Relevant bibliographies by topics / DM techniques

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

Academic literature on the topic 'DM techniques'

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

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Journal articles on the topic "DM techniques"

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Kumar, R., and Pazhanirajan S. "A Review of Diabetes Mellitus Detection using Machine Learning Techniques." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 10, no. 6 (2021): 32–41. https://doi.org/10.35940/ijitee.F8748.0410621.

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Diabetes Mellitus (DM) is a disease that can lead to a multi-organ malfunctioning in patients due to non-regulated diabetes. Recent advancements in machine learning (ML) and artificial intelligence, the early detection and diagnosis of DM is more advantageous than the manual diagnosis through an automated process. It this review, DM's recognition, diagnosis and self-management techniques from six facets, namely DM datasets, techniques involved in pre-processing, extraction of features; identification through ML; classification and diagnosis of DM; intelligent DM assistant based on artifici
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Критська, Я. О., T. O. Білобородова, and І. С. Скарга-Бандурова. "Data mining techniques for IoT analytics." ВІСНИК СХІДНОУКРАЇНСЬКОГО НАЦІОНАЛЬНОГО УНІВЕРСИТЕТУ імені Володимира Даля, no. 5(253) (September 5, 2019): 53–62. http://dx.doi.org/10.33216/1998-7927-2019-253-5-53-62.

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Data mining (DM) is one of the most valuable technologies enable to identify unknown patterns and make Internet of Things (IoT) smarter. The current survey focuses on IoT data and knowledge discovery processes for IoT. In this paper, we present a systematic review of various DM models and discuss the DM techniques applicable to different IoT data. Some data specific features were analyzed, and algorithms for knowledge discovery in IoT data were considered.Challenges and opportunities for mining multimodal, heterogeneous, noisy, incomplete, unbalanced and biased data as well as massive datasets
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Décaudin, Jean-Marc, and Philippe Malaval. "Le lobbying : techniques, intérêts et limites." Décisions Marketing 50 (April 1, 2008): 59–69. http://dx.doi.org/10.7193/dm.050.59.69.

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Décaudin, Jean-Marc, and Philippe Malaval. "Le lobbying : Techniques, intérêts et limites." Décisions Marketing N° 50, no. 2 (2008): 59–69. http://dx.doi.org/10.3917/dm.050.0059.

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Le lobbying, stratégie d’influence du pouvoir politique, exécutif ou législatif s’est développé récemment en France. Cet article essaie de dresser un état des lieux sur cette technique en s’interrogeant sur les objectifs qu’elle poursuit, sur les cibles qu’elle cherche à toucher et sur les moyens plus ou moins spécifiques qu’elle met en œuvre. Enfin, les questions éthiques liées à la pratique du lobbying sont abordées.
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Kumar, R., and Pazhanirajan S. "A Review of Diabetes Mellitus Detection using Machine Learning Techniques." International Journal of Innovative Technology and Exploring Engineering 10, no. 6 (2021): 32–41. http://dx.doi.org/10.35940/ijitee.f8748.0410621.

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Diabetes Mellitus (DM) is a disease that can lead to a multi-organ malfunctioning in patients due to non-regulated diabetes. Recent advancements in machine learning (ML) and artificial intelligence, the early detection and diagnosis of DM is more advantageous than the manual diagnosis through an automated process. It this review, DM's recognition, diagnosis and self-management techniques from six facets, namely DM datasets, techniques involved in pre-processing, extraction of features; identification through ML; classification and diagnosis of DM; intelligent DM assistant based on artificial i
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Liang, Xi, and De Wen Seng. "Research on the Key Techniques for the Construction of a Digital Mine." Applied Mechanics and Materials 182-183 (June 2012): 734–37. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.734.

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The application of digital technology is a trend that holds considerable promise as shown in many applications. This technology includes the means to integrate and interact with diverse multidimensional data. Digital mine (DM) is the result of integrating various disciplines including mine science, information science, computer science and 3S techniques, which will radically change the traditional mine production and our lifestyles. The functions and main characters of DM are analyzed. A framework for a DM operation system is provided. Key techniques concerned in the implementation of DM are d
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Judson, H. G., S. Mckenzie, S. Robinson, A. Nicholls, and A. J. E. Moorhead. "Measurement techniques and yield estimates of fodder beet in Canterbury and Southland." Journal of New Zealand Grasslands 78 (January 1, 2016): 177–80. http://dx.doi.org/10.33584/jnzg.2016.78.502.

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A survey of commercial fodder beet crops across Canterbury and Southland was undertaken to determine average yields and to provide some basic information on commercial crops. Commercial yields were approximately 19 t DM/ha but higher yields (34 t DM/ha) were achievable. Dry matter content (DM%) of bulbs was higher for lighter than for heavier bulbs. Variation in DM% between bulbs was greater than the variation between parts (inner and outer fractions) of the bulb suggesting a rapid method of sampling multiple bulbs may lead to increases in accuracy of DM% assessment. A rapid coring method was
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Reddiex, S. J., S. D. Wratten, G. D. Hill, G. Bourd?t, and C. M. Frampton. "Evaluation of mechanical weed management techniques on weed and crop populations." New Zealand Plant Protection 54 (August 1, 2001): 174–78. http://dx.doi.org/10.30843/nzpp.2001.54.3717.

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One of the main barriers for conventional farmers converting to organic production is weed control An experiment was set up to evaluate the efficacy of three mechanical weed control methods tine weeder spoon weeder and interrow hoe (only in the beans (Phaseolus vulgaris)) in four organically grown crops In borage (Borago officinalis) weed dry matter (DM) was reduced by 41 in tineweeded plots but there was no treatment effect on crop DM or yield There was no treatment effect in the peas (Pisum sativum) In linseed (Linum usitatissimum) mechanical weeding reduced weed DM by 41 and resulted in a 2
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Larceneux, Fabrice. "Segmentation des signes de qualité : Labels experientiels et labels techniques." Décisions Marketing 29 (January 1, 2003): 35–46. http://dx.doi.org/10.7193/dm.029.35.46.

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M., Mayilvaganan*1 S. Malathi2 &. R. Deepa3. "DATA MINING TECHNIQUES FOR THE ANALYSIS OF KIDNEY DISEASE-A SURVEY." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 7 (2017): 616–22. https://doi.org/10.5281/zenodo.829799.

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Data mining is a vital role in several applications such as business organizations, educational institutions, and government sectors, health care industry, scientific and engineering. In the health care industry, the data mining is predominantly used for disease prediction. In India chronic kidney disease is one of the measure causes of death today. Data mining classifiers are used for prediction which can also be used in health area where a large voluminous data is generated. The healthcare industry are used the data mining techniques for predicting the kidney disease from the data set. So th
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Dissertations / Theses on the topic "DM techniques"

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Peroutka, Lukáš. "Návrh a implementace Data Mining modelu v technologii MS SQL Server." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-199081.

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This thesis focuses on design and implementation of a data mining solution with real-world data. The task is analysed, processed and its results evaluated. The mined data set contains study records of students from University of Economics, Prague (VŠE) over the course of past three years. First part of the thesis focuses on theory of data mining, definition of the term, history and development of this particular field. Current best practices and meth-odology are described, as well as methods for determining the quality of data and methods for data pre-processing ahead of the actual data mining
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Jou, Shiang-Peng, and 周相鵬. "Missing Packet Recovery Techniques for DM Coded Speech." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/91436402108659895257.

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碩士<br>國立交通大學<br>電信研究所<br>85<br>Packet communication increases the utilization efficiency of channel capacity by exploiting the bursty nature of voice traffic. Depending upon the contents of speech packets, numerous recovery techniques have been proposed to combat the packet loss due to channel impairments or excessive delay. Most previous research has emphasized the pissing packet recovery techniques for PCM and DPCM coded speech. When using a DM encoder, however, the missing s
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Ferreira, Edgar da Silva. "WIA-DM ophthalmologic decision support system based on clinical workflow and data mining techniques." Master's thesis, 2007. http://hdl.handle.net/10316/9916.

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Nowadays one can see a wide application of computer systems in Medicine, especially in data acquisition, registry and supply, constituting the so called Electronic Patient Record (EPR) which allows providing information for advanced consultation and processing. The work described in this report is an integrating part of a project that aims the creation of an innovator system for medical diagnosis support in Ophthalmology, in cooperation with a notable clinic. This system makes use of Data Mining techniques on intelligent analysis and processing of medical data in order to improve all sta
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Santos, Armanda. "WIA-DM: Decision support system in ophthalmology based on clinical workflow and data mining techniques = WIA-DM: Sistema de suporte à decisão em oftalmologia baseado em técnicas de workflow clínico e data mining." Master's thesis, 2007. http://hdl.handle.net/10316/12265.

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O presente relatório de projecto descreve o desenvolvimento do projecto “WIA-DM: Sistema de Suporte à Decisão em Oftalmologia baseado em técnicas de workflow e data mining aplicado em dados clínicos”, integrado no curso de Engenharia Biomédica da Faculdade de Ciências e Tecnologia da Universidade de Coimbra, em parceria com a ISA e o CCC. O projecto foi desenvolvido por três alunos, sendo neste relatório evidenciadas as tarefas da aluna Armanda Santos. A ideia principal do projecto é o desenvolvimento de um sistema de suporte ao diagnóstico de patologias maculares, baseado na larga exper
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Barbeiro, Paulo. "WIA-DM Ophthalmologic decision support system based on clinical workflow and data mining techniques = sistema de apoio à decisão para a especialidade de Oftalmologia baseado em técnicas de workflow e data mining aplicadas em dados obtidos em ambiente clínico." Master's thesis, 2007. http://hdl.handle.net/10316/12212.

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A prática da medicina é algo subjectivo, e embora se conheçam muitas das regras lógicas que permitem compreender o corpo humano e doenças que o possam afectar, também é do conhecimento comum que diferentes Médicos especialistas podem ter opiniões diferentes acerca de um mesmo caso clínico. Este relatório descreve o trabalho executado durante o Projecto Final de Engenharia Biomédica, que teve como objectivo a diminuição desta subjectividade através da criação de um sistema de apoio à decisão médica para a área de oftalmologia. Esta ideia inicial foi analisada, discutida com engenheiros e
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Books on the topic "DM techniques"

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Nicholson, Grainne, and George M. Hall. Neuroendocrine physiology in anaesthetic practice. Edited by Jonathan G. Hardman. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0008.

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This chapter describes the hormonal, metabolic, and inflammatory response to surgery—commonly known as the surgical stress response. The changes in protein, carbohydrate, and fat metabolism to provide fuel for oxidation are outlined as well as changes in salt and water metabolism. Psychological sequelae of fatigue and malaise are also common in patients undergoing surgery. Attenuating the metabolic and endocrine changes associated with surgery may reduce postoperative morbidity and expedite recovery; the choice of anaesthetic drugs and techniques (regional vs general anaesthesia) and the incre
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Conant, Emily F. Overview of Digital Breast Tomosynthesis. Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0007.

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Digital breast tomosynthesis (DBT) is a relatively new X-ray technique that allows quasi–three-dimensional imaging of the breast to overcome limitations of conventional 2-D digital mammography (DM). Several early screening studies have shown that DBT reduces the number of false-positive recalls while simultaneously improving the cancer detection rate. Cost-effectiveness studies have shown that incorporating DBT in screening has the potential to save health care dollars due to lower recall rates as well as reduced treatment costs resulting from the earlier detection of breast cancer. In the dia
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Book chapters on the topic "DM techniques"

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Aljebreen, Abdulaziz, Allan Pang, Marc de Kamps, and Owen Johnson. "Predicting Unplanned Hospital Readmissions Using Outcome-Oriented Predictive Process Mining." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82225-4_31.

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Abstract Many hospitals in the world are under pressure to improve their efficiency and effectiveness so that they can achieve better health outcomes with limited resources. One common measure of performance is the rate of unplanned hospital readmissions (UHRs) within 30-days. Emergency readmissions for the same disease can be assumed to indicate inappropriate discharge or poor planning, are costly, increase patients’ mortality risks and put additional pressure on bed capacity. Data Mining (DM) techniques have been used to predict UHRs based on clinical and demographic features, but these igno
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Tamsekar, Preetam, Nilesh Deshmukh, Parag Bhalchandra, et al. "Architectural Outline of Decision Support System for Crop Selection Using GIS and DM Techniques." In Lecture Notes in Networks and Systems. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3935-5_11.

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Szécsényi-Nagy, G. "Wide-Field Photographic Versus Wide-Field CCD Techniques in the Activity Analysis of dM Stars." In Astronomy from Wide-Field Imaging. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1146-1_16.

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Hurtado, Remigio, and Eduardo Ayora. "Intelligent System for Predicting Bank Policy Acceptance by Ensemble Machine Learning and Model Explanation." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-87065-1_41.

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Abstract Efficient management of financial resources is crucial for the sustainability and competitiveness of banks, particularly in optimizing term deposit subscriptions to maintain liquidity. This paper introduces an advanced intelligent system for predicting term deposit acceptance using ensemble machine learning techniques. Our approach combines Random Forest and K-Nearest Neighbors (KNN) models to enhance prediction accuracy while providing clear explanations. The system follows the CRISP-DM methodology, which includes detailed phases of data preparation, modeling, fine-tuning, and model
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Wasnik, Pawan, S. D. Khamitkar, P. U. Bhalchandra, et al. "DSS for Prognostication of Academic Intervention by Applying DM Technique." In Communications in Computer and Information Science. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4859-3_18.

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Kasemthaweesab, Pornnapas, and Werasak Kurutach. "Study of Diabetes Mellitus (DM) with Ophthalmic Complication Using Association Rules of Data Mining Technique." In Computational Collective Intelligence. Technologies and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23935-9_52.

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Caron, I., P. Chaimbault, C. Elfakir, and M. Dreux. "Lc-Elsd or (And) Lc-Ms: A Well Suited Technique For Characterization of the Differences in the Commercially Available Dm-ß-Cds." In Proceedings of the Ninth International Symposium on Cyclodextrins. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4681-4_6.

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Khaira, Ashish, and Ravi K. Dwivedi. "A State-of-the-Art Critique Review of the Role of Decision-Making Techniques in NDT for Condition Monitoring." In Advances in Computer and Electrical Engineering. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6989-3.ch011.

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Nondestructive testing (NDT) is a vital tool in maintenance. Each NDT technique has some benefits and hindrances; therefore, the selection is crucial. Generally, the selection of a technique relies on operating personnel experience, and very few research papers shows uses of the decision-making (DM) approach. It was highlighted by various researchers that if a proper DM approach is used, it will save time and increase fault detection reliability. By keeping this fact in mind, this chapter is an attempt to provide a detailed review of research work from the year 2000-2018 that covered the role
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E., Sabitha. "Artificial Intelligence Approaches in Diabetic Prediction." In Handbook of Research on AI Methods and Applications in Computer Engineering. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6937-8.ch021.

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Healthcare applications in monitoring and managing diseases have undergone rapid development in medical sectors and play an important in observing and controlling diabetes mellitus (DM). DM is a chronic infection that is caused by extreme blood sugar level. The rapid increase of DM world-wide have the effect of gaining attention to predict DM at early stage. Consequently, various technologies have been used to diagnose diabetes at an early stage to avoid major health defects. The most satisfaction in disease prediction and classification methods has been achieved through AI techniques and algo
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Vanani, Iman Raeesi, and Mir Seyed Mohammad Mohsen Emamat. "Analytical Review of the Applications of Multi-Criteria Decision Making in Data Mining." In Optimizing Big Data Management and Industrial Systems With Intelligent Techniques. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5137-9.ch003.

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In recent years, multi-criteria decision making (MCDM) is a significant part of operations research (OR) and has become an interesting topic to researcher who works in the data mining (DM) field. The aim of this chapter is to provide an in-depth presentation of the contribution of MCDM in the field of DM. In order to develop a reliable knowledge base on accumulating knowledge from previous studies, we present a review of the usage of MCDM methods in DM field. The chapter presents methodology and application. The result shows that the most usage of MCDM in DM consists of evaluating classificati
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Conference papers on the topic "DM techniques"

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Al Subhi, Sundos Nasser Said, Chetan Tiwari, and Armin R. Mikler. "Automating Hazard-Specific Ontology Construction: Methodological Advancements through Ontology Learning Techniques from Disaster-Related Knowledge Bases." In 2024 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). IEEE, 2024. https://doi.org/10.1109/ict-dm62768.2024.10798930.

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Chang, Wen-Whei, Hwai-Tsu Chang, and Wan-Yu Meng. "Missing packet recovery techniques for DM coded speech." In 5th European Conference on Speech Communication and Technology (Eurospeech 1997). ISCA, 1997. http://dx.doi.org/10.21437/eurospeech.1997-184.

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Sibru, Dan, Ruslan Belikov, Eduardo A. Bendek, Vladimir N. Dudinov, and Eugene A. Pluzhnik. "Focal plane based wavefront sensing with random DM probes." In Techniques and Instrumentation for Detection of Exoplanets VIII, edited by Stuart Shaklan. SPIE, 2017. http://dx.doi.org/10.1117/12.2274457.

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Raja, Ammar Asjad, Madiha Guftar, Irfan-ul-Haq, Tamim Ahmed Khan, and Dominik Greibl. "Intelligent Syncope Disease prediction framework using DM-ensemble techniques." In 2016 Future Technologies Conference (FTC). IEEE, 2016. http://dx.doi.org/10.1109/ftc.2016.7821621.

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Khalid, Aisha, Ahmed Khedr, Hajar Abdulrahman, and Ahmed M. Zeki. "Identifying State-Specific Customer Churn Patterns using DM Techniques." In 2021 International Conference on Data Analytics for Business and Industry (ICDABI). IEEE, 2021. http://dx.doi.org/10.1109/icdabi53623.2021.9655878.

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Trauger, John, Erkin Sidick, Byoung-Joon Seo, Brian D. Kern, Ilya Poberezhskiy, and Bijan Nemati. "Sensitivity of WFIRST coronagraph broadband contrast performance to DM actuator errors." In Techniques and Instrumentation for Detection of Exoplanets VIII, edited by Stuart Shaklan. SPIE, 2017. http://dx.doi.org/10.1117/12.2274421.

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Parente, M., A. Gomes Correia, and P. Cortez. "Use of DM Techniques in Earthworks Management: A Case Study." In Geo-Hubei 2014 International Conference on Sustainable Civil Infrastructure. American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784478523.001.

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Oliker, Michael D. "Alignment techniques for DM, Lenslet, and WFS camera at the SOR." In Optical Science, Engineering and Instrumentation '97, edited by Robert K. Tyson and Robert Q. Fugate. SPIE, 1997. http://dx.doi.org/10.1117/12.290173.

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Kratov, Denis V., Alexander Berlin, Nikolaj A. Nizhelskij, Peter Tsybulev, Marat Mingaliev, and Roman Udovitskiy. "Techniques for excision RFI on RATAN-600 radio telescope in dm ranges." In RFI mitigation workshop. Sissa Medialab, 2010. http://dx.doi.org/10.22323/1.107.0022.

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Hauke, Krzysztof, Mievzyslaw L. Owoc, and Maciej Pondel. "Building Data Mining Models in the Oracle 9i Environment." In 2003 Informing Science + IT Education Conference. Informing Science Institute, 2003. http://dx.doi.org/10.28945/2697.

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Data Mining (DM) is a very crucial issue in knowledge discovery processes. The basic facilities to create data mining models were implemented successfully on Oracle 9i as the extension of the database server. DM tools enable developers to create Business Intelligence (BI) applications. As a result Data Mining models can be used as support of knowledge-based management. The main goal of the paper is to present new features of the Oracle platform in building and testing DM models. Authors characterize methods of building and testing Data Mining models available on the Oracle 9i platform, stressi
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