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Correlation–Comparison Analysis as a New Way of Data-Mining: Application to Neural Data
This paper aims to present a way of multidimensional data-mining termed correlation–comparison analysis (CCA). It was applied to neural data to...
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Performance analysis of memory data layout for sub-block data access
The design of Digital Signal Processing systems involving video data has many challenges other than the optimal design of the processing algorithms....
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Analysis of Employment Information of University Graduates through Data Mining
Abstract—The employment information of university graduates contains a lot of useful information that can provide guidance for employment. This paper...
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Research on interactive analysis report in data analysis and visualization platform
In order to solve the problem that the traditional data analysis visualization tools cannot fully express the potential information behind the...
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An Efficient Data Analysis Method for Big Data Using Multiple-Model Linear Regression
This paper introduces a new data analysis method for big data using a newly defined regression model named multiple model linear regression(MMLR),...
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ContextMate: a context-aware smart agent for efficient data analysis
Pre-trained large language models (LLMs) have demonstrated extraordinary adaptability across varied tasks, notably in data analysis when supplemented...
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Vehicle Industry Big Data Analysis Using Clustering Approaches
Considering a globalized world economy and industry, data analysis and visualization offer enlightening information for decision-making and strategic...
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A General Framework for Blockchain Data Analysis
Blockchain is a foundational technology that allows application paradigms to shift from trusting humans to trusting machines and from centralized to...
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Improving DNS Data Exfiltration Detection Through Temporal Analysis
By leveraging the DNS tunneling technique, malicious actors have the ability to transfer covertly data embedded within a DNS transaction. A DNS...
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Visual sentiment analysis using data-augmented deep transfer learning techniques
The use of visual content to express emotions on social media platforms has become increasingly popular. Visual sentiment analysis can be used to...
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A framework for mediation analysis with massive data
During the past few years, mediation analysis has gained increasing popularity across various research fields. The primary objective of mediation...
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Functional classwise principal component analysis: a classification framework for functional data analysis
In recent times, functional data analysis has been successfully applied in the field of high dimensional data classification. In this paper, we...
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Analysis of Non-imaging Data
Whilst most of this book has focused on imaging data because of the key role it plays in cardiology, non-imaging data also has an important role to...
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VIS+AI: integrating visualization with artificial intelligence for efficient data analysis
Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On one hand, visualization can facilitate humans in data...
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Integrating FAIR Experimental Metadata for Multi-omics Data Analysis
The technological advancements in bio-science research are resulting in the generation of vast amounts of complex and heterogeneous data sets from...
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Boosting HPC data analysis performance with the ParSoDA-Py library
Develo** and executing large-scale data analysis applications in parallel and distributed environments can be a complex and time-consuming task....
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DeepVisInterests : deep data analysis for topics of interest prediction
Deep data analysis for latent information prediction has become an increasingly important area of research. In order to predict users’ interests and...
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Recent trends in computational intelligence for educational big data analysis
Educational big data analytics and computational intelligence have transformed our understanding of learning ability and computing power, catalyzing...
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Python for Data Analysis
This chapter will introduce Ethics in algorithm development and common tools that are used for data analysis. Ethics is an important consideration in...
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Analysis of missing data and comparing the accuracy of imputation methods using wheat crop data
In a realistic scenario, the dataset has missing values encountered during the data collection. To effectively build the prediction model, the...
