Article
Biochemical Research Methods
Umberto Ferraro Petrillo, Francesco Palini, Giuseppe Cattaneo, Raffaele Giancarlo
Summary: The study introduces a new big data platform, FADE, for alignment-free genomic analysis, supporting 18 best-performing AF functions, with faster execution time and user-friendly software design. Additionally, it provides a novel analysis of the informativeness and robustness of AF functions, finding that only a handful of functions out of the 18 included in FADE can actually be used.
Article
Multidisciplinary Sciences
Bivas Dutta, Wenmin Yang, Ron Melcer, Hemanta Kumar Kundu, Moty Heiblum, Vladimir Umansky, Yuval Oreg, Ady Stern, David Mross
Summary: Quantum Hall states have unique quantum phases characterized by gapless edge modes. The most studied nonabelian state is the spin-polarized filling factor 5/2, which can have different topological orders. By interfacing this state with another, we were able to identify its topological order as the particle-hole Pfaffian (PH-Pf) order.
Article
Mathematics
Vasile Preda, Luigi-Ionut Catana
Summary: Theoretical results for different stochastic orders of a log-scale-location family using Tsallis statistics functions are presented, describing inequalities of moments and Gini index based on parameters. Mean calculations for q-Weibull and q-Gaussian distributions are also included. The article analyzes the order between survival functions, Lorenz curves, moments, and Gini index, with a real data application demonstrating the implications of stochastic order.
Article
Engineering, Electrical & Electronic
Mengxi Liu, Xuezhang Li, Zhuoqun Chai, Anqi Chen, Yuanyuan Zhang, Qingnian Zhang
Summary: As high temperature and heatwave pose great threats to human survival, it is important to understand the spatial and temporal changes of temperature. Traditional methods, such as meteorological stations, only provide limited information. To address this, a joint spatio-temporal method using remote sensing data was proposed to obtain dense temperature mapping. Additionally, a heatwave risk model based on population and temperature data was developed to evaluate the risk in different areas. The effectiveness of these methods has been verified through accuracy evaluations and case studies in Zhejiang Province.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Statistics & Probability
Lucy D'Agostino McGowan, Roger D. Peng, Stephanie C. Hicks
Summary: The data revolution has sparked interest in data analysis practices, and design thinking serves as a complementary form of thinking in the field. The choices made by data analysts and producers in constructing and designing data analyses can significantly impact the resulting products and consumer experience. This study introduces design principles for data analysis and explores their variations among producers, providing guidance for characterizing the data analytic process.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2023)
Article
Multidisciplinary Sciences
Omer Bobrowski, Primoz Skraba
Summary: This article reports a surprising discovery that persistence diagrams arising from random point-clouds follow a universal probability law when normalized properly. The authors reach this conclusion based on extensive experimentation on simulated and real data, encompassing point-clouds with diverse geometry, topology, and probability distributions. They also propose a new hypothesis testing framework for computing significance values for individual topological features within persistence diagrams, offering a new quantitative approach to assessing the significance of structure in data.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Interdisciplinary Applications
Alexander Smith, Benjamin Laubach, Ivan Castillo, Victor M. Zavala
Summary: This article explores the use of tools from Riemannian geometry for the analysis of symmetric positive definite matrices. SPD matrices, commonly used in chemical engineering and image analysis, can benefit from techniques that exploit the properties of Riemannian manifold in tasks such as classification and dimensionality reduction.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Physics, Multidisciplinary
M. Ruelle, E. Frigerio, J. -M. Berroir, B. Placais, J. Rech, A. Cavanna, U. Gennser, Y. Jin, G. Feve
Summary: Recent anyon collision experiments have shown the ability to distinguish between fermionic and anyonic statistics. However, only one type of anyons associated with the Laughlin state at filling factor nu = 1/3 has been studied so far. It is important to establish anyon collisions as quantitative probes for more complex topological orders and different species of anyons. In this study, we compare the Laughlin nu = 1/3 state with the Jain nu = 2/5 state, and demonstrate the robustness of anyon collision signals for anyons of the same type while also showing the ability to distinguish between different species of anyons. Our results indicate the influence of interchannel interactions in anyon collision experiments with multiple edge channels.
Article
Computer Science, Theory & Methods
Muhammad Aslam
Summary: This paper introduces that the existing Z-test for comparing sequential contingencies can only be implemented in the presence of certain frequencies and the level of significance. However, it cannot be applied when uncertainty/indeterminacy is found in observed frequencies. This paper proposes a modification of the Z-test for comparing sequential contingencies under indeterminate environment using neutrosophic statistics, and provides the decision procedure with an example from the psychology field. The proposed Z-test is found to be more effective and informative than the existing one.
JOURNAL OF BIG DATA
(2023)
Article
Ergonomics
Yuping Hu, Ye Li, Helai Huang
Summary: This study aims to explore the spatio-temporal dynamic change mechanism of conflict risk based on trajectory data. By integrating and assessing conflict frequency and severity using fuzzy logic theory, the spatial Markov model and panel regression approach are employed to analyze the relationship between spatio-temporal risk and traffic characteristics. The modeling results show that the dynamic change trend of safety states differs under different spatial lag conditions, and the dynamic spatial panel data modeling method performs better than the model that only considers temporal or spatial dependency. This novel framework contributes to a more comprehensive assessment of real-time road safety from a mesoscopic perspective.
ACCIDENT ANALYSIS AND PREVENTION
(2023)
Article
Computer Science, Theory & Methods
Muhammad Aslam, Faten S. Alamri
Summary: The existing Fisher's exact test is commonly used to investigate the significance of differences between observed frequencies. However, it can only be applied when the observed frequencies are in a determinate form without vague information. In complex production processes, observed frequencies are often not in a determinate form, leading to potential misleading results when using the existing Fisher's exact test. This paper proposes a modification of Fisher's exact test using neutrosophic statistics, and provides an operational process, simulation study, and application using production data. Analysis of industrial data indicates that the proposed Fisher's exact test performs better than the existing one.
JOURNAL OF BIG DATA
(2023)
Article
Biochemical Research Methods
Shuang Song, Lin Hou, Jun S. Liu
Summary: The study introduced a unified Bayesian regression framework NeuPred for constructing PRS, which accommodates varying genetic architectures and improves prediction accuracy for complex diseases. An automatic chromosome-level prior selection strategy based on summary statistics was proposed, demonstrating significant improvement in accuracy. NeuPred showed substantial and consistent improvements in predictive r(2) over existing methods, while maintaining similar or advantageous computational efficiency.
Article
Hospitality, Leisure, Sport & Tourism
Adam Weaver
Summary: Efforts to aggregate data comprehensively have led to a crisis of analysis in the tourism industry, where individuals are increasingly treated as mere objects. The recognition of tourism as a series of distinctive human actions is overshadowed by a fervor for impersonal mass quantification, reflecting tensions caused by a positivistic, business-driven way of knowing in the industry.
ANNALS OF TOURISM RESEARCH
(2021)
Article
Energy & Fuels
Vitor Hugo Ferreira, Rubens Lucian da Silva Correa, Angelo Cesar Colombini, Marcio Zamboti Fortes, Flavio Luis de Mello, Fernando Carvalho Cid de Araujo, Natanael Rodrigues Pereira
Summary: This paper presents a big data analytics-based model developed for electric distribution utilities aiming to forecast the demand of service orders (SOs) on a spatio-temporal basis. The algorithm automatically forecasts the number of SOs that will need to be executed in each location in several time steps, based on robust history and location data provided by an energy utility.
Article
Automation & Control Systems
Subha Maity, Yuekai Sun, Moulinath Banerjee
Summary: This paper discusses the task of meta-analysis in high-dimensional settings with similar but non-identical data sources. A global parameter is introduced to borrow strength across heterogeneous datasets, emphasizing interpretability and statistical efficiency in the presence of heterogeneity. A one-shot estimator of the global parameter is also proposed, which preserves data source anonymity and converges based on the size of the combined dataset. The paper demonstrates the superior performance of the identification restrictions in adapting to known data distribution and predicting for new/unseen data distribution in high-dimensional linear model settings. The benefits of the approach are further demonstrated on a large-scale drug treatment dataset involving different cancer cell-lines.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)