Over the last decade, several interconnected disruptions have happened in the large scale
distributed and parallel computing landscape. The volume of data currently produced by …

Traditional scalable clustering algorithms mainly deal with the clustering of linearly
separable data, but it is challenging to cluster the non-linear separable data efficiently in the …

Abstract Self-Organizing Neural Networks (SONNs) have a wide range of applications with
massive computational requirements that often need to be satisfied with optimized parallel …

Internet of things (IoT) allows various smart devices to get connected to anything, anywhere,
and at anytime. The ubiquitous nature of IoT devices generates huge volume of data called …

During the previous decades, intelligent identification of acronym and expansion pairs from
a large corpus has garnered considerable research attention, particularly in the fields of text …

In this paper, we analyzed large-scale face image retrieval method in cloud computing
environment. Based on Hadoop platform, a large-scale face retrieval method by using deep …

This paper proposes a solution to the deployment of a distributed map-reduce application; a
multi-cloud platform (DMRA-MCP) based on cloud broker architecture. The current …

This study investigated factors influencing the adoption of cloud-based electronic health
record/electronic medical record (EHR/EMR) systems by primary care providers (PCPs) …

В работе предлагается метод проектирования параллельных алгоритмов. Цель метода-
обеспечение точности описания алгоритмов без зависимости от языка …

Advances in Computing, Communication, Automation and Biomedical Technology aims to
bring together leading academic, scientists, researchers, industry representatives …