Making it ‘Local’: Community data journalism for health justice by Shirley Roburn

“…The Local’s Code of Ethics and its Race, Representation and Equity Commitment shaped the magazine’s structure, which in turn influenced reporting. The Local applied a health-equity lens to its pandemic data journalism. …”
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Outcomes of West syndrome: literature review and own data by T. M. Prygunova

“…These criteria are based on literature and our own data. Predictors of an adverse outcome of West syndrome include: symptomatic forms of disease (structural, genetic, infectious), impaired neuropsychological development before onset of epileptic spasms, age of spasms onset more than 8 months, the presence of other seizures types in addition to epileptic spasms, the need for polytherapy of antiepileptic drugs. …”
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Parenclitic Network Analysis of Methylation Data for Cancer Identification. by Alexander Karsakov, Thomas Bartlett, Artem Ryblov, Iosif Meyerov, Mikhail Ivanchenko, Alexey Zaikin

“…We make use of ideas from the theory of complex networks to implement a machine learning classification of human DNA methylation data, that carry signatures of cancer development. …”
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From data to medical context: the power of categorization in healthcare by Batoul Msheik, Hamid Mcheick, Sara Hariri, Mehdi Adda, Mohamed Dbouk

“…In the rapidly evolving healthcare domain, the ability to structure and interpret contextual medical data is crucial for delivering personalized and efficient patient care. …”
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Big Data in marketing analytics: opportunities and problems of use by S.F., T.O.

“…The main problems of using Big Data for the development of marketing analytics have been described (objective limitation of the use of Big Data; the time gap between the occurrence and receipt of processed data for decision-making; storage and processing of streaming data; the need to acquire new competencies by employees of the marketing department; the need to improve the structure of the marketing department).…”
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Efficient Reasoning upon Fusion of Many Data Sources by Chase Alexander Yakaboski, Eugene Santos

“…Bayesian Knowledge Bases (BKB), a graphical model for representing structured probabilistic information, allow for efficient fusion of knowledge from multiple sources. …”
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Survey of artificial intelligence data security and privacy protection by Kui REN, Quanrun MENG, Shoukun YAN, Zhan QIN

“…Artificial intelligence and deep learning algorithms are developing rapidly.These emerging techniques have been widely used in audio and video recognition, natural language processing and other fields.However, in recent years, researchers have found that there are many security risks in the current mainstream artificial intelligence model, and these problems will limit the development of AI.Therefore, the data security and privacy protection was studied in AI.For data and privacy leakage, the model output based and model update based problem of data leakage were studied.In the model output based problem of data leakage, the principles and research status of model extraction attack, model inversion attack and membership inference attack were discussed.In the model update based problem of data leakage, how attackers steal private data in the process of distributed training was discussed.For data and privacy protection, three kinds of defense methods, namely model structure defense, information confusion defense and query control defense were studied.In summarize, the theoretical foundations, classic algorithms of data inference attack techniques were introduced.A few research efforts on the defense techniques were described in order to provoke further research efforts in this critical area.…”
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Construction and Application of Media Corpus Based on Big Data by Bochun Yin, Lei Fu

“…Then, the state characteristics and probability distribution of feature data are determined by dynamic Bayesian network, the relationship between the state variables and dimensions of media corpus data is determined, and the media corpus data state is processed by component to complete the preprocessing of media corpus data; finally, through the application research of storage and encryption of the designed database through big data technology, the storage structure data and encryption secret key are designed to realize the construction and application of media corpus. …”
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Methods for Constructing Artificial Neural Networks for Data Classification by L. V. Serebryanaya

“…Trained networks are used to classify data. Both networks showed acceptable classification accuracy of the results obtained in the course of the students’ knowledge testing.…”
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An autoencoder for compressing angle-resolved photoemission spectroscopy data by Steinn Ýmir Ágústsson, Mohammad Ahsanul Haque, Thi Tam Truong, Marco Bianchi, Nikita Klyuchnikov, Davide Mottin, Panagiotis Karras, Philip Hofmann

“…Angle-resolved photoemission spectroscopy (ARPES) is a powerful experimental technique to determine the electronic structure of solids. Advances in light sources for ARPES experiments are currently leading to a vast increase of data acquisition rates and data quantity. …”
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Reading fluency: normative data for Romanian speaking population by Carolina Bodea Hategan, Dorina Talas, Carmen Costea-Bărluțiu, Raluca Trifu

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Providing Web Archive News Articles as Corpus Data by Jon Carlstedt Tønnessen, Magnus Breder Birkenes

“…While the huge data repositories of web archives carry big potential for knowledge production in academia, researchers have described significant challenges when trying to access and make use of web archives in research. …”
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Where and how to house big data on small fragments by Daniel A. Erlanson, Stephen K. Burley, Daren Fearon, James S. Fraser, Dale Kreitler, Maria Cristina Nonato, Naoki Sakai, Jan Wollenhaupt, Manfred S. Weiss

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THE SCOPE OF FARMS SUSTAINABILITY TOOLS BASED ON FADN DATA by Vida DABKIENĖ

“…This paper reviews recent reports on the farm sustainability assessment, in particular, the farm sustainability assessments based on EU Farm Accountancy Data Network (FADN). The most commonly-used data source for evaluation of farms economic, social and environment sustainability is farmers’ survey, employing structured questionnaire or/and in-depth interview. …”
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Stair Scheduling for Data Collection in Wireless Sensor Networks by Jinbiao Chen, Yongcai Wang, Yuexuan Wang, Changjian Hu

“…Spatially organized clusters are basic structure for large-scale wireless sensor networks. …”
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Data-driven model discovery with Kolmogorov-Arnold networks by Shirin Panahi, Mohammadamin Moradi, Erik M. Bollt, Ying-Cheng Lai

“…Data-driven model discovery of complex dynamical systems can be done using sparse optimization, but it has a fundamental limitation: sparsity in that the underlying governing equations of the system contain only a small number of elementary mathematical functions. …”
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Evaluation of Plaid Models in Biclustering of Gene Expression Data by Hamid Alavi Majd, Soodeh Shahsavari, Ahmad Reza Baghestani, Seyyed Mohammad Tabatabaei, Naghme Khadem Bashi, Mostafa Rezaei Tavirani, Mohsen Hamidpour

“…Two simulated matrices with different degrees of overlap and noise are generated and then the intrinsic structure of these data is compared with biclusters result. …”
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Emergent Technologies in Big Data Sensing: A Survey by Ting Zhu, Sheng Xiao, Qingquan Zhang, Yu Gu, Ping Yi, Yanhua Li

“…However, big data is a fuzzy data science concept and there is no existing research architecture for it nor a generic application structure in the field of sensing. …”
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Drones and Drawings - methods of data acquisition, management, and representation by Francesca Picchio, Sandro Parrinello, Salvatore Barba

“…The common objective of these researches is to arrive at an effective configuration of integrated, verified, and discretized data, from which to structure valid multiscale and multilevel representation systems. …”
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A Survey on Data Selection for Efficient Speech Processing by Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza

“…This survey provides a comprehensive overview and introduces a unifying taxonomy for data selection methods in speech processing, structured along three key dimensions: selection granularity (sample-level vs. segment-level), selection process (static, dynamic, or active learning), and selection criteria (uncertainty, diversity, or hybrid approaches). …”
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