An Efficient Approach for Polyps Detection in Endoscopic Videos Based on Faster R-CNN

Polyp has long been considered as one of the major etiologies to colorectal cancer which is a fatal disease around the world, thus early detection and recognition of polyps plays a crucial role in clinical routines. Accurate diagnoses of polyps through endoscopes operated by physicians becomes a challenging task not only due to the varying expertise of physicians, but also the inherent nature of endoscopic inspections. To facilitate this process, computer-aid techniques that emphasize fully-conventional image processing and novel machine learning enhanced approaches have been dedicatedly designed for polyp detection in endoscopic videos or images. Among all proposed algorithms, deep learning based methods take the lead in terms of multiple metrics in evolutions for algorithmic performance. In this work, a highly effective model, namely the faster region-based convolutional neural network (Faster R-CNN) is implemented for polyp detection. In comparison with the reported results of the state-of-the-art approaches on polyps detection, extensive experiments demonstrate that the Faster R-CNN achieves very competing results, and it is an efficient approach for clinical practice.Comment: 6 pages, 10 figures,2018 International Conference on Pattern Recognitio

HyCell: Enabling GREEN Base Station Operations in Software-Defined Radio Access Networks

The radio access networks (RANs) need to support massive and diverse data traffic with limited spectrum and energy. To cope with this challenge, software-defined radio access network (SDRAN) architectures have been proposed to renovate the RANs. However, current researches lack the design and evaluation of network protocols. In this paper, we address this problem by presenting the protocol design and evaluation of hyper-cellular networks (HyCell), an SDRAN framework making base station (BS) operations globally resource-optimized and energy-efficient (GREEN). Specifically, we first propose a separation scheme to realize the decoupled air interface in HyCell. Then we design a BS dispatching protocol which determines and assigns the optimal BS for serving mobile users, and a BS sleeping protocol to improve the network energy efficiency. Finally, we evaluate the proposed design in our HyCell testbed. Our evaluation validates the feasibility of the proposed separation scheme, demonstrates the effectiveness of BS dispatching, and shows great potential in energy saving through BS sleeping control.Comment: 6 pages, 4 figures, accepted by IEEE ICC 2015 Workshop on Next Generation Green IC

Kuramoto dilemma alleviated by optimizing connectivity and rationality

Recently, Antonioni and Cardillo proposed a coevolutionary model based on the intertwining of oscillator synchronization and evolutionary game theory [Phys. Rev. Lett. \textbf{118}, 238301 (2017)], in which each Kuramoto oscillator can decide whether to interact-or not-with its neighbors, and all oscillators can receive some benefits from the local synchronization but those who choose to interact must pay a cost. Oscillators are allowed to update their strategies according to payoff difference, wherein the strategy of an oscillator who has obtained higher payoff is more likely to be followed. Utilizing this coevolutionary model, we find that the global synchronization level reaches the highest level when the average degree of the underlying interaction network is moderate. We also study how synchronization is affected by the individual rationality in choosing strategy

Amending coherence-breaking channels via unitary operations

The coherence-breaking channels play a significant role in quantum information theory. We study the coherence-breaking channels and give a method to amend the coherence-breaking channels by applying unitary operations. For given incoherent channel $\Phi$, we give necessary and sufficient conditions for the channel to be a coherence-breaking channel and amend it via unitary operations. For qubit incoherent channels $\Phi$ that are not coherence-breaking ones, we consider the mapping $\Phi\circ\Phi$ and present the conditions for coherence-breaking and channel amendment as well.Comment: 8 page

Theory of Network Contractor Dynamics for Exploring Thermodynamic Properties of Two-dimensional Quantum Lattice Models

Based on the tensor network state representation, we develop a nonlinear dynamic theory coined as network contractor dynamics (NCD) to explore the thermodynamic properties of two-dimensional quantum lattice models. By invoking the rank-$1$ decomposition in the multi-linear algebra, the NCD scheme makes the contraction of the tensor network of the partition function be realized through a contraction of a local tensor cluster with vectors on its boundary. An imaginary-time-sweep algorithm for implementation of the NCD method is proposed for practical numerical simulations. We benchmark the NCD scheme on the square Ising model, which shows a great accuracy. Besides, the results on the spin-1/2 Heisenberg antiferromagnet on honeycomb lattice are disclosed in good agreement with the quantum Monte Carlo calculations. The quasi-entanglement entropy $S$, Lyapunov exponent $I^{lya}$ and loop character $I^{loop}$ are introduced within the dynamic scheme, which are found to display the ``nonlocality" near the critical point, and can be applied to determine the thermodynamic phase transitions of both classical and quantum systems.Comment: 8 pages, 9 figure