4,808 research outputs found
Study of singly heavy baryon lifetimes
We study the inclusive decay widths of singly heavy baryons with the improved
bag model in which the unwanted center-of-mass motion is removed. Additional
insight is gained by comparing the charmed and bottom baryons. We discuss the
running of the baryon matrix elements and compare the results with the
non-relativistic quark model (NRQM). While the calculated two-quark operator
elements are compatible with the literature, those of the four-quark ones
deviate largely. In particular, the heavy quark limit holds reasonably well in
the bag model for four-quark operator matrix elements but is badly broken in
the NRQM. We predict in
accordance with the current experimental value of
and compatible with obtained in the NRQM. We find an
excellent agreement between theory and experiment for the lifetimes of bottom
baryons. We confirm that could live longer than
after the dimension-7 four-quark operators are taken into account. We recommend
to measure some semileptonic inclusive branching fractions in the forthcoming
experiments to discern different approaches. For example, we obtain and in sharp contrast to and found in the NRQM.Comment: Accepted by JHEP, 39 pages, 4 figure
Supervised Collective Classification for Crowdsourcing
Crowdsourcing utilizes the wisdom of crowds for collective classification via
information (e.g., labels of an item) provided by labelers. Current
crowdsourcing algorithms are mainly unsupervised methods that are unaware of
the quality of crowdsourced data. In this paper, we propose a supervised
collective classification algorithm that aims to identify reliable labelers
from the training data (e.g., items with known labels). The reliability (i.e.,
weighting factor) of each labeler is determined via a saddle point algorithm.
The results on several crowdsourced data show that supervised methods can
achieve better classification accuracy than unsupervised methods, and our
proposed method outperforms other algorithms.Comment: to appear in IEEE Global Communications Conference (GLOBECOM)
Workshop on Networking and Collaboration Issues for the Internet of
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Multi-Hop Routing Mechanism for Reliable Sensor Computing
Current research on routing in wireless sensor computing concentrates on increasing the service lifetime, enabling scalability for large number of sensors and supporting fault tolerance for battery exhaustion and broken nodes. A sensor node is naturally exposed to various sources of unreliable communication channels and node failures. Sensor nodes have many failure modes, and each failure degrades the network performance. This work develops a novel mechanism, called Reliable Routing Mechanism (RRM), based on a hybrid cluster-based routing protocol to specify the best reliable routing path for sensor computing. Table-driven intra-cluster routing and on-demand inter-cluster routing are combined by changing the relationship between clusters for sensor computing. Applying a reliable routing mechanism in sensor computing can improve routing reliability, maintain low packet loss, minimize management overhead and save energy consumption. Simulation results indicate that the reliability of the proposed RRM mechanism is around 25% higher than that of the Dynamic Source Routing (DSR) and ad hoc On-demand Distance Vector routing (AODV) mechanisms
Congestion Control for Machine-Type Communications in LTE-A Networks
Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20~40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A
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