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"Internet-based speech recognition applications prefer using TCP to ensure reliable speech data delivery. TCP-based speech recognition can be designed to push recognition updates on the fly, without waiting for all speech data to fully arrive at the server. We propose an ns-3-based emulation platform to evaluate the performance of TCP-based speech recognition. The server and the client are connected to the simulated network using a tap bridge. The real-time performance of full-duplex speech recognition is measured based on data size, loss rate, and propagation delay. For all our data samples, the application exhibits good performance when the propagation delay is 120 seconds and the loss rate is less than 0.3%, as well as when the propagation delay is 50 seconds and the loss rate is less than 0.5%."

"Penelitian ini mengoptimasi pengelolaan data domain masif pada Dashboard NetPro untuk mengatasi tantangan pemblokiran situs berbahaya secara efisien. Solusi yang dikembangkan menerapkan metode chunking dan teknologi WebSocket untuk mencapai efisiensi proses dan interaksi real-time. Hasil pengujian membuktikan keberhasilan pendekatan ini, di mana dengan pemilihan ukuran chunk optimal sebesar 10.000 data, sebuah nilai yang menyeimbangkan antara efisiensi pemrosesan batch dan kontrol penggunaan memori, sistem mampu menangani hingga sepuluh juta data dan memprosesnya lebih dari 9.000 kali lebih cepat dibandingkan metode input satuan. Sistem berbasis Node.js dan PostgreSQL ini berhasil mengubah proses manajemen data yang tidak efisien menjadi alur kerja yang cepat, andal, dan responsif.

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This research optimizes massive domain data management on the NetPro Dashboard to efficiently address the challenge of blocking malicious websites. The developed solution implements the chunking method and WebSocket technology to achieve processing efficiency and real-time interaction. Testing proves the success of this approach, where with an optimal chunk size of 10,000 data entries, a value chosen to balance batch processing efficiency with memory usage control, the system can handle up to ten million entries and process them over 9,000 times faster than conventional single-entry input methods. This Node.js and PostgreSQL-based system successfully transforms an inefficient data management process into a fast, reliable, and responsive workflow."