Research in the data-oriented areas of computerscience is contributing a new wave of theory and tools for learning from data. Some of the research areas complement those in statistics and others overlap. While the re...
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Research in the data-oriented areas of computerscience is contributing a new wave of theory and tools for learning from data. Some of the research areas complement those in statistics and others overlap. While the research topics of the two fields are not the same, the goals of the research are identical–to enhance theory, methods, models, and systems for the study of data. Unification–close collaboration in research, in teaching, and in applications–would greatly enhance new developments in learning from data.
The detection of community structures in complex networks has garnered significant attention in recent years. Given its NP-hardness, numerous evolutionary optimization-based approaches have been proposed. However, the...
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Keystroke biometrics is a promising approach for user identification and verification, leveraging the unique patterns in individuals’ typing behavior. In this paper, we propose a Transformer-based network that employ...
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This article proposes a novel method for detecting shilling attacks in Matrix Factorization (MF)-based Recommender Systems (RSs), in which attackers use false user-item feedback to promote a specific item. Unlike exis...
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Currently, it has become a consensus to enhance privacy protection. Randomized response(RR) technique, as the mainstream perturbation mechanism for local differential privacy, has been widely studied. However,most of ...
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Currently, it has become a consensus to enhance privacy protection. Randomized response(RR) technique, as the mainstream perturbation mechanism for local differential privacy, has been widely studied. However,most of the research in literature managed to modify existing RR schemes and propose new mechanisms with better privacy protection and utility, which are illustrated only by numerical experiments. We study the properties of generalized binary randomized response mechanisms from the perspectives of Lanke privacy and utility. The mathematical expressions of privacy and utility for the binary RR mechanism are given respectively. Moreover, the comparison principle for privacy and utility of any two mechanisms is proved. Finally, the optimization problem of the binary RR mechanism is discussed. Our work is based on a rigorous mathematical proof of privacy and utility for the general binary RR mechanism, and numerical verification illustrates the correctness of the conclusions. It can provide theoretical support for the design of binary RR mechanism and can be applied in data collection, analysis and publishing.
With digitisation globally on the rise, corporates are compelled to better understand the usage of their websites. In doing so, corporates will be empowered to better understand consumers, and make necessary adjustmen...
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In this paper, we propose a new iterative method for approximating a common solution of pseudo-monotone equilibrium problems and common fixed point problems of Bregman quasi-nonexpansive mappings in a p-uniformly conv...
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Colorectal cancer is one of the most prevalent cancers in the world. It illustrates the effectiveness of early detection and treatment of precursor polyps to prevent progression to malignancy. Despite the pivotal role...
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Sentiment analysis has witnessed significant advancements with the emergence of deep learning models such as transformer models. Transformer models adopt the mechanism of self-attention and have achieved state-of-the-...
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The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical *** article presents a novel mathematical...
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The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical *** article presents a novel mathematical model that addresses the dynamics of this co-infection by extending the SEIR(Susceptible-Exposed-Infectious-Recovered)framework to incorporate treatment and hospitalization *** population is divided into eight compartments,with infectious individuals further categorized into influenza infectious,corona infectious,and co-infection *** proposed mathematical model is constrained to adhere to fundamental epidemiological properties,such as non-negativity and boundedness within a feasible ***,the model is demonstrated to be well-posed with a unique *** points,including the disease-free and endemic equilibria,are identified,and various properties related to these equilibrium points,such as the basic reproduction number,are *** and global sensitivity analyses are performed to identify the parameters that highly influence disease dynamics and the reproduction *** the most influential parameters is crucial for understanding their impact on the co-infection’s spread and ***,an optimal control problem is defined to minimize disease transmission and to control strategy *** purpose of our study is to identify the most effective(optimal)control strategies for mitigating the spread of the co-infection with minimum cost of the *** results illustrate the effectiveness of the implemented control strategies in managing the co-infection’s impact on the population’s *** mathematical modeling and control strategy framework provides valuable tools for understanding and combating the dual threat of corona and influenza co-infection,helping public health authorities and policymakers make informed decisions in the face of these intertwined epidemics.
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