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    Author 3
    ORCID
    0009-0000-9335-9773
    Ping Zhang
    School of Computer, BaoJi University of Arts and Sciences
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    3
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    Free Access | Research Article | 23 May 2024
    Machine Learning-Based Prediction of Cardiovascular Diseases
    by
    Weicheng Sun
    ,
    Ping Zhang
    ,
    Zilin Wang
    ,
    Dongxu Li
    IECE Transactions on Internet of Things | Volume 2, Issue 2: 50-54, 2024 | DOI:10.62762/TIOT.2024.128976
    Abstract
    With the rapid development of artificial intelligence, extracting latent information from medical data has become increasingly critical. Cardiovascular disease is now a major threat to human health, being one of the leading causes of mortality. Therefore, developing effective prediction methods for cardiovascular diseases is urgently needed. Current medical approaches primarily focus on disease detection rather than prediction, which limits early intervention. By leveraging computational methods, it is possible to predict cardiovascular disease in advance, enabling timely treatment and potentially reducing the disease’s impact. This study employs machine learning techniques, including Supp... More >
    Graphical Abstract
    Machine Learning-Based Prediction of Cardiovascular Diseases
    Free Access | Research Article | 12 February 2024
    Application of Dimension Reduction Methods to High-Dimensional Single-Cell 3D Genomic Contact Data
    by
    Zilin Wang
    ,
    Ping Zhang
    ,
    Weicheng Sun
    ,
    Dongxu Li
    IECE Transactions on Internet of Things | Volume 2, Issue 1: 20-25, 2024 | DOI:10.62762/TIOT.2024.186430
    Abstract
    The volume and complexity of data in various fields, particularly in biology, are increasing exponentially, posing a challenge to existing analytical methods, which often struggle with high-dimensional data such as single-cell Hi-C data. To address this issue, we employ unsupervised methods, specifically Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE), to reduce data dimensions for visualization. Furthermore, we assess the information retention of the decomposed components using a Linear Discriminant Analysis (LDA) classifier model. Our findings indicate that these dimensionality reduction techniques effectively capture and present information not r... More >
    Graphical Abstract
    Application of Dimension Reduction Methods to High-Dimensional Single-Cell 3D Genomic Contact Data
    Free Access | Research Article | 11 January 2024
    Development and Evaluation of an IoT-Based Monitoring System for Patchouli Cultivation: An Integrated Approach to Enhance Agricultural Efficiency
    by
    Guodong Li
    ,
    Ping Zhang
    IECE Transactions on Internet of Things | Volume 2, Issue 1: 1-7, 2024 | DOI:10.62762/TIOT.2024.499965
    Abstract
    This study investigates the application of Internet of Things (IoT) technology in agriculture, focusing on the cultivation of patchouli, a medicinal plant known for its therapeutic properties. The research highlights the specific growth requirements and medicinal benefits of patchouli, and proposes a monitoring system based on ZigBee technology. The system's hardware design incorporates cc2530 and esp8266 chips for wireless data transmission, while communication between the OneNET cloud server and the MySQL database is managed through MQTT, TCP/IP, and HTTP protocols. This integration showcases the potential of IoT to significantly enhance agricultural efficiency by providing real-time data... More >
    Graphical Abstract
    Development and Evaluation of an IoT-Based Monitoring System for Patchouli Cultivation: An Integrated Approach to Enhance Agricultural Efficiency