Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An ...

With this research we will investigate a novel machine learning approach to the prediction of location from received signal strength indicators (RSSI) values obtained from these transmitting access points. Indoor localization ...

The recent advent of using social media and search engine queries to detect and classifying events is an emerging area in data science. This study uses current Natural Language Processing (NLP) techniques for deep learning ...

Virtualized datacenters, the platform for supporting Cloud computing, allow diverse applications to share the underlying server resources. Due to the highly dynamic nature of Internet workloads, increasing complexity of ...

Recent studies have shown evidences regarding trauma recovery through web-based interventions. Currently, a widespread protocol is to assess trauma severity by answering the PTSD Checklist (PCL) questionnaire, which requires ...

The U.S Government has been the target of cyber-attacks from all over the world. Former President Obama accused the Russian government of leaking emails to WikiLeaks and declared that the U.S. might be forced to respond. ...

Effective detection of code clones is important for software maintenance. Code clones introduce difficulty in software maintenance and lead to bug propagation. Detection of duplicated bugs within a piece of software is ...

Abstract In this research we have used different machine learning algorithms to predict the performance of the elite athletes riding bicycles. The study of measuring the performance of the athletes is based on different ...

Recent advances in Natural Language Processing are finding ways to place an emphasis on the hierarchical nature of text instead of representing language as a flat sequence or unordered collection of words or letters. A ...