in big data processing. In this stage, bad quality data isn't entered to the Big Data value chain. This paper, proposed the Enhanced data quality Rules discovery model (EDQRM) for assessment of quality and Big Data pre-processing. EDQRM discovery model to improve and precisely focus on the pre-p
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Dissertations / Theses on the topic "Pre-processing data"

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Bilalli, Besim. "Learning the impact of data pre-processing in data analysis." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/587221.

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There is a clear correlation between data availability and data analytics, and hence with the increase of data availability --- unavoidable according to Moore's law, the need for data analytics increases too. This certainly engages many more people, not necessarily experts, to perform analytics tasks. However, the different, challenging, and time consuming steps of the data analytics process, overwhelm non-experts and they require support (e.g., through automation or recommendations). A very important and time consuming step that marks itself out of the rest, is the data pre-processing step.
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Khondoker, Md Mizanur Rahman. "Statistical methods for pre-processing microarray gene expression data." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/12367.

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A novel method is developed for combining multiple laser scans of microarrays to correct for “signal saturation” and “signal deterioration” effects in the gene expression measurement. A multivariate nonlinear functional regression model with Cauchy distributed errors having additive plus multiplicative scale is proposed as a model for combining multiple scan data. The model has been found to flexibly describe the nonlinear relationship in multiple scan data. The heavy tailed Cauchy distribution with additive plus multiplicative scale provides a basis for objective and robust estimation of gene
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Mukun, Wang, Liu Gozhi, and Li Zhenglian. "HARDWARE PRE-PROCESSING FOR DATA OF UNDERWATER MEASURING SYSTEM." International Foundation for Telemetering, 1991. http://hdl.handle.net/10150/612907.

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International Telemetering Conference Proceedings / November 04-07, 1991 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>The synchro double pulse signal mode is freqently used in Short Base Line (SBL) underwater positioning system so as to obtain the information of both distance and depth of a target simultaneously. Howerer, this signal mode also brings about ranging indistinctness resulting in a shorter positioning distance much less than that limited by the period of the synchro signal. This paper presents a hardware distance gate date acquiring scheme. It puts the original data
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Giovanelli, Joseph. "AutoML: A new methodology to automate data pre-processing pipelines." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20422/.

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It is well known that we are living in the Big Data Era. Indeed, the exponential growth of Internet of Things, Web of Things and Pervasive Computing systems greatly increased the amount of stored data. Thanks to the availability of data, the figure of the Data Scientist has become one of the most sought, because he is capable of transforming data, performing analysis on it, and applying Machine Learning techniques to improve the business decisions of companies. Yet, Data Scientists do not scale. It is almost impossible to balance their number and the required effort to analyze the increasingly
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Patel, Ankur. "3D morphable models : data pre-processing, statistical analysis and fitting." Thesis, University of York, 2011. http://etheses.whiterose.ac.uk/1576/.

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This thesis presents research aimed at using a 3D linear statistical model (known as a 3D morphable model) of an object class (which could be faces, bodies, cars, etc) for robust shape recovery. Our aim is to use this recovered information for the purposes of potentially useful applications like recognition and synthesis. With a 3D morphable model as its central theme, this thesis includes: a framework for the groupwise processing of a set of meshes in dense correspondence; a new method for model construction; a new interpretation of the statistical constraints afforded by the model and addres
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Hutton, Tanya. "Sensitivity of fusion neutronics to the pre-processing of nuclear data." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6724/.

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Nuclear data are the foundation of simulation and design in the nuclear industry. The success of commercialising thermonuclear fusion will be based on a set of highly accurate simulations used in design, optimisation and safety analyses. This work focuses on the often overlooked, pre-processing stage of nuclear data. The effect of legacy methods in a fusion context is a concern within the community, but has never been quantified. The sensitivity of fusion neutronics to pre-processing was determined using a set of codes and methods developed as part of this thesis. Legacy pre-processing methods
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Pettersson, Hanna. "Estimation and Pre-Processing of Sensor Data in Heavy Duty Vehicle Platooning." Thesis, Linköpings universitet, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79038.

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Today, a rapid development towards fuel efficient technological aids for vehicles is in progress. One step towards this is the development of platooning systems. The main concept of platooning is to let several heavy duty vehicles (HDVs) drive in a convoy and share important information with each other via wireless communication. This thesis describes one out of three subsystems in a project developed to handle the process from raw sensor data to control signal. The goal of the project is to achieve a safe and smooth control with the main purpose of reduced fuel consumption. This subsystem pro
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Abdul, Rahim Siti Khatijah Nor. "Transformation of the university examination timetabling problem space through data pre-processing." Thesis, University of Nottingham, 2015. http://eprints.nottingham.ac.uk/28895/.

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This research investigates Examination Timetabling or Scheduling, with the aim of producing good quality, feasible timetables that satisfy hard constraints and various soft constraints. A novel approach to scheduling, that of transformation of the problem space, has been developed and evaluated for its effectiveness. The examination scheduling problem involves many constraints due to many relationships between students and exams, making it complex and expensive in terms of time and resources. Despite the extensive research in this area, it has been observed that most of the published methods d
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Rahman, M. Mostafizur. "Machine learning based data pre-processing for the purpose of medical data mining and decision support." Thesis, University of Hull, 2014. http://hydra.hull.ac.uk/resources/hull:10103.

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Building an accurate and reliable model for prediction for different application domains, is one of the most significant challenges in knowledge discovery and data mining. Sometimes, improved data quality is itself the goal of the analysis, usually to improve processes in a production database and the designing of decision support. As medicine moves forward there is a need for sophisticated decision support systems that make use of data mining to support more orthodox knowledge engineering and Health Informatics practice. However, the real-life medical data rarely complies with the requirement
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Pabarškaitė, Židrina. "Enhancements of pre-processing, analysis and presentation techniques in web log mining." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090713_142203-05841.

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As Internet is becoming an important part of our life, more attention is paid to the information quality and how it is displayed to the user. The research area of this work is web data analysis and methods how to process this data. This knowledge can be extracted by gathering web servers’ data – log files, where all users’ navigational patters about browsing are recorded. The research object of the dissertation is web log data mining process. General topics that are related with this object: web log data preparation methods, data mining algorithms for prediction and classification tasks, web
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Books on the topic "Pre-processing data"

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Ahmad, Masri Bin. PC graphical pre- and post-processing of finele data. UMIST, 1996.

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Dombroff, Mark A. Litigation organization and management. 2nd ed. Prentice Hall Law & Business, 1991.

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Shi, Feng. Learn About Text Pre-Processing in R With Data From How ISIS Uses Twitter Dataset (2016). SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526488909.

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Shi, Feng. Learn About Text Pre-Processing in Python With Data From How ISIS Uses Twitter Dataset (2016). SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526497864.

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1959-, Kanellopoulos I., ed. Neurocomputation in remote sensing data analysis: Proceedings of concerted action COMPARES (connectionist methods for pre-processing and analysis of remote sensing data). Springer, 1997.

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Martinez, Julia. Learn Data Preparation and Pre-Processing in SPSS With an Online Survey of Correlates of Heavy Drinking (2012). SAGE Publications Ltd., 2019. http://dx.doi.org/10.4135/9781526474902.

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1945-, Clark Andrew, and Lynas David 1964-, eds. Enterprise security architecture: A business-driven approach. CMP Books, 2005.

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Center, Federal Judicial, and National Institute for Trial Advocacy (U.S.), eds. Effective use of courtroom technology: A judge's guide to pretrial and trial. Federal Judicial Center, 2001.

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Kiely, Terrence F. Using litigation databases. Wiley Law Publications, 1987.

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Southern Africa Transport and Communications Commission., ed. Telecommunications statistics database system: Pre-study report. Southern Africa Transport and Communications Commision, 1991.

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Book chapters on the topic "Pre-processing data"

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Christen, Peter. "Data Pre-Processing." In Data Matching. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31164-2_3.

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Kuhn, Max, and Kjell Johnson. "Data Pre-processing." In Applied Predictive Modeling. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6849-3_3.

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Malley, Brian, Daniele Ramazzotti, and Joy Tzung-yu Wu. "Data Pre-processing." In Secondary Analysis of Electronic Health Records. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43742-2_12.

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Ghosh, Chandril. "Data Pre-processing." In Data Analysis with Machine Learning for Psychologists. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14634-3_3.

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Lin, Hui, and Ming Li. "Data Pre-processing." In Practitioner’s Guide to Data Science. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781351132916-5.

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Finlay, Steven. "Data Pre-processing." In Credit Scoring, Response Modelling and Insurance Rating. Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230298989_6.

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Maimon, Oded, and Mark Last. "Automated Data Pre-Processing." In Knowledge Discovery and Data Mining. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3296-2_2.

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Hong, Wei-Chiang. "Data Pre-processing Methods." In Hybrid Intelligent Technologies in Energy Demand Forecasting. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36529-5_3.

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Finlay, Steven. "Data Transformation (Pre-processing)." In Credit Scoring, Response Modeling, and Insurance Rating. Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1057/9781137031693_6.

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Teye, Ernest, and Charles Lloyd Yeboah Amuah. "Data Pre-processing Techniques." In Application of Fluorescence Spectroscopy in Food Quality and Control. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89681-1_2.

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Conference papers on the topic "Pre-processing data"

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Maas, Rene, Eduard Shevtshenko, and Tatjana Karaulova. "AI generated route data pre - processing for faster decision making." In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering (YEF-ECE). IEEE, 2024. http://dx.doi.org/10.1109/yef-ece62614.2024.10625086.

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Saranya, V., Devi T, and N. Deepa. "Enhanced Systematic Structure for Data Pre-Processing and Intensifying Data Augmentation for Audio Data Processing with SS-GRNN Technique." In 2025 4th International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE). IEEE, 2025. https://doi.org/10.1109/icdcece65353.2025.11035421.

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Tagliabue, Jacopo, Ryan Curtin, and Ciro Greco. "FaaS and Furious: abstractions and differential caching for efficient data pre-processing." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825377.

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Ribeiro, Marcela X., Mônica R. P. Ferreira, Caetano Traina, and Agma J. M. Traina. "Data pre-processing." In the 5th international conference. ACM Press, 2008. http://dx.doi.org/10.1145/1456223.1456277.

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Frigui, H. "Pre-processing for data clustering." In IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04. IEEE, 2004. http://dx.doi.org/10.1109/nafips.2004.1337437.

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Batista, Lu, and Lu Alexandre. "Text Pre-processing for Lossless Compression." In 2008 Data Compression Conference DCC. IEEE, 2008. http://dx.doi.org/10.1109/dcc.2008.78.

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Vu, Minh Thanh, Tobias J. Oechtering, and Mikael Skoglund. "Gaussian Hierarchical Identification with Pre-processing." In 2018 Data Compression Conference (DCC). IEEE, 2018. http://dx.doi.org/10.1109/dcc.2018.00036.

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Saleem, Asma, Khadim Hussain Asif, Ahmad Ali, Shahid Mahmood Awan, and Mohammed A. Alghamdi. "Pre-processing Methods of Data Mining." In 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC). IEEE, 2014. http://dx.doi.org/10.1109/ucc.2014.57.

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Gan, Jiangying, and Zhijun Xu. "Pre-Processing VDIF Data in FPGA." In 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama). IEEE, 2018. http://dx.doi.org/10.23919/piers.2018.8597678.

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Lv, Qiujuan, and Suping Fang. "ICT slice profile data pre-processing." In 2010 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2010. http://dx.doi.org/10.1109/icma.2010.5588019.

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Reports on the topic "Pre-processing data"

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Hennekens, S. M., W. A. Ozinga, and J. H. J. Schaminée. BioScore 3 - Plants : Background and pre-processing of distribution data. Wageningen University & Research, Statutory Research Tasks Unit for Nature & the Environment, 2017. http://dx.doi.org/10.18174/428824.

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Tayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2014.

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As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and f
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Taasevigen, Danny J. User's Guide to Pre-Processing Data in Universal Translator 2 for the Energy Charting and Metrics Tool (ECAM). Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1032417.

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Cossarini, Gianpiero. Results of the BGC data assimilation. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.10.

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This document presents the results of simulations that include glider profiles assimilation. Simulations are performed with the Marine Copernicus operational biogeochemical model system of the Mediterranean Sea. The deliverable shows that the assimilation of BGC-glider is feasible in the contest of biogeochemical operational systems and that it is built upon the experience of BGC-Argo float data assimilation. Different configuration of the assimilation of glider data have been tested to assess the impact of the physical and biogeochemical glider observations. The deliverable also describes the
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Bauer, Andrew, James Forsythe, Jayanarayanan Sitaraman, Andrew Wissink, Buvana Jayaraman, and Robert Haehnel. In situ analysis and visualization to enable better workflows with CREATE-AV™ Helios. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40846.

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The CREATE-AV™ Helios CFD simulation code has been used to accurately predict rotorcraft performance under a variety of flight conditions. The Helios package contains a suite of tools that contain almost the entire set of functionality needed for a variety of workflows. These workflows include tools customized to properly specify many in situ analysis and visualization capabilities appropriate for rotorcraft analysis. In situ is the process of computing analysis and visualization information during a simulation run before data is saved to disk. In situ has been referred to with a variety of te
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Choquette, Gary. PR-000-16209-WEB Data Management Best Practices Learned from CEPM. Pipeline Research Council International, Inc. (PRCI), 2019. http://dx.doi.org/10.55274/r0011568.

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DATE: Wednesday, May 1, 2019 TIME: 2:00 - 3:30 p.m. ET PRESENTER: Gary Choquette, PRCI CLICK DOWNLOAD/BUY TO ACCESS THE REGISTRATION LINK FOR THIS WEBINAR Systems that manage large sets of data are becoming more common in the energy transportation industry. Having access to the data offers the opportunity to learn from previous experiences to help efficiently manage the future. But how does one manage to digest copious quantities of data to find nuggets within the ore? This webinar will outline some of the data management best practices learned from the research projects associated with CEPM.
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O'Neill, Francis, Kristofer Lasko, and Elena Sava. Snow-covered region improvements to a support vector machine-based semi-automated land cover mapping decision support tool. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45842.

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This work builds on the original semi-automated land cover mapping algorithm and quantifies improvements to class accuracy, analyzes the results, and conducts a more in-depth accuracy assessment in conjunction with test sites and the National Land Cover Database (NLCD). This algorithm uses support vector machines trained on data collected across the continental United States to generate a pre-trained model for inclusion into a decision support tool within ArcGIS Pro. Version 2 includes an additional snow cover class and accounts for snow cover effects within the other land cover classes. Overa
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Liu, X., Z. Chen, and S. E. Grasby. Using shallow temperature measurements to evaluate thermal flux anomalies in the southern Mount Meager volcanic area, British Columbia, Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330009.

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Geothermal is a clean and renewable energy resource. However, locating where elevated thermal gradient anomalies exist is a significant challenge when trying to assess potential resource volumes during early exploration of a prospective geothermal area. In this study, we deployed 22 temperature probes in the shallow subsurface along the south flank of the Mount Meager volcanic complex, to measure the transient temperature variation from September 2020 to August 2021. In our data analysis, a novel approach was developed to estimate the near-surface thermal distribution, and a workflow and code
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Li, Honghai, Mitchell Brown, Lihwa Lin, et al. Coastal Modeling System user's manual. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48392.

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The Coastal Modeling System (CMS) is a suite of coupled 2D numerical models for simulating nearshore waves, currents, water levels, sediment transport, morphology change, and salinity and temperature. Developed by the Coastal Inlets Research Program of the US Army Corps of Engineers, the CMS provides coastal engineers and scientists a PC-based, easy-to-use, accurate, and efficient tool for understanding of coastal processes and for designing and managing of coastal inlets research, navigation projects, and sediment exchange between inlets and adjacent beaches. The present technical report acts
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Lasko, Kristofer, and Elena Sava. Semi-automated land cover mapping using an ensemble of support vector machines with moderate resolution imagery integrated into a custom decision support tool. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42402.

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Land cover type is a fundamental remote sensing-derived variable for terrain analysis and environmental mapping applications. The currently available products are produced only for a single season or a specific year. Some of these products have a coarse resolution and quickly become outdated, as land cover type can undergo significant change over a short time period. In order to enable on-demand generation of timely and accurate land cover type products, we developed a sensor-agnostic framework leveraging pre-trained machine learning models. We also generated land cover models for Sentinel-2 (
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