In this paper we present the OpenMP Analysis Toolkit (OAT), which uses Satisfiability
Modulo Theories (SMT) solver based symbolic analysis to detect data races and deadlocks …

With the development of deep learning and artificial intelligence, more and more research
apply neural networks to natural language processing tasks. However, while the majority of …

This work presents the Persona-AIML architecture for the creation of chatterbots in AIML
(Artificial Intelligence Markup Language) with personality. It is a flexible architecture that …

The growing development of Cloud Computing raised the need of making hardware
available “as a Service”. Reconfigurable hardware-like FPGA (Field Programmable Gate …

Deep learning has been an emerging field of machine learning during past decades.
However, the diversity and large scale data sizes have posed significant challenge to …

Neural networks have been widely used as a powerful representation in various research
domains, such as computer vision, natural language processing, and artificial intelligence …

The maximal information coefficient (MIC) has been proposed to discover relationships and
associations between pairs of variables. It poses significant challenges for bioinformatics …

Large-scale data is often represented as graphs in the field of modern cloud computing.
Graph processing attracts more and more attentions when utilizing the cloud computing …

This paper presents SmartMal—a novel service‐oriented behavioral malware detection
framework for vehicular and mobile devices. The highlight of SmartMal is to introduce …

Convolutional neural networks (CNNs) have been widely applied for image recognition, face
detection, and video analysis because of their ability to achieve accuracy close to or even …