The Interpretive Turn: History, Memory, and Storage in Qualitative Research by Véronique Mottier

“…This article reviews the field of qualitative inquiry, identifying three conceptual breaks: the "orthodox consensus" of positivism which conceives the social world as a collection of external facts and attempts to eliminate bias and subjectivity; post-positivist philosophy of science, which concedes that objective observation of pure data is impossible but nevertheless tries to establish criteria of "good" research practice; and the interpretive turn, which rehabilitates subjectivity and views data collection as a mutual construction of meaning where the researcher is engaged in "double hermeneutics" (GIDDENS). …”
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Rough North Correction Estimation Algorithm Based on Terrain Visibility by Ondrej Nemec, Jan Pidanic, Pavel Sedivy

“…The uniqueness of the algorithm is the pure data/software nature without need for any additional north-seeking equipment. …”
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Physics-informed Neural Networks:Recent Advances and Prospects by LI Ye, CHEN Song-can

“…Physical-informed neural networks (PINN) are a class of neural networks used to solve supervised learning tasks.They not only try to follow the distribution law of the training data, but also follow the physical laws described by partial diffe-rential equations.Compared with pure data-driven neural networks, PINN imposes physical information constraints during the training process, so that more generalized models can be acquired with fewer training data.In recent years, PINN has gradually become a research hotspot in the interdisciplinary field of machine learning and computational mathematics, and has obtained relatively in-depth research in both theory and application, and has made considerable progress.However, due to the unique network structure of PINN, there are some problems such as slow training or even non-convergence and low precision in practical application.On the basis of summarizing the current research of PINN, this paper explores the network/system design and its application in many fields such as fluid mechanics, and looks forward to the further research directions.…”
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Feature-Driven 3D Building Modeling using Planar Halfspaces by M. Kada, A. Wichmann

“…With the exception of pure data-driven methods, reconstruction approaches for 3D building models from aerial point clouds often incorporate some level of model information to construct regularized and well-formed roof structures. …”
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Integration of an Active Research Data System with a Data Repository to Streamline the Research Data Lifecyle: Pure-NOMAD Case Study by Simone Ivan Conte, Federica Fina, Michalis Psalios, Shyam Ryal, Tomas Lebl, Anna Clements

“…In this paper we present the integration between an active data management system developed in-house (NOMAD) and Elsevier’s Pure data repository used at our institution, with the aim of offering a simple workflow to facilitate and promote the data deposit process. …”
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Predicting Rogue Content and Arabic Spammers on Twitter by Adel R. Alharbi, Amer Aljaedi

“…In this work, we collected a pure data set from spam accounts producing Arabic tweets. …”
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A Pore Classification System for the Detection of Additive Manufacturing Defects Combining Machine Learning and Numerical Image Analysis by Sahar Mahdie Klim Al-Zaidawi, Stefan Bosse

“…This approach achieves sufficient accuracy by training a Random Forest as a hybrid-model data-driven classifier, compared with a pure data-driven model such as a CNN.…”
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Learning battery model parameter dynamics from data with recursive Gaussian process regression by Aitio, A, Joest, D, Sauer, DU, Howey, DA

“…As a result, existing techniques based on fitting equivalent circuit models may exhibit inaccuracy at extremes of performance and over long-term ageing, or instability of parameter estimates. Pure data-driven techniques, on the other hand, suffer from a lack of generality beyond their training dataset. …”

Design and Aural Analysis of Signal Processing Using Time Delay by Mauricio Perez, Regis Alves Rossi Faria, Rodolfo Coelho de Souza

“…This paper presents the design in PureData of some audio signals processes in real time like delay, echo, reverb, chorus, flanger e phaser. …”
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A vision sensing-enhanced knowledge graph inference method for a healthy operation index in higher education by Yu Nie, Xingpeng Luo, Yanghang Yu

“…The vision sensing-enhanced knowledge inference method for the HOI-HE is able to exceed the benefit of pure data-driven methods. The experimental results in some simulated scenes show that the proposed knowledge inference method can work well in the evaluation of a HOI-HE, as well as to discover some latent risk.…”
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A Physics-Guided Neural Network for Predicting Protein–Ligand Binding Free Energy: From Host–Guest Systems to the PDBbind Database by Sahar Cain, Ali Risheh, Negin Forouzesh

“…Results demonstrate that the proposed Physics-Guided Neural Network can successfully improve the “accuracy” of the pure data-driven model. In addition, the “interpretability” and “transferability” of our model have boosted compared to the purely data-driven model. …”
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An Approach for the Relationship Analysis between Social Events and the Stock Market during the Pandemic by Ruogu Zhou, Jie Hua, Xin Chi, Xiao Ren, Shuyang Hua

“…Here, we proposed a methodology based on pure data analytics, which gathers two types of data, event and stock index in China, to explore their relationship through analysing the stock index’s shift in reacting to pertinent social events, hence revealing insights into how events affect fluctuations in stock indices. …”
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Research on temperature prediction model of molten steel of tundish in continuous casting by Bowen Dong, Wu Lv, Zhi Xie

“…The results show that the error of the model is about 2.1k which has better accuracy compared to pure mechanistic model and pure data model. Additionally, it can capture the variation patterns of tundish lining thermal parameters under different operating conditions. …”
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A wireless sensor-based mobile music environment complied from a graphical language by Jacobs, Robert N. (Robert Nathan)

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Indeterminacy of reverse engineering of Gene Regulatory Networks: the curse of gene elasticity. by Arun Krishnan, Alessandro Giuliani, Masaru Tomita

“…In this work, we study the effect of this particular problem on the pure, data-driven inference of gene regulatory networks.We simulated a four-gene network in order to produce "data" (protein levels) that we use in lieu of real experimental data. …”
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Machine Learning in Tropical Cyclone Forecast Modeling: A Review by Rui Chen, Weimin Zhang, Xiang Wang

“…Machine learning, as a means of artificial intelligence, has been certified by many researchers as being able to provide a new way to solve the bottlenecks of tropical cyclone forecasts, whether using a pure data-driven model or improving numerical models by incorporating machine learning. …”
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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

“…The planned model is improved through conducting deep learning methods incorporated to the existing practice for different crop condition. Pure data and related evidence are attained concerning the quantities of soil constituents desired through their expenditures distinctly. …”
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Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz by Mohammud Z. Bocus, Afzal Lodhi

“…The performance comparison between varying number of input features highlights that whilst an excellent prediction accuracy can be achieved when the training data include all test scenarios, it also reveals the limitations of pure data driven prediction methods and their inability to generalise. …”
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Phenobot - Intelligent photonics for molecular phenotyping in Precision Viticulture by Martins R.C., Cunha M., Santos F., Tosin R., Barroso T.G., Silva F., Queirós C., Pereira M.R., Moura P., Pinho T., Boaventura J., Magalhães S., Aguiar A.S., Silvestre J., Damásio M., Amador R., Barbosa C., Martins C., Araújo J., Vidal J.P., Rodrigues F., Maia M., Rodrigues V., Garcia A., Raimundo D., Trindade M., Pestana C., Maia P.

“…The Phenobot platform is comprised by an autonomous robot, instrumentation, artificial intelligence, and digital twin diagnosis at the molecular level, marking the transition from pure data-driven to knowledge-driven agriculture 4.0, towards a physiology-based approach to precision viticulture. …”
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Assessing the Impacts of Human Activities on Air Quality during the COVID-19 Pandemic through Case Analysis by Xin Chi, Jie Hua, Shuyang Hua, Xiao Ren, Shuanghe Yang

“…In order to analyse the potential relationship between pandemic-related information and air quality data from a more holistic and detailed point of view, we propose a methodology based on pure data analysis. Three types of data were collected, namely air quality index, pandemic-related events, and number of COVID cases. …”
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