The taxonomy is the most popular way for organizing a large volume of content. A taxonomy, which is typically a hierarchical representation of categories, provides a navigation structure for exploring and understanding the underlying corpus without sifting through a huge volume of documents. Creating and maintaining taxonomies with a large volume of documents remains a daunting task facing many enterprises. Content organization process typically involves four basic steps: (i) creating taxonomies, (ii) building classification models, (iii) populating taxonomies with documents, and (iv) deploying populated taxonomies in enterprise portals. Each step in the process may have unique requirements that determine what techniques and tools are suitable for the tasks. In this paper, we present a comprehensive suite of tools developed by Verity Inc. for accurately, collaboratively, and efficiently organizing enterprise content.
The use of smart-meters is proliferating, they are now being deployed without asking the obvious question: Do we really need each of them? Beyond the cost of smart-meters, there are overheads related to installation, wiring, etc. To formally tackle this question, we first define the notion of observability that one or more pieces of information (including that from smart-meters) enable. This notion allows us to compare two different deployments of sensors with respect to their information content and their usefulness. We then examine some commonly available information from which one can infer power consumption of devices in a given space. We show how we have applied this approach to systematically decide the optimal number and location of smart-meters to ensure observability of consumption by different parts of a building. General TermsSmart Energy
The performance analysis of a server application and the sizing of the hardware required to host it in a data center continue to be pressing issues today. With most servergrade computers now built with "frequency-scaled CPUs" and other such devices, it has become important to answer performance and sizing questions in the presence of such hardware. PowerPerfCenter is an application performance modeling tool that allows specification of devices whose operating speeds can change dynamically. It also estimates power usage by the machines in presence of such devices. Furthermore, it allows specification of a dynamic workload which is required to understand the impact of power management. We validated the performance metrics predicted by PowerPerfCenter against measured ones of an application deployed on a test-bed consisting of frequency-scaled CPUs, and found the match to be good. We also used PowerPerfCenter to show that power savings may not be significant if a device does not have different idle power consumption when configured with different operating speeds.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.