Admissions for orthostatic hypotension: an analysis of NHS England Hospital Episode Statistics data by Rose Anne Kenny, Eoin Duggan, Roman Romero-Ortuno

“…Objectives To determine whether admissions for orthostatic hypotension (OH) and its consequences, such as falls, have changed over the past 10 years in the National Health Service (NHS) England.Setting Data from NHS England Hospital Episode Statistics, a database containing details of all admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England, were obtained and analysed.Participants Data on hospital admissions in NHS England, as defined by finished consultant episodes (FCEs), were examined between 2008 and 2017.Main outcome measures FCEs for the following International Classification of Disease codes were examined: OH (I95.1), tendency to fall (R29.6), epilepsy (G40) and chronic obstructive pulmonary disease (COPD) (J44). …”
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Effective deep learning aided vehicle classification approach using Seismic Data by Sherief Hashima, Mohamed H. Saad, Ahmad B. Ahmad, Takeshi Tsuji, Hamada Rizk

“…Experimental results validate the efficacy of our approach, achieving state-of-the-art performance using seismic signal classification tasks with limited training data. Our approach achieves an impressive accuracy of 99.8%, underscoring its potential for robust and precise VC in ITSs using seismic data, particularly in data-scarce scenarios. …”
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PERFORMANCE REFINEMENT OF CONVOLUTIONAL NEURAL NETWORK ARCHITECTURES FOR SOLVING BIG DATA PROBLEMS by Saud Aljaloud

“…However, in order to be trained and deliver accurate results, neural networks need a sizeable amount of sample data, as will be covered in more detail later. Because of this, big data experts frequently encounter problems of this nature. …”
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An air target intention data extension and recognition model based on deep learning by Bo Cao, Qinghua Xing, Longyue Li, Weijie Lin

“…The model mainly consists of two parts: intention data generation and intention recognition. First, the air target intention recognition problem is analyzed in detail, and the air target intention space and feature set are constructed and coded uniformly. …”
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Multi channel fusion diffusion models for brain tumor MRI data augmentation by Cuihua Zuo, Junhao Xue, Cao Yuan

“…In our experiments, we used a publicly available brain tumor dataset and compared the performance of image classification and segmentation tasks between the original data and the data enhanced by our method. The results show that the enhanced data improved the classification accuracy by approximately 3% and the Dice coefficient for segmentation tasks by 1.5%–2.5%. …”
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Overview of Finnish national patient data repository for research on medical risk assessment by Viljami Männikkö, Klaus Förger, Henna Kujanen, Jani Tikkanen, Simo Antikainen, Joona Munukka

“…Main challenges in the use of data in the Kanta PDR are multiple code systems for laboratory results, short durations of recorded data for specific data types, and missing or very rarely used structured format e.g., in cases of tobacco and alcohol use. …”
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A momentary view of engagement in collaborative learning: Triangulation through multimodal data by Eetu Haataja, Tiina Törmänen, Matthew P. Somerville, Jonna Malmberg, Hanna Järvenoja, Sanna Järvelä

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A benchmark study of compression software for human short-read sequence data by Raphael O. Betschart, Felix Thalén, Stefan Blankenberg, Martin Zoche, Tanja Zeller, Andreas Ziegler

“…Abstract Efficient data compression technologies are crucial to reduce the cost of long-term storage and file transfer in whole genome sequencing studies. …”
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Investigation of a Novel Approach to Securing Data Exchanges Within Industrial Environments by Marko Slunjski

“…As a result, vulnerabilities in data exchange protocols can expose unencrypted process data to malicious cyber activities. …”
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rEHR: An R package for manipulating and analysing Electronic Health Record data. by David A Springate, Rosa Parisi, Ivan Olier, David Reeves, Evangelos Kontopantelis

“…The package also contains functions for cutting data by time-varying covariates, matching controls to cases, unit conversion and construction of clinical code lists. …”
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Evaluating habitat use and relative abundance of Iowa's river otter with harvest data by Bridget A. Nixon, Vince Evelsizer, Robert W. Klaver

“…Our objective was to relate land cover characteristics and otter abundance using harvest data. We used data collected by agency staff to map the locations of otter harvest in Iowa from 2006 to 2016. …”
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Multimodal Learning for Traffic Risk Prediction: Combining Aerial Imagery With Contextual Data by Hanlin Tian, Yuxiang Feng, Mohammed Quddus, Yiannis Demiris, Panagiotis Angeloudis

“…These findings underscore the effectiveness of a multimodal approach in traffic risk assessment, offering a more precise tool for urban planning and traffic management interventions. The code and data used in this study are available at <uri>https://github.com/zachtian/Multimodal-Learning-for-Traffic-Risk-Prediction</uri>.…”
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Causes of dog mortality in Paraíba/Brazil: Use of DATASIMA for data diagnosis and mapping by Eduardo S.S. Sousa, Maria E.S. Sousa, Moisés D.C.A. Pereira, Ricardo A.M. Negreiros, Arthur W.L. Brasil, Inácio J. Clementino, Sérgio S. Azevedo, Ricardo B. Lucena

“…The findings of this study demonstrate the feasibility of using DATASIMA for the mapping and standardization of data on the causes of animal death, allowing for strategies for intervention in public health, the prevention of zoonoses, the reduction of garbage codes, better and more efficient communication between veterinary doctors, and the possibility of using ICD-10 to classify the causes of animal death.…”
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Enhancing Industrial Robot Arms Data Security with a Hybrid Encryption Approach by Mustafa Emre Erbil, Hilmi Cenk Bayrakçı, Merdan Özkahraman

“…The suggested encryption framework combines the strengths of Elliptic Curve Cryptography (ECC) for its efficient asymmetric encryption capabilities, ChaCha20 for its rapid and low-energy symmetric encryption, and Poly1305 for ensuring data integrity through its message authentication code (MAC) algorithm. …”
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Fall Detection Based on Recurrent Neural Networks and Accelerometer Data from Smartphones by Natalia Bartczak, Marta Glanowska, Karolina Kowalewicz, Maciej Kunin, Robert Susik

“…We also provide all the data and code used in our experiments publicly, allowing other researchers to reproduce our results.…”
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Link stability - based optimal routing path for efficient data communication in MANET by Renisha Pulinchuvallil Salim, Rajesh Ramachandran

“…Following this, PCC-SWIFFT methodologies are utilized to generate hash codes, serving as unique identifiers for data packets or routing information. …”
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PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse by Einari Vaaras, Manu Airaksinen, Okko Rasanen

“…Self-supervised learning (SSL) is a data-driven learning approach that utilizes the innate structure of the data to guide the learning process. …”
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Tracking Air Pollution Changes Using Sentinel-5P Data in Khuzestan. by Behnaz Ghaderi, Payam Alemi Safaval, Mohammad Reza Tabesh, Zahra Azizi

“…This study utilized Sentinel-5P satellite image products and data from synoptic stations in Khuzestan province. …”
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Utilizing the Ethereum blockchain for retrieving and archiving augmented reality surgical navigation data by Sai Batchu, Michael J. Diaz, Lauren Ladehoff, Kevin Root, Brandon Lucke-Wold

“…Aim: Conventional techniques to share and archive spinal imaging data raise issues with trust and security, with novel approaches being more greatly considered. …”
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The NANOGrav 15 yr Data Set: Harmonic Analysis of the Pulsar Angular Correlations by Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Jeremy G. Baier, Paul T. Baker, Bence Bécsy, Laura Blecha, Kimberly K. Boddy, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Rand Burnette, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Paul B. Demorest, Heling Deng, Lankeswar Dey, Timothy Dolch, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Emiko C. Gardiner, Nate Garver-Daniels, Peter A. Gentile, Kyle A. Gersbach, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, Bjorn Larsen, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Patrick M. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Jonathan Nay, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Polina Petrov, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Jessie C. Runnoe, Alexander Saffer, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Tristan L. Smith, Sophia V. Sosa Fiscella, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Rutger van Haasteren, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, David Wright, Olivia Young, The NANOGrav Collaboration

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