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private-ethereum-blockchain

react-fullstack-graphql

Starter projects for fullstack applications based on React & GraphQL.

react-say

A React component that synthesis text into speech using Web Speech API.

reference-apps

Spark reference applications

s3-lambda-ffmpeg-aac-wav-to-mp3-s3

shopizer-shop-reactjs

slate-find-replace

Find and replace functionality for SlateJS

sparkscalacourse

Learning Spark with Scala

speech-to-text

REST client for Microsoft speech-to-text API

speech_to_text_api_v30

speechtotextapiv30

spring-cloud-netflix

Integration with Netflix OSS components

spring-cloud-stream

Framework for building Event-Driven Microservices

spring-cloud-stream-binder-kafka

Spring Cloud Stream binders for Apache Kafka and Kafka Streams

spring-cloud-stream-samples

Samples for Spring Cloud Stream

spring-jwt-done-right

Example of integration of Spring and jjwt without boilerplate code. Do it right!

springboot-elk

Demo springboot + elastic search + kibana

springboot-kafka-avro

springboot-kafka-avro

stellar-docker-testnet

stellar-sbt

stellar-sbt-demo

add account component

stellar-test

stream-applications

Functions and Spring Cloud Stream Applications for data driven microservices

stream-live-system

:red_circle: An example of a live broadcast system using microservice concepts and architected with docker.

subpost

WordPress: Plugin: Subordinate Post Type Helpers

sust-msc-semntiment_analysis-semantically

This research proposes a new framework for analyzing Arabic opinions and measuring the sentiment analysis for Arabic contents using semantic approach and text analysis. The proposed framework detects the Arabic opinion orientation using Arabic ontology and Part Of Speech Tag ‘POS’ for Arabic words. The framework consisted of five components. These are; the Arabic Part Of Speech “POS” tagger which was used to assign the correct tag for every word in the opinion, the Arabic Ontology Classifier to query RDF Ontology using ontology engineering; the SPARQL language to extract the main concepts, the third component is Arabic Sentiment Lexicon which was used as the Arabic dictionary; and the final components are the Counter and Report components which perform the calculation and display the final results and reports. A framework was designed using advance integration technologies such as Stanford POS tagger, Stanford Ontology protégé, and Jean framework from Apache which was used to integrate the Ontology. The framework was tested against Arabic comments using the Arabic movie ontology, and the results showed that the framework was successfully able to detect and classify the pilot comments written in Arabic language and measure them against the five star rating system. The results also agreed well with the calculated stars which was entered by the opinion holders.

sustasa

Sudan univerisity for science and technology Arabic Sentiment Analysis using Ontologies

t

tensorflow_object_detector

Tensorflow Object Detector

tus-java-server

Library to receive tus v1.0.0 file uploads in a Java server environment