Titlebook: 5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing; BDCC 2022 Anandakumar Haldorai,Arulmurugan Ram

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Karl-Heinz Hellwich,Carsten D. Siebertfor the silver nanoparticle images, and the PNN classifier has an accuracy of 86.67% for boron, 93.33% for iron, and 93.33% for silver nanoparticle images. Hence, based on the experimentation, the proposed study suggested that the PNN classification with texture features is the best classifier used

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https://doi.org/10.1007/978-3-662-10660-0edict the outcome of unstructured data. The primary purpose of the research is to reduce the rising size of data stored and sent, improve data security, and create organized data using machine learning techniques. A graphical model shows our aim of research attained with exemplary efficient implemen

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Die Klassisch-Neoklassische Theorie management system. It provides an overview of the system architecture with insights into the mesh network formed using Raspberry Pi 4 and ESP32 with MQ Telemetry Transport (MQTT) protocol. The mesh network, layered architecture, and MQTT communication system are presented. The system is highly flex

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Bernhard Felderer,Stefan Homburg analysts’ work based on the results of the unsupervised approach. The newly developed process is able to supervise the decisions made by analysts thus improving the labeling process. The main goal of this chapter is to present a new, more deterministic labeling workflow with the ability to provide