In today’s era of big data, with the introduction of high resolution systems, remote sensing imagery is one of the fastest growing fields resulting in a rapid increase in volume of data being generated day by day. To handle such massive volumes of data, a high processing speed has become an indispensable requirement. This is possible with the help of big data platforms such as Hadoop. Clusterin...

Our goal in this paper is to establish a means for a dialogue platform to be able to cope with open domains considering the possible interaction between the embodied agent and humans. To this end we present an algorithm capable of processing natural language utterances and validate them against knowledge structures of an intelligent agent’s mind. Our algorithm leverages dialogue techniques in o...

Last time, we introduced the task of hierarchical clustering, in which we aim to produce nested clusterings that reflect the similarity between clusters. This contrasts sharply with our former discussion of “flat” or structureless clustering methods like k-means which do not model relationships between clusters. In this lecture, we will continue our discussion of the standard model-free approac...

Purpose An in-depth literature review was undertaken to uncover (1) what are described as the desired outcomes for 20 minute neighbourhoods (20MNs) – normatively based ends which planners, architects and decision-makers want 20MNs achieve; (2) means (the mechanisms, levers, triggers causal factors) that have be correctly assembled lined up operate intended (3), in order avoid naive environmenta...

The trace consists of cell information of about 29 days spanning across 700k jobs. This paper deals with statistical analysis of this cluster trace. Since the size of trace is very large, Hive which is a Hadoop distributed file system (HDFS) based platform for querying and analysis of Big data, has been used. Hive was accessed through its Beeswax interface. The data was imported into HDFS throu...