KSR@ authors are typically scientific researchers and/or ideas developers just like our readers! so all of them are specialists in their field. We want our writers to share the tips and tricks they have researched and learned, and we will give you plenty of help along the way. If you have a research paper or idea to share, here is how to turn it into a KSR@ article.
Abstract As the number of data in various industries and government sectors is growing exponentially, the ‘7V’ concept of big data aims to create new value by indiscriminately collecting and
Abstract: Currently, communications and computer networks are an inevitable part of IT discussions. Whenever network and communications are involved, network security comes with it. According to the studies we have
Abstract Sorting is pivotal data analytics and becomes challenging with intensive computation on drastically growing data volume. Sorting on FPGA has shown superior throughput, but the limited in-system memory causes
Abstract Recently, wireless sensor networks (WSNs) have had many real-world applications; they have thus become one of the most interesting areas of research. The network lifetime is a major challenge
Abstract In this paper, we present an intelligent information kiosk called MIDAS (Multimodal Interactive-Dialogue Automaton for Self-service), including its hardware and software architecture, stages of deployment of speech recognition and
Abstract Current Conditional Functional Dependency (CFD) discovery algorithms always need a well-prepared training dataset. This condition makes them difficult to apply on large and low-quality datasets. To handle the volume
Abstract In order to analyze the big data of people’s livelihood appeal, this paper proposes a time series modeling and algorithm to decompose the time series {x(t)} of data into
Preface: big data?(BD ) Big data can be one of the terms exists no superset of the sayings and writings related to information technology, he said. If you have a query related
Abstract In this work the following three basic research questions are discussed: (1) can significant effects of modality efficiency and input performance on the selection of input modalities in multimodal
Abstract We present M3ER, a learning-based method for emotion recognition from multiple input modalities. Our approach combines cues from multiple co-occurring modalities (such as face, text, and speech) and also
