Download JAR files tagged by reliable with all dependencies

ToroDB is an open source project that turns your RDBMS into a MongoDB-compatible server, supporting the MongoDB query API and MongoDB's replication, but storing your data into a reliable and trusted ACID database. ToroDB currently supports PostgreSQL as a backend, but others will be added in the future. ToroDB natively implements the MongoDB protocol, so you can use it with MongoDB tools and drivers, and features a document-to-relational mapping algorithm that transforms the JSON documents into relational tables. ToroDB also offers a native SQL layer and automatic data normalization and partitioning based on JSON documents' implicit schema.

Little Nanny is new type of Application to keep parents and their young children in touch. The idea is to reuse any old Smartphone (Android or iOS) as a high precision tracking device. After speaking with other parents, it was clear that there was a need for a really reliable App to help give children the freedom they need to explore and discover, while staying in touch with those who matter most. Little Nanny has a simple mission – to help kids be kids again, while giving parents an amazing new window into their children’s lives.

RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. If you wish to cite RuSH in a publication, please use: Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587. The full text can be found at: https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616 This version allows defining section scopes for sentence segmentation.

RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. If you wish to cite RuSH in a publication, please use: Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587. The full text can be found at: https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616