@article {12301,
	title = {Deno: a decentralized, peer-to-peer object-replication system for weakly connected environments},
	journal = {Computers, IEEE Transactions on},
	volume = {52},
	year = {2003},
	month = {2003/07//},
	pages = {943 - 959},
	abstract = {This paper presents the design, implementation, and evaluation of the replication framework of Deno, a decentralized, peer-to-peer object-replication system targeted for weakly connected environments. Deno uses weighted voting for availability and pair-wise, epidemic information flow for flexibility. This combination allows the protocols to operate with less than full connectivity, to easily adapt to changes in group membership, and to make few assumptions about the underlying network topology. We present two versions of Deno{\textquoteright}s protocol that differ in the consistency levels they support. We also propose security extensions to handle a class of malicious actions that involve misrepresentation of protocol information. Deno has been implemented and runs on top of Linux and Win32 platforms. We use the Deno prototype to characterize the performance of the Deno protocols and extensions. Our study reveals several interesting results that provide fundamental insight into the benefits of decentralization and the mechanics of epidemic protocols.},
	keywords = {actions;, connected, consistency, data, data;, databases;, decentralized, Deno;, distributed, environments;, epidemic, group, levels;, Linux;, malicious, management;, membership;, network, object, object-replication, of, operating, peer-to-peer, protocols;, replicated, replication;, Security, security;, synchronisation;, system;, systems;, topology;, Unix;, voting;, weakly, weighted, Win32;},
	isbn = {0018-9340},
	doi = {10.1109/TC.2003.1214342},
	author = {Cetintemel,U. and Keleher,P. J and Bhattacharjee, Bobby and Franklin,M.J.}
}
@conference {13240,
	title = {Exemplar-based tracking and recognition of arm gestures},
	booktitle = {Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on},
	volume = {2},
	year = {2003},
	month = {2003/09//},
	pages = {656 - 661 Vol.2 - 656 - 661 Vol.2},
	abstract = {This paper presents a probabilistic exemplar-based framework for recognizing gestures. The approach is based on representing each gesture as a sequence of learned body poses. The gestures are recognized through a probabilistic framework for matching these body poses and for imposing temporal constrains between different poses. Matching individual poses to image data is performed using a probabilistic formulation for edge matching to obtain a likelihood measurement for each individual pose. The paper introduces a correspondence-free weighted matching scheme for edge templates that emphasize discriminating features in the matching. The weighting does not require establishing correspondences between the different pose models. The probabilistic framework also imposes temporal constrains between different pose through a learned hidden Markov model (HMM) of each gesture.},
	keywords = {arm, constrains;, correspondence-free, edge, exemplar-based, framework;, gesture, hidden, HMM;, image, logic;, Markov, MATCHING, matching;, model;, models;, probabilistic, recognition;, scheme;, segmentation;, temporal, tracking;, weighted},
	doi = {10.1109/ISPA.2003.1296358},
	author = {Elgammal,A. and Shet,V. and Yacoob,Yaser and Davis, Larry S.}
}
