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Batch effect is a frequent challenge in deep sequencing data analysis that can lead to misleading conclusions. Existing methods do not correct batch effects satisfactorily, especially with single-cell RNA sequencing (scRNA-seq) data. To address this ...

As automotive companies increasingly move operations to the cloud, they need to carefully make architectural decisions. Currently, architectural decisions are made ad-hoc and depend on the experience of the involved architects. Recent research has ...

In China’s rapid urbanization, the dietary structure of preschool children tends to be high in sugar, fat, and salt. Due to increased economic and employment pressures, some Chinese families have adopted intergenerational education where children ...

The size of network data increasing tremendously day by day. This huge amount of data contains large number of attributes which need to be analysed for particular application. In this paper, three feature reduction techniques such as, principal component ...

The blended learning model combines traditional classroom instruction with online learning and has shown significant impact in higher education. Analysis of its effectiveness reveals a decrease in the root-mean-square deviation and the smallest mean ...

Regional economic development objectives are improved economic, political, and social conditions in a certain area. Investment, production, innovation, wealth, and affluence are the four stages of regional economic development that may be identified in ...

In recent years, deep learning frameworks have been increasingly used for hyperspectral image classification (HIC) challenges, with outstanding results. Existing network models, on the other hand, are more sophisticated and require longer computing. ...

From four dimensions of resource, environment, ecology (green ecology) and social economy, correlation analysis method and principal component analysis method of SPSS are used to screen evaluation indexes to design a scientific and reasonable evaluation ...

The advancements in cyber-physical systems (CPS) have brought significant changes to the healthcare industry, especially in the exchange of information. Medical CPS integrates smart data collection devices with cyberspace components for data analytics ...

In order to control the cost of online free marketing mode, a recommendation model for online free marketing mode based on social network analysis is proposed in this paper. Firstly, a set of cost constraint indicators for online free marketing mode is ...

In order to improve the accuracy and efficiency of data mining of consumer purchase behaviour in mobile e-commerce, a data mining method of consumer purchase behaviour in mobile e-commerce is proposed. Firstly, through the calculation of support in ...

Artificial light sources make our daily life convenient, but cause a severe problem called light pollution. We propose a novel system for efficient visualization of light pollution in the night sky. Numerous methods have been proposed for rendering the ...

White matter hyperintensities (WMH) in fluid-attenuated inversion recovery (FLAIR) imaging are used as an indicator of clinical conditions ranging from multiple sclerosis to cerebrovascular disease. However, the biophysics underlying FLAIR WMH is ...

Aiming at the problem that cohesion force and internal friction Angle are difficult to be measured as shear strength indexes, correlation analysis and principal component analysis are used to explore the relationship between these two indexes and the ...

Oxides are classified into various oxides according to their constituent elements, among which there are binary and quaternary oxides. Binary oxides are widely used in industry, and quaternary oxides have great potential in this aspect of ...

In this paper, we consider the alignment between an upstream dimensionality reduction task of learning a low-dimensional representation of a set of high-dimensional data and a downstream optimization task of solving a stochastic program parameterized by ...

In the field of Explainable AI, population-based search metaheuristics are of growing interest as they become more widely used in critical applications. The ability to relate key information regarding algorithm behaviour and drivers of solution ...

Modeling as real options the operations of energy production companies that operate in wholesale markets gives rise to a challenging Markov decision process. In “Least Squares Monte Carlo and Pathwise Optimization for Merchant Energy Production,” Yang, ...

We study merchant energy production modeled as a compound switching and timing option. The resulting Markov decision process is intractable. Least squares Monte Carlo combined with information relaxation and duality is a state-of-the-art reinforcement ...

At present, with the development of 5G technology, the bandwidth requirement of data communication is increasing, which makes the limited spectrum resources become more and more tight. Based on the current situation of the utilization and allocation of ...

The movement of large quantities of data during the training of a deep neural network presents immense challenges for machine learning workloads, especially those based on future functional memories deployed to store network models. As the size of network ...