Weighted citation: An indicator of an article's prestige

We propose using the technique of weighted citation to measure an article's prestige. The technique allocates a different weight to each reference by taking into account the impact of citing journals and citation time intervals. Weighted citation captures prestige, whereas citation counts capture popularity. We compare the value variances for popularity and prestige for articles published in the Journal of the American Society for Information Science and Technology from 1998 to 2007, and find that the majority have comparable status.Comment: 17 pages, 6 figure

Entangler and analyzer for multiphoton maximally entangled states using weak nonlinearities

In the regime of weak nonlinearity we present two general feasible schemes. One is an entangler for generating any one of the $n$-photon Greenberger-Horne-Zeilinge (GHZ) states and Bell states. After the interactions with cross-Kerr nonlinear media, a phase gate followed by a measurement on the probe beam, and appropriate local operations via classical feed-forward, one can obtain the desired states in a nearly deterministic way. Another scheme is an analyzer for multiphoton maximally entangled states, which is taken as a further application of the above entangler. In this scheme, all of the $2^n$ $n$-photon GHZ states can, nearly deterministically, be discriminated. Furthermore, an efficient two-step nondestructive Bell-state analyzer is designed.Comment: 7 pages, 6 figure

Energy Efficiency and Emission Testing for Connected and Automated Vehicles Using Real-World Driving Data

By using the onboard sensing and external connectivity technology, connected and automated vehicles (CAV) could lead to improved energy efficiency, better routing, and lower traffic congestion. With the rapid development of the technology and adaptation of CAV, it is more critical to develop the universal evaluation method and the testing standard which could evaluate the impacts on energy consumption and environmental pollution of CAV fairly, especially under the various traffic conditions. In this paper, we proposed a new method and framework to evaluate the energy efficiency and emission of the vehicle based on the unsupervised learning methods. Both the real-world driving data of the evaluated vehicle and the large naturalistic driving dataset are used to perform the driving primitive analysis and coupling. Then the linear weighted estimation method could be used to calculate the testing result of the evaluated vehicle. The results show that this method can successfully identify the typical driving primitives. The couples of the driving primitives from the evaluated vehicle and the typical driving primitives from the large real-world driving dataset coincide with each other very well. This new method could enhance the standard development of the energy efficiency and emission testing of CAV and other off-cycle credits

Rumba : a Python framework for automating large-scale recursive internet experiments on GENI and FIRE+

It is not easy to design and run Convolutional Neural Networks (CNNs) due to: 1) finding the optimal number of filters (i.e., the width) at each layer is tricky, given an architecture; and 2) the computational intensity of CNNs impedes the deployment on computationally limited devices. Oracle Pruning is designed to remove the unimportant filters from a well-trained CNN, which estimates the filters’ importance by ablating them in turn and evaluating the model, thus delivers high accuracy but suffers from intolerable time complexity, and requires a given resulting width but cannot automatically find it. To address these problems, we propose Approximated Oracle Filter Pruning (AOFP), which keeps searching for the least important filters in a binary search manner, makes pruning attempts by masking out filters randomly, accumulates the resulting errors, and finetunes the model via a multi-path framework. As AOFP enables simultaneous pruning on multiple layers, we can prune an existing very deep CNN with acceptable time cost, negligible accuracy drop, and no heuristic knowledge, or re-design a model which exerts higher accuracy and faster inferenc

Nucleon-antinucleon Interaction from the Modified Skyrme Model

We calculate the static nucleon-antinucleon interaction potential from the modified Skyrme model with additional $B^{\mu}B_{\mu}$ term using the product ansatz. The static properties of single baryon are improved in the modified Skyrme model. State mixing is taken into account by perturbation theory, which substantially increases the strength of the central attraction. We obtain a long and mid range potential which is in qualitative agreement with some phenomenological potentials.Comment: 21 pages, 7 figur