Models with unnormalized probability density functions are ubiquitous in statistics, artificial intelligence and many other fields. However, they face significant challenges in model selection if the normalizing const...
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This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous *** s...
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This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous *** study proposes a classification framework for SOM research based on product flow,from its design to its final *** SOM has been studied for many years,most related research remains *** criterion for choosing papers is that they must be relevant to practical *** review aims to provide readers a guide that will facilitate their search for papers in their field of *** importantly,we hope that this review can provide insightful managerial implications for SOM.
Credit risk assessment is crucial for financial institutions. The data-driven methods regard the credit risk assessment as the class-imbalanced binary classification task since the non-default samples greatly outnumbe...
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In this work, we address the challenging task of Generalized Referring Expression Comprehension (GREC). Compared to the classic Referring Expression Comprehension (REC) that focuses on single-target expressions, GREC ...
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In the rapidly evolving field of medical diagnostics, the challenge of imbalanced datasets, particularly in diabetes classification, calls for innovative solutions. The study introduces DiGAN, a groundbreaking approac...
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We propose an autoregressive framework for modelling dynamic networks with dependent edges. It encompasses the models which accommodate, for example, transitivity, density-dependent and other stylized features often o...
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Private mutual authentication(PMA) enables two-way anonymous authentication between two users certified by the same trusted group authority. Most existing PMA schemes focus on acquiring a relatively onefold authentica...
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Private mutual authentication(PMA) enables two-way anonymous authentication between two users certified by the same trusted group authority. Most existing PMA schemes focus on acquiring a relatively onefold authentication policy that ensures affiliation-hiding or designated single-attribute ***, in practice, users are typically provided with multiple attributes. In addition to the affiliation-hiding requirement, how to effectively achieve a more flexible authentication policy for multi-attribute applications remains a challenging issue. The intersection policy for authentication is also required when the attribute intersection is not an empty set or its cardinality is no less than a threshold value. To solve the above problems, we first propose an optimal authorized private set intersection protocol with forward security based on identity-based encryption and then design a new PMA protocol with intersection-policy called IP-PMA, which provides a simple solution for secret handshakes between two members(holding multiple attributes) from the same organization. Formal security analyses proved that our two proposed protocols are secure in the random oracle model. Empirical tests demonstrated that the IP-PMA protocol is optimized with linear complexity and may be more suitable for resource-constrained applications.
The Olympic Games are striking a balance between economic and ecological benefits. Taking the 5 ice event venues of the 2018 PyeongChang Winter Olympic Games as the research object, the CO2 emissions under the 2018 Py...
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It is an important task in the literature to check whether a fitted autoregressive moving average (ARMA) model is adequate, while the currently used tests may suffer from the size distortion problem when the underlyin...
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Covariance regression offers an effective way to model the large covariance matrix with the auxiliary similarity matrices. In this work, we propose a sparse covariance regression (SCR) approach to handle the potential...
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