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    <title>Artificial Intelligence Tools and Applications in Embedded and Mobile Systems</title>
    <subTitle>Selected Papers from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), 24-25 November 2022, Arusha, Tanzania</subTitle>
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    <namePart>Marx Gómez, Jorge.</namePart>
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    <namePart>Elikana Sam, Anael.</namePart>
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    <namePart>Godfrey Nyambo, Devotha.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>XV, 271 p. 30 illus. online resource.</extent>
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  <abstract>The emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI’s impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.</abstract>
  <tableOfContents>Improving Robustness of Optimized Parameters Gradient Tree Boosting for Crime Forecast Model -- Evidence Based Practices On Co-Operative Societies Information Record Management -- Influence of Microservice Design Patterns for Data Science Workflows -- A systematic literature review toward standardization of business rules discovery in the context of Process Mining -- Contextual Multi-view Graph Community Detection using Graph Neural Networks -- Feature Selection Approach To Improve Malaria Diagnosis Model's Performance For High And Low Endemic Areas Of Tanzania -- 2-Stage Hybrid Ensemble Based Heterogeneous Committee Machine for Improving Soil Fertility Status Prediction Performance -- Convolutional Neural Network deep learning model for early detection of streak virus and lethal necrosis in maize: A case of Northern-highlands, Tanzania -- Object Detection Model for Poultry Diseases Diagnostics -- Machine Learning Model for Predicting Construction Project Success in Tanzania -- Improved MedicalImaging Transfer learning through the conflation of domain features -- Determining Emotion Intensities From Audio Data Using A Convolutional Neural Network -- Machine Learning Based Forward Collision Avoidance System: A Case study for the Kayoola EVS -- Visualizing Outlier Explanations for Mixed-type Data -- A Dolutegravir-Associated Hyperglycemia Computational Prediction Tool for People Living with HIV in Uganda -- Extraction of Numerical Facts from German Texts to enrich Internal Audit Data -- From Process Mining to Enterprise Mining -- CNN With Attention Guided Concatenation For Improved Image Restoration -- A Contribution to the Development of Sustainable Target Value Streams with Machine Learning Considering Material Flow Cost -- Mask R-CNN model for banana diseases segmentation -- The artificial neural network-based smart number plate for vehicles with real-time traffic signs recognition and notification -- Intermodal matching algorithm including public transportation and ride-hailing -- A Machine Learning-Based IoT Environmental Monitoring Platform for Data Centres.</tableOfContents>
  <note type="statement of responsibility">edited by Jorge Marx Gómez, Anael Elikana Sam, Devotha Godfrey Nyambo.</note>
  <subject authority="lcsh">
    <topic>Information technology</topic>
    <topic>Management</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Artificial intelligence</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Big data</topic>
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  <subject authority="lcsh">
    <topic>Computers, Special purpose</topic>
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  <subject authority="lcsh">
    <topic>Business information services</topic>
  </subject>
  <subject>
    <topic>Business IT Infrastructure</topic>
  </subject>
  <subject>
    <topic>Artificial Intelligence</topic>
  </subject>
  <subject>
    <topic>Big Data</topic>
  </subject>
  <subject>
    <topic>Special Purpose and Application-Based Systems</topic>
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  <subject>
    <topic>Business Information Systems</topic>
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  <classification authority="lcc">HD30.2</classification>
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  <identifier type="isbn">9783031565762</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-56576-2</identifier>
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