Relevant bibliographies by topics / Data driven frame work

Contents

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

Academic literature on the topic 'Data driven frame work'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Data driven frame work"

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Gothard, Andrew, Daniel Jones, Andre Green, Michael Torrez, Alessandro Cattaneo, and David Mascareñas. "Digital coded exposure formation of frames from event-based imagery." Neuromorphic Computing and Engineering 2, no. 1 (2022): 014005. http://dx.doi.org/10.1088/2634-4386/ac4917.

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Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into
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Yu, Siwei, Jianwei Ma, and Stanley Osher. "Monte Carlo data-driven tight frame for seismic data recovery." GEOPHYSICS 81, no. 4 (2016): V327—V340. http://dx.doi.org/10.1190/geo2015-0343.1.

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Seismic data denoising and interpolation are essential preprocessing steps in any seismic data processing chain. Sparse transforms with a fixed basis are often used in these two steps. Recently, we have developed an adaptive learning method, the data-driven tight frame (DDTF) method, for seismic data denoising and interpolation. With its adaptability to seismic data, the DDTF method achieves high-quality recovery. For 2D seismic data, the DDTF method is much more efficient than traditional dictionary learning methods. But for 3D or 5D seismic data, the DDTF method results in a high computation
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Vegesna, Dr Vinod. "AI-Driven Personalized Medicine: A Frame Work for Tailored Cancer Treatment." International Journal of Innovative Research in Advanced Engineering 11, no. 06 (2024): 747–52. http://dx.doi.org/10.26562/ijirae.2024.v1106.06.

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Regardless of the variability of the disease and the individual variances among patients, cancer treatment has historically taken a standardised approach, which frequently leads to less than ideal results. By customising treatment plans to each patient's distinct genetic, phenotypic, and clinical characteristics, AI-driven personalised medicine has the promise of completely changing the way cancer is treated. This study suggests a thorough framework for predicting the best course of treatment for each patient by combining multi-omics data, electronic health records (EHRs), and empirical eviden
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Tumpa, Tasmia Rahman, Shelley N. Acuff, Jens Gregor, Yong Bradley, Yitong Fu, and Dustin R. Osborne. "Data-driven head motion correction for PET using time-of-flight and positron emission particle tracking techniques." PLOS ONE 17, no. 8 (2022): e0272768. http://dx.doi.org/10.1371/journal.pone.0272768.

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Objectives Positron emission tomography (PET) is susceptible to patient movement during a scan. Head motion is a continuing problem for brain PET imaging and diagnostic assessments. Physical head restraints and external motion tracking systems are most commonly used to address to this issue. Data-driven methods offer substantial advantages, such as retroactive processing but typically require manual interaction for robustness. In this work, we introduce a time-of-flight (TOF) weighted positron emission particle tracking (PEPT) algorithm that facilitates fully automated, data-driven head motion
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Howard-Grenville, Jennifer, Andrew J. Nelson, Andrew G. Earle, Julie A. Haack, and Douglas M. Young. "“If Chemists Don’t Do It, Who Is Going To?” Peer-driven Occupational Change and the Emergence of Green Chemistry." Administrative Science Quarterly 62, no. 3 (2017): 524–60. http://dx.doi.org/10.1177/0001839217690530.

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We investigate the emergence and growth of “green chemistry”—an effort by chemists to encourage other chemists to reduce the health, safety, and environmental impacts of chemical products and processes—to explore how occupational members, absent external triggers for change, influence how their peers do their work. Using extensive interviews, archival data, and observations, we find that advocates simultaneously advanced different frames that specified the utility of making the change: (1) a normalizing frame, positioning green chemistry as consistent with mainstream chemistry innovation; (2)
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Thajchayapong, Ploy, and Ashok K. Goel. "Personalized Learning through AI-Driven Data Pipeline." Proceedings of the AAAI Symposium Series 5, no. 1 (2025): 111–14. https://doi.org/10.1609/aaaiss.v5i1.35572.

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The integration of artificial intelligence (AI) in education holds significant promise for transforming personalized learning. By analyzing student learning data, AI systems can adapt instruction to meet individual needs through tailored content, adaptive learning paths, real-time feedback, and continuous improvement loops. However, effective personalization at scale demands not only access to large volumes of learner data but also robust data architectures to collect, organize, standardize, and analyze that data in a secure and meaningful way. However, note that the ability of AI to personali
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Nennuri, Rajasekhar, Atmakuri Krishna Chaitanya, and Lakshmi Prasanthi Malyala. "Implementation of data frame work system based on model driven architecture for MAS and Web based applications." International Journal of Engineering & Technology 7, no. 2.20 (2018): 1. http://dx.doi.org/10.14419/ijet.v7i2.20.11730.

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To utilize those Incomprehensible measures from claiming data effectively on the Web to make the data transforming intelligent, customize Furthermore programmed will be those A large portion vital requisitions of the present information mining innovation organization. Model driven Architecture (MDA) which will be utilized for code era need huge numbers profits In conventional product improvement routines. In this paper, Web information mining transform is acquainted from the see for function, a canny mining framework from claiming data is based for joining together those information mining. Th
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Sánchez-Borrego, Ismael, María del Mar Rueda, and Héctor Mullo. "Estimation of Non-Linear Parameters with Data Collected Using Respondent-Driven Sampling." Mathematics 8, no. 8 (2020): 1315. http://dx.doi.org/10.3390/math8081315.

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Respondent-driven sampling (RDS) is a snowball-type sampling method used to survey hidden populations, that is, those that lack a sampling frame. In this work, we consider the problem of regression modeling and association for continuous RDS data. We propose a new sample weight method for estimating non-linear parameters such as the covariance and the correlation coefficient. We also estimate the variances of the proposed estimators. As an illustration, we performed a simulation study and an application to an ethnic example. The proposed estimators are consistent and asymptotically unbiased. W
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Law, James. "Constructional change and frameelement selection." Constructions and Frames 15, no. 1 (2023): 119–44. http://dx.doi.org/10.1075/cf.00069.law.

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Abstract While most work in diachronic construction grammar considers individual constructional changes, these changes share an understudied relationship with broader changes at the level of the semantic frame. Literary corpus data shows that in the Spending frame in French, between the 12th and 20th centuries, the selection rates of four alternating frame elements shifted: Purpose, Cause of expense, Goods, and Seller. This frame-level shift is examined alongside related constructional changes including lexicalization, pejoration, and constructional loss. The analysis suggests that constructio
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Zhang, Meng, Duygu Ceylan, and Niloy J. Mitra. "Motion Guided Deep Dynamic 3D Garments." ACM Transactions on Graphics 41, no. 6 (2022): 1–12. http://dx.doi.org/10.1145/3550454.3555485.

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Realistic dynamic garments on animated characters have many AR/VR applications. While authoring such dynamic garment geometry is still a challenging task, data-driven simulation provides an attractive alternative, especially if it can be controlled simply using the motion of the underlying character. In this work, we focus on motion guided dynamic 3D garments, especially for loose garments. In a data-driven setup, we first learn a generative space of plausible garment geometries. Then, we learn a mapping to this space to capture the motion dependent dynamic deformations, conditioned on the pre
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Dissertations / Theses on the topic "Data driven frame work"

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Draicchio, Francesco. "Frame-driven Extraction of Linked Data and Ontologies from Text." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3165/.

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Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and
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Grunden, Beverly K. "On the Characteristics of a Data-driven Multi-scale Frame Convergence Algorithm." Wright State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=wright1622208959661057.

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Agerskans, Natalie. "A Framework for Achieving Data-Driven Decision Making in Production Development." Thesis, Mälardalens högskola, Innovation och produktrealisering, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48133.

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Industry 4.0 and the development of novel digital technologies is forcing manufacturing companies to introduce drastic changes to their productions systems. These technologies provide unique opportunities for manufacturing companies to collect, process and store large data volumes, which can be used to facilitate the coordination of factory elements. Previous research indicate that decisions based on data can provide fact-based decisions which can contribute to an increased productivity. However, manufacturing companies are not fully exploiting data as support for decision-making, which is des
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Falkenstrand, Johanna, and Camilla Lemos. "Fostering Proactiveness in Data-Driven Matrix Organizations : A Study of Alfa Laval's Distribution Center in Tumba." Thesis, KTH, Industriell produktion, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254341.

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Globalization has increased the complexity of the business world, as it adds new dimensions to companies’ operations, such as global suppliers and customers, and competition from global actors. To handle the complexity, companies are pressured to become more data-driven to be able to measure and align their operations, and create possibilities for efficiency and competitiveness [Skjott-Larsen etal., 2007; Long, 2018]. In order to enable the change towards becoming more data-driven, companies need to rethink the structure of their organization. Matrix structures have gained popularity, since it
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Stella, Federico. "Learning a Local Reference Frame for Point Clouds using Spherical CNNs." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20197/.

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Uno dei problemi più importanti della 3D Computer Vision è il cosiddetto surface matching, che consiste nel trovare corrispondenze tra oggetti tridimensionali. Attualmente il problema viene affrontato calcolando delle feature locali e compatte, chiamate descrittori, che devono essere riconosciute e messe in corrispondenza al mutare della posa dell'oggetto nello spazio, e devono quindi essere invarianti rispetto all'orientazione. Il metodo più usato per ottenere questa proprietà consiste nell'utilizzare dei Local Reference Frame (LRF): sistemi di coordinate locali che forniscono un'orientazione
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Hostiuck, Katherine E. "A Study of School Climate and Its Relationship to the Accountability-Focused Work ofPrincipals." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1438420249.

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Johansson, Antonia, and Filip Lindgren. "“Jag tror att man som företag säger sig vara ganska datadriven i sina beslut” : En kvalitativ studie om Business intelligence och datadrivenhet i ett svenskt konsultföretag." Thesis, Södertörns högskola, Institutionen för naturvetenskap, miljö och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-45639.

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In an increasingly digital world, companies need to be at the forefront of development in order to gain market share and be competitive. Therefore this qualitative case study intends to investigate how Business intelligence should be implemented to increase the technology acceptance among the employees. Furthermore, it is investigated how data-driven a consulting company in Sweden is. An important factor when Business intelligence is about to be implemented and applied are the employees and the company culture. It is important to normalize the collection of data, in order to create a data cult
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Teng, Sin Yong. "Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-433427.

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S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a pr
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Vyas, Gayatri Sachin. "Development of a frame work for Indian green building rating system." Thesis, 2017. http://localhost:8080/iit/handle/2074/7433.

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Books on the topic "Data driven frame work"

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Sea We Swim In: How Stories Work Ina Data-Driven World. Norton & Company Limited, W. W., 2024.

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Sea We Swim In: How Stories Work in a Data-Driven World. Norton & Company Limited, W. W., 2021.

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Sea We Swim In: How Stories Work in a Data-Driven World. Norton & Company, Incorporated, W. W., 2021.

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Achor, Shawn, and Jennifer Moss. Unlocking Happiness at Work: How a Data-Driven Happiness Strategy Fuels Purpose, Passion and Performance. Kogan Page, Limited, 2016.

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Achor, Shawn, and Jennifer Moss. Unlocking Happiness at Work: How a Data-driven Happiness Strategy Fuels Purpose, Passion and Performance. Kogan Page, 2021.

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Achor, Shawn, author of introduction, ed. Unlocking happiness at work: How a data-driven happiness strategy fuels purpose, passion and performance. Kogan Page, 2016.

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Graziano, Leigh, and Remi Hudgins. Making Administrative Work Visible: Data-Driven Advocacy for Understanding the Labor of Writing Program Administration. University Press of Colorado, 2023.

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Graziano, Leigh, and Remi Hudgins. Making Administrative Work Visible: Data-Driven Advocacy for Understanding the Labor of Writing Program Administration. University Press of Colorado, 2023.

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Sihn, Wilfried, and Sebastian Schlund. Competence development and learning assistance systems for the data-driven future. Goto Verlag, 2021. http://dx.doi.org/10.30844/wgab_2021.

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The continuous acquisition of new digital competences and the development of situational learning assistance systems will become more important than ever in the coming years, because the world of work is becoming more complex, more informative and all above more data-driven. Jobs are changing due to increasing digitalisation, whereby the use of modern technologies must be designed in a way, that employees can continue to work productively in the company despite these changes and benefit purposefully from digital solutions. The research results presented under the main topic „Competence develop
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Heitzeg, Nancy A. The School-to-Prison Pipeline. ABC-CLIO, LLC, 2016. http://dx.doi.org/10.5040/9798216011392.

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This book offers a research and comparison-driven look at the school-to-prison pipeline, its racial dynamics, the connections to mass incarceration, and our flawed educational climate—and suggests practical remedies for change. How is racism perpetuated by the education system, particularly via the "school-to-prison pipeline?" How is the school to prison pipeline intrinsically connected to the larger context of the prison industrial complex as well as the extensive and ongoing criminalization of youth of color? This book uniquely describes the system of policies and practices that racialize cr
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Book chapters on the topic "Data driven frame work"

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Berthet, Valentine, Barbara Gaweda, Johanna Kantola, Cherry Miller, Petra Ahrens, and Anna Elomäki. "Interpreting the Data." In Guide to Qualitative Research in Parliaments. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39808-7_6.

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AbstractOnce the data (or part of it) is coded it becomes possible to move on to the next step, which is to interpret the data in view of answering research questions. Interpreting the data is a crucial step in the qualitative research process—it is core to qualitative data analysis. Hence, the volume dedicates a whole chapter to it. This Chapter presents key methodological steps and strategies to interpret the data for the purpose of individual studies for peer-reviewed articles. It covers practical steps such as exporting code reports from Atlas.ti and reviewing them in a collaborative fashi
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Quick, Darren, and Kim-Kwang Raymond Choo. "Data Reduction and Data Mining Frame-Work." In SpringerBriefs on Cyber Security Systems and Networks. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7763-0_3.

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Elmer, Christina, Jonathan Schwabish, and Benjamin Wiederkehr. "Organizing the Work of Data-Driven Visual Storytelling." In Data-Driven Storytelling. A K Peters/CRC Press, 2018. http://dx.doi.org/10.1201/9781315281575-8.

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Parker, Austin, Gerardo I. Simari, Amy Sliva, and V. S. Subrahmanian. "Introduction and Related Work." In Data-driven Generation of Policies. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4939-0274-3_1.

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Morelli, Neil. "Work Analysis-based Job Descriptions." In Data-Driven Decision Making in Entrepreneurship. CRC Press, 2024. http://dx.doi.org/10.1201/9781003196853-3.

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Chen, Zhiwen. "Conclusions and Future Work." In Data-Driven Fault Detection for Industrial Processes. Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-16756-1_8.

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Schlinkert, Anne Mareike, Leonhard Kunczik, Orlando Hohmeier, and Michael Kuehne-Schlinkert. "Preserving Digital Sovereignty in Data-Driven Manufacturing Networks." In New Digital Work II. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-69994-8_16.

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Abstract Leveraging data in collaboration with other organizations requires resolving a paradox: Organizations of Manufacturing Networks must find a way to share data while protecting their own intellectual property. Vertical Federated Learning (VFL) allows collaborative machine learning without compromising data privacy, as it keeps data local. It facilitates effective, secure data-driven enhancements across organizations and country borders, enabling more efficient, more sustainable, and more customer-focused production.
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Singh, Devendra Pal, Sachin Gupta, D. Ganesh, et al. "Technologies that Work Together for Precision Agriculture." In Data Driven Mathematical Modeling in Agriculture. River Publishers, 2024. http://dx.doi.org/10.1201/9781003515883-17.

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Patel, Mayank, Saurabh Srivastava, Harshita Jain, and Milind D. Jain. "Time Restricted Frame Aggregation for Better QoS in IEEE 802.11ac." In Studies in Autonomic, Data-driven and Industrial Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3915-9_20.

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Mavani, Monali, and Leena Ragha. "MapReduce Frame Work: Investigating Suitability for Faster Data Analytics." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36321-4_11.

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Conference papers on the topic "Data driven frame work"

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Jr., Robert. "Surface Mount On-Blade Optical Telemetry System." In Vertical Flight Society 80th Annual Forum & Technology Display. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0080-2024-1219.

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AAM concepts use multiple distributed electric motors driving propellers and rotors to augment or directly generate lift and propulsive forces. Several current concepts incorporate separate drive systems for providing vertical lift, for takeoff and landing, and propulsive thrust for wing-borne cruising flight. Measurement of loads and performance on these rotating systems is very important in both the design and development stage, as well as for certification use and ultimately supporting HUMS monitoring. However, providing instrumentation in the rotating frame and extracting their associated
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Zhu, Lixun, and Xiaohua Li. "Measurement of Automobile Frame Circular Holes Based on Point Cloud Completion." In 2025 IEEE 14th Data Driven Control and Learning Systems (DDCLS). IEEE, 2025. https://doi.org/10.1109/ddcls66240.2025.11064988.

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Stephen, Navya, S. Saranya, Betty Martin, and Rajesh Anbazhagan. "Machine Learning-Driven Thermal Imaging Frame Work for Early Detection of Red Palm Weevil Infestation." In 2025 International Conference in Advances in Power, Signal, and Information Technology (APSIT). IEEE, 2025. https://doi.org/10.1109/apsit63993.2025.11086254.

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Zhang, Yukang, Jianchao Zheng, Junwei Luo, and Xiaohui Yan. "A Path Planning Approach for Optic Inspection Based on Composite Frame." In 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2024. http://dx.doi.org/10.1109/docs63458.2024.10704497.

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MUHOMI, Hassan, and Troels MØNSTED. "Challenges for Data-Driven Health Planning in Primary Healthcare Facilities: A Data Work Perspective." In 2025 IST-Africa Conference (IST-Africa). IEEE, 2025. https://doi.org/10.23919/ist-africa67297.2025.11060496.

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Brands, Ren�, Vikas Kumar Mishra, Jens Bartsch, Mohammad Al Khatib, Markus Thommes, and Naim Bajcinca. "From Experiment Design to Data-Driven Modeling of Powder Compaction Process." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.101076.

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Tableting is a dry granulation process for compacting powder blends into tablets. In this process, a blend of active pharmaceutical ingredients (APIs) and excipients are fed into the hopper of a rotary tablet press via feeders. Inside the tablet press, rotating feed frame paddle wheels fill powder into dies, with tablet mass adjusted by the lower punch position during the die filling process. Pre-compression rolls press air out of the die, while main compression rolls apply the force necessary for compacting the powder into tablets. In this paper, process variables such as feeder screw speeds,
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Xu, Jiahao, Weinan Sha, Chengjun Wang, Jiapeng You, Luyao Jiang, and Xinguo Ming. "Data Space-Driven Trusted Circulation and Synergistic Application Paradigm of Multi-Source Operational Data at Container Transshipment Ports." In 2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2025. https://doi.org/10.1109/cscwd64889.2025.11033599.

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Zhang, Xiaorui, Feng Xiao, Xu Cheng, and Jianhua Zhang. "Data-Driven Diffusion-Augmented Network for Imbalanced Sea State Estimation with Dynamic Prototypes." In 2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2025. https://doi.org/10.1109/cscwd64889.2025.11033443.

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Olayiwola, Teslim, Kyle Territo, and Jose Romagnoli. "Physics-informed Data-driven control of Electrochemical Separation Processes." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.163984.

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Optimizing the operational conditions of electrochemical separation systems to achieve higher separation efficiency remains a complex challenge due to their nonlinear and dynamic nature. In this work, we proposed a Reinforcement Learning (RL)-based control framework to address this challenge. By applying various RL algorithms, we trained an RL-based controller that adapts to different system configurations and conditions. Also, the trained model learns the optimality between the removal efficiency and energy consumption. Overall, this approach autonomously learns the optimal operational parame
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Zhao, Mingze, Bin Yuan, Wei Zhang, and Mingliang Han. "A Data-Driven Approach for Hydraulic Fracturing Simulation in Shale Based on Time-Series Images of Fracture Propagation." In GOTECH. SPE, 2024. http://dx.doi.org/10.2118/219321-ms.

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Summary Optimizing the hydraulic fracturing design requires efficient and accurate simulation of fracture propagation. However, traditional numerical methods are computationally expensive due to the solution of coupled differential equations, and the simulation accuracy may be reduced by the uncertainty of the input parameters (e.g., rock mechanical and fluid properties). To address these issues, this paper proposes a deep-learning-based approach to improve both the efficiency and accuracy of fracturing simulation in shale. This study develops a novel method integrating Feedforward neural netw
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Reports on the topic "Data driven frame work"

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Lim, Kenneth Yang Teck, and Longkai Wu. The development of a framework for the effective translation of educational research into sustained practice in Singapore. National Institute of Education, Nanyang Technological University, Singapore, 2024. https://doi.org/10.32658/10497/27412.

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This project arose from the need to engage in translation and scaling efforts from previous technologically mediated research projects; this is in line with the strategic direction set by the third tranche of research funding at the OER. The concepts of diffusion, scaling and translation are contested and are sometimes framed too narrowly from the paradigm of numbers progressing along a unilinear trajectory alone; to an extent, this paradigm arises from how translation has been understood from the bioscience and pharmacological industries. Transposing these understandings to the Social Science
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Gamkrelidze, Tamar, and Arto Väisänen. Securitisation of the Neighbourhood: EU-Driven Frame Alignment and Projection on Southern and Eastern Neighbourhood Partner Countries. EsadeGeo. Center for Global Economy and Geopolitics, 2022. https://doi.org/10.56269/202212tg.

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This paper is the first deliverable of ENGAGE Work Package 8, “Engaging with the EU’s Neighbourhoods”. It scrutinises the EU-driven strategic framings of “neighbours” and “neighbourhood” through a critical and thorough investigation of the European Neighbourhood Policy’s (ENP) documents and related official EU texts. The paper enquires into how the EU has discursively framed the ENP since 2003. Based on a discursive and empirical analysis of key ENP documents and the ENP itself, this paper argues that the EU’s internal understanding of the ENP has changed over time. The main change the paper i
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Lambon-Quayefio, Monica P. The Challenges of Child Labour Research: Data Challenges and Opportunities. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/acha.2021.006.

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his Rapid Review is an attempt to instigate a broader discussion on child labour by considering the various dimensions and angles associated with the phenomenon beyond the straitjacket definitions provided in most reports. Its objectives are threefold. First, it aims to determine whether re-analysis of existing data sets is likely to yield new insights into the forms, prevalence and drivers of children’s work in agriculture in Ghana. Second, it aims to provide specific guidance on how these re-analyses might be undertaken and framed. And third, it aims to determine whether any of the available
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Johra, Hicham, Anders Rhiger Hansen, and Lasse Rohde. Do International Building Researchers Mostly Work Right Before the Deadline? Yes, According to Empirical Data. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541562346.

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Academic work is characterised as increasingly time-pressured and deadline-driven. Moreover, increased use of online tools underpins flexible working hours. Does this make researchers work just before a deadline or a meeting (perceived as an intermediate deadline)? The "imminent deadline-driven work habit" hypothesis seems intuitively plausible since the research and academic world is notorious for heavy workloads and multiple parallel tasks and projects. The current article investigates the activity of several collaborative online documents from international building research projects as a f
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Meidani, Hadi, and Amir Kazemi. Data-Driven Computational Fluid Dynamics Model for Predicting Drag Forces on Truck Platoons. Illinois Center for Transportation, 2021. http://dx.doi.org/10.36501/0197-9191/21-036.

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Fuel-consumption reduction in the truck industry is significantly beneficial to both energy economy and the environment. Although estimation of drag forces is required to quantify fuel consumption of trucks, computational fluid dynamics (CFD) to meet this need is expensive. Data-driven surrogate models are developed to mitigate this concern and are promising for capturing the dynamics of large systems such as truck platoons. In this work, we aim to develop a surrogate-based fluid dynamics model that can be used to optimize the configuration of trucks in a robust way, considering various uncert
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Pandya, Phorum. Data In Deed. Edited by Sowmya Rajaram and Swetha Prakash. Indian School of Development Management, 2024. http://dx.doi.org/10.58178/2411.1050.

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"Data Stories is a project that captures inspirational stories of how Social Purpose Organisations (SPOs) are using data to maximise their impact. These stories will be told in a unique format – a graphic novel – and emphasise how data-driven decision-making has helped Social Purpose Organisations (SPOs) create real, measurable change on the ground. This edition of the novel features the stories of 3 SPOs across the country – Udayan Care, Saturday Art Class, and Nourishing Schools Foundation. Told in a narrative, storytelling style, each story shows how the use of data has helped the SPO becom
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Soar, Philip, Colin Thorne, David Biedenharn, et al. Development and testing of the FRAME tool on a 200-mile reach of the Lower Mississippi River. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49744.

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Understanding the likely long-term evolution of the Lower Mississippi River (LMR) is a challenging mission for the US Army Corps of Engineers (USACE) that remains difficult for conventional river engineering models. A new type of model is currently in development, tasked with revealing uncertainty-bounded trends in sediment transport and channel morphology over annual, decadal, and centennial timescales. The Future River Analysis and Management Evaluation (FRAME) tool is being designed with river managers and planners in mind to provide exploratory insights into plausible river futures and the
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Ali, Ibraheem, Thea Atwood, Renata Curty, et al. Research Data Services: Partnerships. Association of Research Libraries and Canadian Association of Research Libraries, 2022. http://dx.doi.org/10.29242/report.rdspartnerships2022.

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The Association of Research Libraries (ARL)/Canadian Association of Research Libraries (CARL) Joint Task Force on Research Data Services (RDS) formed in 2020 with a two-fold purpose: (1) to demonstrate and commit to the roles research libraries have in stewarding research data and as part of institution-wide research support services and (2) to guide the development of resources for the ARL and CARL memberships in advancing their organizations as collaborative partners with respect to research data services in the context of FAIR (findable, accessible, interoperable, and reusable) data princip
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van den Boogaard,, Vanessa, and Fabrizio Santoro. Co-Financing Community-Driven Development Through Informal Taxation: Experimental Evidence from South-Central Somalia. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/ictd.2021.016.

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Community contributions are often required as part of community-driven development (CDD) programmes, with payment encouraged through matching grants. However, little remains known about the impact of matching grants, or the implications of requiring community contributions in order for communities to receive development funding. This paper describes research where we partner with two non-governmental organisations (NGOs) – one international and one Somali – and undertake a randomised control trial of a CDD matching grant programme designed to incentivise informal contributions for local public
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Hilgert, Marianne, and Miguel Székely. What's Behind the Inequality We Measure: An Investigation Using Latin American Data. Inter-American Development Bank, 1999. http://dx.doi.org/10.18235/0010769.

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The use of income distribution indicators in the economics literature has increased considerably in recent years. This work relies on household surveys from 18 LAC countries to take a step back from the use of these indicators, and explore what's behind the numbers, and what information they convey. We find: a) that the way countries rank according to inequality measured in a conventional way is to a large extent an illusion created by differences in characteristics of the data and on the particular ways in which the data is treated; b) Our ideas about the effect of inequality on economic grow
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