Adaptive data embedding for curved spaces by Anoop Praturu, Tatyana O. Sharpee

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JTAG and Chip-Off Technologies in Computer Forensics by A. N. Yakovlev, A. S. Danilova

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Exploring the feasibility of a data center-free cloud computing framework utilizing underutilized personal computers by Ibrahim Mekawy, Alhanouf Alburaikan, Iman Atighi

“…Big Data and Computing Visions…”
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An Analysis of Age-Related Body Composition Changes and Metabolic Patterns in Korean Adults Using FDG-PET/CT Health Screening Data by Chang-Myung Oh, Ji-In Bang, Sang Yoon Lee, Jae Kyung Lee, Jee Won Chai, So Won Oh

“…The present study aimed to identify age-related changes in body composition and glucose metabolism in Korean using opportunistic FDG-PET/CT imaging. …”
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Computational modeling of epidemiological count data using Non-Homogeneous Poisson Processes and functional data by Santiago Ortiz, Juan Esteban Chavarría, Henry Velasco

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Advancements in Coded Computation: Integrating Encoding Matrices with Data Shuffling for Enhanced Data Transmission Efficiency by Yuan Shijie

“…In the interconnected age of big data, cloud computing, and the Internet of Things, the demand for robust data processing and transmission systems is critical. …”
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Faster computation of left-bounded shortest unique substrings by Larissa L. M. Aguiar, Felipe A. Louza

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Multimedia: multimodal mediation analysis of microbiome data by Hanying Jiang, Xinran Miao, Margaret W. Thairu, Mara Beebe, Dan W. Grupe, Richard J. Davidson, Jo Handelsman, Kris Sankaran

“…The software includes modules for regularized linear, compositional, random forest, hierarchical, and hurdle modeling, making it well-suited to microbiome data. …”
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CLOUD COMPUTING SECURITY by Ştefan IOVAN, Alina Anabela IOVAN

“…Cloud computing reprentes the software applications offered as a service online, but also the software and hardware components from the data center.In the case of wide offerd services for any type of client, we are dealing with a public cloud. …”
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Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia by Junkang Zhao, Junkang Zhao, Yajie Zhao, Jiannan Han, Jiannan Han, Yixuan Zhao, Sumiao Liu, Zhida Liu, Liyun Zhang, Yan Zhang

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Movement behaviors and cardiorespiratory fitness – a cross-sectional compositional data analysis among German adults by Alexander Roosz, Martin Bahls, Sabina Ulbricht, Antje Ullrich, Anne Obst, Beate Stubbe, Ralf Ewert, Sabine Kaczmarek, Till Ittermann, Marcus Dörr, Lisa Voigt

“…Abstract Background We investigated associations of movement behaviors (moderate-vigorous physical activity, light physical activity, and stationary time) with various parameters measured during cardiopulmonary exercise testing. We applied compositional data analysis to account for the relative contributions of different movement behaviors to the overall time budget of the waking day. …”
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Assessing the damage: analyzing the impact of the COVID-19 pandemic on accelerometer-assessed 24-hour movement behaviours in Brazilian adolescents by Marcus V. V. Lopes, Ian Janssen, Bruno G. G. da Costa, Bruno N. de Oliveira, Gabrielli T. de Mello, Jean-Philippe Chaput, Kelly S. Silva

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Biomedical Informatics and Computational Biology for High-Throughput Data Analysis by Bairong Shen, Jian Ma, Jiajun Wang, Junbai Wang

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Single‐Cell Hi‐C Technologies and Computational Data Analysis by Madison A Dautle, Yong Chen

“…Although many scHi‐C protocols have been developed, they often involve intricate procedures and the resulting data are sparse, leading to computational challenges for systematic data analysis and limited applicability. …”
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Computational methods for protein identification from mass spectrometry data. by Leo McHugh, Jonathan W Arthur

“…Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. …”
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Application of the Fuzzy Computational Intelligence in Power Quality Data Management by Hoda Farag

“…This Paper addresses the perfect load management using the computational techniques by analyzing the data of the system taking into account the density of the  feeding nodes and its distribution  also the classification of major Power quality degradations such as power factor and harmonics in the System and The methodology will be illustrated, simulated and evaluated using the fuzzy technique clustering the data and on an Artificial Neural Network (ANN) to achieve the optimum utilization of the energy loads and perfect load management and optimization. …”
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Bayesian deconvolution for computational cognitive modeling of fMRI data by Jonathon R. Howlett, Katia M. Harlé, Alan N. Simmons, Charles T. Taylor

“…A central goal of cognitive neuroscience is to make inferences about underlying cognitive processes from observable data. However, current fMRI analysis tools cannot directly estimate latent parameters in computational cognitive models from blood-oxygen-level-dependent (BOLD) signal. …”
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Dna-storalator: a computational simulator for DNA data storage by Gadi Chaykin, Omer Sabary, Nili Furman, Dvir Ben Shabat, Eitan Yaakobi

“…Results The DNA-Storalator is a cross-platform software tool that simulates in a simplified digital point of view biological and computational processes involved in the process of storing data in DNA molecules. …”
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Data-driven polarimetric approaches fuel computational imaging expansion by Sylvain Gigan

“…Incorporating polarization in computer vision tasks provides new solutions to high-level analytics, in particular when coupled with machine learning frameworks such as convolutional neural networks (CNN). …”
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Breakdown of the compositional data approach in psychometric Likert scale big data analysis: about the loss of statistical power of two-sample t-tests applied to heavy-tailed big data by René Lehmann, Bodo Vogt

“…Considering psychometric bipolar scale data as compositional data can enhance the statistical power of well-known paired and unpaired two-sample t-tests, supporting managerial decision-making and the development or implementation of health interventions. …”
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