Review of privacy computing techniques for multi-party data fusion analysis by LIU Shenglong, HUANG Xiuli, JIANG Yiwen, JIANG Jiawei, TIAN Yuechi, ZHOU Zejun, NIU Ben

“…This work focused on the needs of multi-party privacy computing for cross-system exchanges in ubiquitous sharing environments, taking the security sharing and controlled dissemination of private data in multi-party data fusion applications as the starting point, and provided reviews of existing relevant work from the perspectives of multi-party privacy computing, multi-party privacy information sharing control, and multi-party data collaborative secure computing. …”
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Geographical origin discrimination of Chenpi using machine learning and enhanced mid-level data fusion by Xin Kang Li, Li Jun Tang, Ze Ying Li, Dian Qiu, Zhuo Ling Yang, Xiao Yi Zhang, Xiang-Zhi Zhang, Jing Jing Guo, Bao Qiong Li

“…Four machine learning methods are employed to establish discrimination models based on GC and MIR data, with two mid-level data fusion strategies to combine the data. The results show that data fusion significantly improves Chenpi origin discrimination. …”
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Enhanced multivariate data fusion and optimized algorithm for comprehensive quality profiling and origin traceability of Chinese jujube by Peng Chen, Xiaoli Wang, Rao Fu, Xiaoyan Xiao, Yu Li, Tulin Lu, Tao Wang, Qiaosheng Guo, Peina Zhou, Chenghao Fei

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Time-Series Load Online Prediction of Wind Turbine Based on Adaptive Multisource Operational Data Fusion by Ruojin Wang, Xiaodong Wang, Deyi Fu, Bin Yang, Yingming Liu

“…Aiming at the problem that the stochastic change of wind turbine generator (WTG) working conditions and the complex nonlinear relationship between load and operation data make it difficult to predict the short-term load online, this paper proposes an adaptive multi-information source data fusion online prediction method for WTG load. Random forest (RF) and WaveNet time series (WTS) are established as subinformation source models, and the influence of input features and historical data on load prediction is considered from horizontal and vertical dimensions. …”
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TMFN: a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis by Junsong Fu, Youjia Fu, Huixia Xue, Zihao Xu

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Application of IoT and blockchain technology in the integration of innovation and industrial chains in high-tech manufacturing by Zepei Li, Peng Zheng, Yanjia Tian

“…This study introduces BD-IoTQNet, a novel framework designed to address these challenges by integrating data fusion, anomaly detection using the Isolation Forest algorithm, and blockchain-enabled DQM (Data Quality Management). …”
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Multi-key fully homomorphic encryption scheme based on NTRU bootstrapping by ZHENG Junhua, JIANG Hongwei, LIU Rong, LI Yixiu, LI Wen, WENG Jian

“…Multi-key fully homomorphic encryption (MK-FHE) technology supports homomorphic operations on ciphertexts encrypted with different keys, and can be directly applied to real-world multi-user data fusion computing scenarios, such as multi-party collaborative computing and federated learning. …”
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Targeting ferroptosis in prostate cancer management: molecular mechanisms, multidisciplinary strategies and translational perspectives by Hubo Yang, Xuefeng Zhang, Zongming Jia, He Wang, Jixiang Wu, Xuedong Wei, Yuhua Huang, Wenying Yan, Yuxin Lin

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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

“…Traditional single models show limitations in processing large-scale multimodal data.MethodsThis study constructed an interpretable ensemble learning model for maize seed variety identification through improved differential evolutionary algorithm and multimodal data fusion. Morphological and hyperspectral data of maize samples were extracted and preprocessed, and three methods were used to screen features, respectively. …”
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A CNN-RF Hybrid Approach for Rice Paddy Fields Mapping in Indramayu Using Sentinel-1 and Sentinel-2 Data by Dodi Sudiana, Mia Rizkinia, Rahmat Arief, Tiara De Arifani, Anugrah Indah Lestari, Dony Kushardono, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo

“…This research focuses on developing a classification model for rice paddy field mapping using remote sensing with radar and optical data fusion, including input variations in polarization, texture, and optical derivative indices. …”
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