Relevant bibliographies by topics / Data-driven techniques

Contents

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

Academic literature on the topic 'Data-driven techniques'

Author: Grafiati
Published: 30 November 2024
Last updated: 31 July 2025

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Journal articles on the topic "Data-driven techniques"

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Kumar, Sandeep. "Enhancing Data Privacy in SAP Finance with Artificial Intelligence Driven Masking Techniques." International Journal of Science and Research (IJSR) 13, no. 5 (2024): 1819–24. http://dx.doi.org/10.21275/sr24518072929.

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Bossé, Michael J. "Data-Driven Mathematics Investigations on Curved Data." Mathematics Teacher 99, no. 1 (2005): 46–54. http://dx.doi.org/10.5951/mt.99.1.0046.

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Investigations of real–world data begin in elementary school. Students often produce scatter plots, leading to trend lines. In the middle grades, lines of best fit are often investigated through median–median lines and double–centroid lines (Shawer et al. 2002). In the secondary grades, linear regression is produced by the least squares line. While these techniques are adequate for data that is more or less linear, teachers and students often encounter data that produce a “curved” scatter plot. In these cases additional techniques are required. This article demonstrates three techniques to det
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Azkune, Gorka, Aitor Almeida, Diego López-de-Ipiña, and Liming Chen. "Extending knowledge-driven activity models through data-driven learning techniques." Expert Systems with Applications 42, no. 6 (2015): 3115–28. http://dx.doi.org/10.1016/j.eswa.2014.11.063.

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Zhong, Jinghui, Dongrui Li, Zhixing Huang, Chengyu Lu, and Wentong Cai. "Data-driven Crowd Modeling Techniques: A Survey." ACM Transactions on Modeling and Computer Simulation 32, no. 1 (2022): 1–33. http://dx.doi.org/10.1145/3481299.

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Data-driven crowd modeling has now become a popular and effective approach for generating realistic crowd simulation and has been applied to a range of applications, such as anomaly detection and game design. In the past decades, a number of data-driven crowd modeling techniques have been proposed, providing many options for people to generate virtual crowd simulation. This article provides a comprehensive survey of these state-of-the-art data-driven modeling techniques. We first describe the commonly used datasets for crowd modeling. Then, we categorize and discuss the state-of-the-art data-d
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Li, Tao, Ning Xie, Chunqiu Zeng, et al. "Data-Driven Techniques in Disaster Information Management." ACM Computing Surveys 50, no. 1 (2017): 1–45. http://dx.doi.org/10.1145/3017678.

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Arunkumar, R., and V. Jothiprakash. "Reservoir Evaporation Prediction Using Data-Driven Techniques." Journal of Hydrologic Engineering 18, no. 1 (2013): 40–49. http://dx.doi.org/10.1061/(asce)he.1943-5584.0000597.

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Li, Tao, Chunqiu Zeng, Yexi Jiang, et al. "Data-Driven Techniques in Computing System Management." ACM Computing Surveys 50, no. 3 (2017): 1–43. http://dx.doi.org/10.1145/3092697.

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I., V. "Data Engineering: using Data Analysis Techniques in Producing Data Driven Products." International Journal of Computer Applications 161, no. 1 (2017): 13–16. http://dx.doi.org/10.5120/ijca2017912712.

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Meliboev, Azizjon. "ANALYZING HOTEL DATA-DRIVEN SYSTEM BY USING DATA SCIENCE TECHNIQUES." QO‘QON UNIVERSITETI XABARNOMASI 11 (June 30, 2024): 108–11. http://dx.doi.org/10.54613/ku.v11i11.971.

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In the past few years, both the City Hotel and Resort Hotel have experienced significant increases in their cancellation rates. As a result, both hotels are currently facing a range of challenges, such as reduced revenue and underutilized hotel rooms. Therefore, the top priority for both hotels is to reduce their cancellation rates, which will enhance their efficiency in generating revenue. This report focuses on the analysis of hotel booking cancellations and other factors that do not directly impact their business and annual revenue generation.
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Poonia, Ramesh Chandra, and Santosh R. Durugkar. "Sampling Techniques Used in Big-Data Driven Applications." Journal of Intelligent Systems and Computing 2, no. 1 (2021): 17–20. http://dx.doi.org/10.51682/jiscom.00201004.2021.

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Data-driven systems process the data from various sources in multiple applications. Data retrieved from heterogeneous sources need to be available in an aggregate and unique format. This requirement gives rise to the process of the Big-data and proposed next-generation big-data processing systems. There are many applications based on contextual data useful for identifying the traffic intensity, changing users per application, weather conditions etc., and serve as next- generation business-specific systems. In such systems data abstraction and representation are the important tasks & granul
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Dissertations / Theses on the topic "Data-driven techniques"

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Mousas, Christos. "Data-driven techniques for animating virtual characters." Thesis, University of Sussex, 2015. http://sro.sussex.ac.uk/id/eprint/52967/.

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One of the key goals of current research in data-driven computer animation is the synthesis of new motion sequences from existing motion data. This thesis presents three novel techniques for synthesising the motion of a virtual character from existing motion data and develops a framework of solutions to key character animation problems. The first motion synthesis technique presented is based on the character's locomotion composition process. This technique examines the ability of synthesising a variety of character's locomotion behaviours while easily specified constraints (footprints) are pla
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Battle, Leilani Marie. "Behavior-driven optimization techniques for scalable data exploration." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111853.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 153-162).<br>Interactive visualizations are a popular medium used by scientists to explore, analyze and generally make sense of their data. However, with the overwhelming amounts of data that scientists collect from various i
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Massey, Tammara. "Data driven and optimization techniques for mobile health systems." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1930907801&sid=4&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Nordahl, Christian. "Data-Driven Techniques for Modeling and Analysis of User Behavior." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18667.

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Our society is becoming more digitalized for each day. Now, we are able to gather data from individual users with higher resolution than ever. With the increased amount of data on an individual user level, we can analyze their behavior. This is of interest in many different domains, for example service providers wanting to improve their service for their customers. If they know how their service is used, they have more insight in how they can improve. But, it also imposes additional difficulties. When we reach the individual user, the irregularities in the regular behavior makes it harder to m
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Ogweno, Austin Juma. "Power efficient, event driven data acquisition and processing using asynchronous techniques." Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/4121.

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Data acquisition systems used in remote environmental monitoring equipment and biological sensor nodes rely on limited energy supply soured from either energy harvesters or battery to perform their functions. Among the building blocks of these systems are power hungry Analogue to Digital Converters and Digital Signal Processors which acquire and process samples at predetermined rates regardless of the monitored signal's behavior. In this work we investigate power efficient event driven data acquisition and processing techniques by implementing an asynchronous ADC and an event driven power gate
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Essaidi, Moez. "Model-Driven Data Warehouse and its Automation Using Machine Learning Techniques." Paris 13, 2013. http://scbd-sto.univ-paris13.fr/secure/edgalilee_th_2013_essaidi.pdf.

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L'objectif de ce travail de thèse est de proposer une approche permettant l'automatisation complète du processus de transformation de modèles pour le développement d'entrepôts de données. L'idée principale est de réduire au mieux l'intervention des experts humains en utilisant les traces de transformations réalisées sur des projets similaires. L'objectif est d'utiliser des techniques d'apprentissage supervisées pour traiter les définitions de concepts avec le même niveau d'expression que les données manipulées. La nature des données manipulées nous a conduits à choisir les langages relationnel
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Stender, Merten [Verfasser]. "Data-driven techniques for the nonlinear dynamics of mechanical structures / Merten Stender." Hamburg : Universitätsbibliothek der Technischen Universität Hamburg-Harburg, 2020. http://d-nb.info/1221669583/34.

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Godwin, Jamie Leigh. "Exploiting robust multivariate statistics and data driven techniques for prognosis and health management." Thesis, Durham University, 2015. http://etheses.dur.ac.uk/11157/.

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This thesis explores state of the art robust multivariate statistical methods and data driven techniques to holistically perform prognostics and health management (PHM). This provides a means to enable the early detection, diagnosis and prognosis of future asset failures. In this thesis, the developed PHM methodology is applied to wind turbine drive train components, specifically focussed on planetary gearbox bearings and gears. A novel methodology for the identification of relevant time-domain statistical features based upon robust statistical process control charts is presented for high freq
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Fields, Evan(Evan Jerome). "Demand uncensored : car-sharing mobility services using data-driven and simulation-based techniques." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121825.

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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 141-145).<br>In the design and operation of urban mobility systems, it is often desirable to understand patterns in traveler demand. However, demand is typically unobserved and must be estimated from available data. To address this disconnect, we begin by proposing a method for recovering an unknown probability distribution given a censored or truncated sample from that distribution. The propos
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Reinoso, Nicholas L. "Forecasting Harmful Algal Blooms for Western Lake Erie using Data Driven Machine Learning Techniques." Cleveland State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=csu1494343783463819.

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Books on the topic "Data-driven techniques"

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Damper, Robert I., ed. Data-Driven Techniques in Speech Synthesis. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3413-3.

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Damper, R. I. Data-Driven Techniques in Speech Synthesis. Springer US, 2001.

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I, Damper R., ed. Data-driven techniques in speech synthesis. Kluwer Academic Publishers, 2001.

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Si, Xiao-Sheng, Zheng-Xin Zhang, and Chang-Hua Hu. Data-Driven Remaining Useful Life Prognosis Techniques. Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54030-5.

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Kumar Rana, Arun, Sumit Kumar Rana, Vishnu Sharma, and Ritu Dewan. Intelligent Data-Driven Techniques for Security of Digital Assets. CRC Press, 2025. https://doi.org/10.1201/9781003590439.

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P, Ford Michael, and Erekson James A, eds. Accessible assessment: How 9 sensible techniques can power data-driven reading instruction. Heinemann, 2011.

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W, Stoughton John, Mielke Roland R, and Langley Research Center, eds. Strategies for concurrent processing of complex algorithms in data driven architectures. National Aeronautics and Space Administration, Langley Research Center, 1990.

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Data-Driven Techniques in Speech Synthesis. Island Press, 2001.

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Winston, Wayne L. Marketing Analytics: Data-Driven Techniques with Microsoft Excel. Wiley & Sons, Incorporated, John, 2014.

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Winston, Wayne L. Marketing Analytics: Data-Driven Techniques with Microsoft Excel. Wiley & Sons, Incorporated, John, 2014.

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Book chapters on the topic "Data-driven techniques"

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Stolper, Charles D., Bongshin Lee, Nathalie Henry Riche, and John Stasko. "Data-Driven Storytelling Techniques." In Data-Driven Storytelling. A K Peters/CRC Press, 2018. http://dx.doi.org/10.1201/9781315281575-4.

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Hasan Hussain, S., T. B. Sivakumar, and Alex Khang. "Cryptocurrency Methodologies and Techniques." In The Data-Driven Blockchain Ecosystem. CRC Press, 2022. http://dx.doi.org/10.1201/9781003269281-2.

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Jansen, Bernard J., Joni Salminen, Soon-gyo Jung, and Kathleen Guan. "Using Data-Driven Personas Alongside Other Human-Computer Interaction (HCI) Techniques." In Data-Driven Personas. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-02231-9_8.

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Courty, Nicolas, and Thomas Corpetti. "Data-Driven Animation of Crowds." In Computer Vision/Computer Graphics Collaboration Techniques. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71457-6_34.

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Ateeq, Muhammad, and Muhammad Khalil Afzal. "Programming Languages, Tools, and Techniques." In Data-Driven Intelligence in Wireless Networks. CRC Press, 2023. http://dx.doi.org/10.1201/9781003216971-13.

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Liang, Yuan, Song-Hai Zhang, and Ralph Robert Martin. "Automatic Data-Driven Room Design Generation." In Next Generation Computer Animation Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69487-0_10.

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Livraga, Giovanni. "Privacy in Microdata Release: Challenges, Techniques, and Approaches." In Data-Driven Policy Impact Evaluation. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78461-8_5.

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Singh, Sanika, Aman Anand, Tanupriya Choudhury, Pankaj Sharma, and Ved P. Mishra. "Extensive Review on Product Recommendation Techniques." In Data Driven Approach Towards Disruptive Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9873-9_43.

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Guru, Sudhanshu Kumar, and Lov Kumar. "Investigation of Predictive Power of Sentiment Analysis Model Developed Using Different Word Embedding Techniques." In Data-Driven Decision Making. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2902-9_2.

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Rani, Komal, Naveen Kumar, Manju Rani, and Kamal. "Intelligent data mining techniques." In Intelligent Data-Driven Techniques for Security of Digital Assets. CRC Press, 2025. https://doi.org/10.1201/9781003590439-8.

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Conference papers on the topic "Data-driven techniques"

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Hsieh, Wen-Chun, Yu-Ting Sheng, and Shih-Yuan Wang. "Exploration of Incremental Sheet Forming for Application in Formwork Techniques." In eCAADe 2024: Data-Driven Intelligence. eCAADe, 2024. http://dx.doi.org/10.52842/conf.ecaade.2024.1.085.

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Dangwal, Kartikeye, Iman Ardekani, Soheil Varastehpour, and Abdolhossein Sarrafzadeh. "Bioacoustic Data Augmentation Techniques for Data-Driven Apiculture." In 2024 IEEE International Conference on Future Machine Learning and Data Science (FMLDS). IEEE, 2024. https://doi.org/10.1109/fmlds63805.2024.00031.

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Mansuri, Ahmad, Asterios Agkathidis, Davide Lombardi, and Hanmei Chen. "Rethinking Bamboo Roof-Based Architecture of Indonesian Traditional House Using Parametric Design and Automated Fabrication Techniques." In eCAADe 2024: Data-Driven Intelligence. eCAADe, 2024. http://dx.doi.org/10.52842/conf.ecaade.2024.1.203.

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Tsurunaga, Shinya, Tomohiro Fukuda, and Nobuyoshi Yabuki. "Enhanced Landscape Visualization of Post-Structure Removal: Integrating 3D reconstruction techniques and diffusion models through machine learning." In eCAADe 2024: Data-Driven Intelligence. eCAADe, 2024. http://dx.doi.org/10.52842/conf.ecaade.2024.1.549.

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Zhang, Guodong, Zhuo Jin, Tianyu Yao, and Jiawei Qin. "ECET: Enhanced Vulnerability Detection through Code Embedding Techniques." In 2024 Sixth International Conference on Next Generation Data-driven Networks (NGDN). IEEE, 2024. http://dx.doi.org/10.1109/ngdn61651.2024.10744066.

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Shinde, Priyanka P., V. P. Desai, and Kavita S. Oza. "A Data Driven Mental Health Analysis Using Machine Learning Techniques." In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). IEEE, 2024. http://dx.doi.org/10.1109/icoici62503.2024.10696584.

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Rao, K. Dhananjay, CH Sunil, N. Bala Adithya, Naga Lakshmi Pujitha Nagasarapu, Ch Manaswi, and Prakash. "Data Driven Techniques for Fault Detection in Lithium Ion Battery." In 2024 International Conference on Sustainable Power & Energy (ICSPE). IEEE, 2024. https://doi.org/10.1109/icspe62629.2024.10924393.

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Fan, Zhiwei, Chao Xu, Yuling Huang, et al. "MonoDDT: Monocular 3D Object Detection Enhanced by Data-Driven Techniques." In 2025 7th International Conference on Software Engineering and Computer Science (CSECS). IEEE, 2025. https://doi.org/10.1109/csecs64665.2025.11009909.

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Gabrielski, Jawana, and Ulf Häger. "Advancing Standard Load Profiles with Data-Driven Techniques and Recent Datasets." In 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, 2024. http://dx.doi.org/10.1109/smartgridcomm60555.2024.10738046.

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Meng, Yiming, Hangyu Li, Melkior Ornik, and Xiaopeng Li. "Koopman-Based Data-Driven Techniques for Adaptive Cruise Control System Identification." In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2024. https://doi.org/10.1109/itsc58415.2024.10920220.

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Reports on the topic "Data-driven techniques"

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Gravina, Antonio Francesco, and Matteo Lanzafame. “What’s Your Shape?”: A Data-Driven Approach to Estimating the Environmental Kuznets Curve. Asian Development Bank, 2024. http://dx.doi.org/10.22617/wps240334-2.

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This paper uses Bayesian Model Averaging techniques to explore the relationship between environmental degradation and economic growth and finds that per capita gross domestic product (GDP) and carbon dioxide emissions are positively associated in emerging economies. Due to model and variable selection uncertainty, studies on the inverted U-shaped relationship between environmental degradation and economic growth—known as the Environmental Kuznets Curve—have produced very mixed evidence. This paper addresses these issues by using Bayesian Model Averaging techniques. The results indicate that th
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Crews, John H., Ralph C. Smith, Kyle M. Pender, Jennifer C. Hannen, and Gregory D. Buckner. Data-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory Alloys. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada556936.

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Zanoni, Wladimir, Jimena Romero, Nicolás Chuquimarca, and Emmanuel Abuelafia. Dealing with Hard-to-Reach Populations in Panel Data: Respondent-Driven Survey (RDS) and Attrition. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005194.

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Hidden populations, such as irregular migrants, often elude traditional probabilistic sampling methods. In situations like these, chain-referral sampling techniques like Respondent-Driven Surveys (RDS) offer an effective solution. RDS, a variant of network sampling sometimes referred to as “snowball” sampling, estimates weights based on the network structures of friends and acquaintances formed during the sampling process. This ensures the samples are representative of the larger population. However, one significant limitation of these methods is the rigidity of the weights. When faced with pa
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Hu, Zhengzheng, Ralph C. Smith, and Jon Ernstberger. The Homogenized Energy Model (HEM) for Characterizing Polarization and Strains in Hysteretic Ferroelectric Materials: Implementation Algorithms and Data-Driven Parameter Estimation Techniques. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada556961.

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Chhipi-Shrestha, Gyan, Vipul Moudgil, Rachid Ouche, et al. Enhancing Resilience of Urban Systems Against Climate-Induced Floods Using Advanced Data-Driven and Computing Techniques: A Driver-Pressure-State-Impact-Response (DPSIR) Framework. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769705.

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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats,
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Mohammadian, Abolfazl, Amir Bahador Parsa, Homa Taghipour, Amir Davatgari, and Motahare Mohammadi. Best Practice Operation of Reversible Express Lanes for the Kennedy Expressway. Illinois Center for Transportation, 2021. http://dx.doi.org/10.36501/0197-9191/21-033.

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Reversible lanes in Chicago’s Kennedy Expressway are an available infrastructure that can significantly improve traffic performance; however, a special focus on congestion management is required to improve their operation. This research project aims to evaluate and improve the operation of reversible lanes in the Kennedy Expressway. The Kennedy Expressway is a nearly 18-mile-long freeway in Chicago, Illinois, that connects in the southeast to northwest direction between the West Loop and O’Hare International Airport. There are two approximately 8-mile reversible lanes in the Kennedy Expressway
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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add
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Rose and Luo. L52069 Guided Wave Sizing and Discrimination for SCC Magnetostriction ILI Inspection. Pipeline Research Council International, Inc. (PRCI), 2003. http://dx.doi.org/10.55274/r0011179.

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With the goal to be able to inspect a large area of the pipe from a single sensor position, hence the development of what we call guided wave inspection. From one point on the circumference of the pipe, it is therefore proposed to inspect the entire circumferential area of the pipe. This approach leads to inspection efficiency.� Experimental techniques cannot be developed on a trial and error basis. The purpose of this work is therefore to develop a guided wave propagation model and subsequent numerical solutions to assist in the �theoretically driven� sensor design and data acquisition system
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Lindig, Sascha, Julien Deckx, Magnus Herz, et al. Technical Key Performance Indicators for Photovoltaic Systems: Challenges and Best Practices. International Energy Agency Photovoltaic Power Systems Programme, 2024. https://doi.org/10.69766/luzi3108.

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Key Performance Indicators (KPIs) are an important set of metrics used to assess various aspects of photovoltaic (PV) systems, including their long-term performance, economic viability and carbon footprint. Technical KPIs support data-driven and informed decision-making when optimizing PV systems and provide a comprehensive overview of how PV systems operate across different conditions and climates. Different KPIs are commonly employed throughout the entire value chain of PV projects and can be categorized into technical, economic and sustainability aspects. In this work, a set of best practic
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