monitoring (NILM). The datasets used for NILM research generally contain real power readings, with the data often being too coarse for more sophisticated analysis algorithms, and often covering too short a time period. We present the Almanac of Minutely Power dataset (AMPds) for load disaggregation research

: friendship links and community membership on LiveJournal, and co-authorship and conference publications in DBLP. Both of these datasets provide explicit user-defined communities, where conferences serve as proxies for communities in DBLP. We study how the evolution of these communities relates to properties

stage by gradually pruning the support value spectrum and optimizing the hyperparameters during the sparse approximation procedure. In this paper, twenty public domain benchmark datasets are used to evaluate the test set performance of LS-SVM classifiers with linear, polynomial and radial basis function

that applies priority search on hierarchical k-means trees, which we have found to provide the best known performance on many datasets. After testing a range of alternatives, we have found that multiple randomized k-d trees provide the best performance for other datasets. We are releasing public domain code

. We present a new technique, called "backscatter analysis", that provides an estimate of worldwide denial-of-service activity. We use this approach on three week-long datasets to assess the number, duration and focus of attacks, and to characterize their behavior. During this period, we

Abstract. The world is moving from a state where there is paucity of data to one of surfeit. These data, and datasets, are normally in different datastores and of different formats. Connecting these datasets together will increase their value and help discover interesting relationships amongst them

This Convention paper was selected based on a submitted abstract and 750-word precis that have been peer reviewed by at least two qualified anonymous reviewers. The complete manuscript was not peer reviewed. This convention paper has been reproduced from the author’s advance manuscript without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for the contents. Additional papers may be obtained by sending request

publicly available for the energy and sustainability research community. In this paper we present a freely available dataset containing power usage and related information from 50 homes. Here we describe our dataset, the hardware and software setups used when collecting the data and how others can access

Variability (HRV), Skin Conductance Level (SCL), and frequency of Electrodermal Responses (EDR). The dataset will be released for public use in both driver monitoring and data mining research.

com-paratively with retinal vessels. To enable replication of our results, we use the public dataset for retinal tortuosity, RET-TORT. We find that (1) the tortuosity density index offers good performance overall, but is not always the best performer; (2) curvature-based methods are the best if high