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    Volume 2, Issue 1 - Table of Contents
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    March (2024), pp.1-35, 4 articles
    Citations: 0, 0   |   Viewed: 4351, Download: 447
    Free Access | Research Article | 12 March 2024
    Advancements in Multi-Year Ice Concentration Estimation from SSM/I 91.6GHz Observations
    by
    Yue Zhao
    ,
    Xingdong Wang
    ,
    Zifan Zhang
    IECE Transactions on Internet of Things | Volume 2, Issue 1: 26-35, 2024 | DOI:10.62762/TIOT.2024.682080
    Abstract
    To enhance the LOMAX algorithm for sea ice concentration analysis in the polar regions, SSM/I 91.6GHz data was utilized, addressing the underuse of higher frequency data. The refinement process involved redefining PCT values for one-year and multi-year ice regions through both interpolation and least squares methods. Moreover, band operations were conducted to facilitate Arctic multi-year ice concentration retrieval. Comparative analyses with the NT algorithm indicated that the Arctic sea ice extents determined by both algorithms were similar, affirming the credibility of the modified LOMAX algorithm. When examining the results for March and September, the updated LOMAX algorithm demonstrate... More >
    Graphical Abstract
    Advancements in Multi-Year Ice Concentration Estimation from SSM/I 91.6GHz Observations
    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 | 14 January 2024
    3D Convolutional Neural Network-Based Multi-Parameter Video Quality Assessment Model on Cloud Platforms
    by
    Xue Li
    ,
    Jiali Qiu
    IECE Transactions on Internet of Things | Volume 2, Issue 1: 8-19, 2024 | DOI:10.62762/TIOT.2024.369369
    Abstract
    In light of the rapid advancements in big data and artificial intelligence technologies, the trend of uploading local files to cloud servers to mitigate local storage limitations is growing. However, the surge of duplicate files, especially images and videos, results in significant network bandwidth wastage and complicates server management. To tackle these issues, we have developed a multi-parameter video quality assessment model utilizing a 3D convolutional neural network within a video deduplication framework. Our method, inspired by the analytic hierarchy process, thoroughly evaluates the effects of packet loss rate, codec, frame rate, bit rate, and resolution on video quality. The model... More >
    Graphical Abstract
    3D Convolutional Neural Network-Based Multi-Parameter Video Quality Assessment Model on Cloud Platforms
    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