Reversible Embedding to Covers Full of Boundaries

In reversible data embedding, to avoid overflow and underflow problem, before data embedding, boundary pixels are recorded as side information, which may be losslessly compressed. The existing algorithms often assume that a natural image has little boundary pixels so that the size of side information is small. Accordingly, a relatively high pure payload could be achieved. However, there actually may exist a lot of boundary pixels in a natural image, implying that, the size of side information could be very large. Therefore, when to directly use the existing algorithms, the pure embedding capacity may be not sufficient. In order to address this problem, in this paper, we present a new and efficient framework to reversible data embedding in images that have lots of boundary pixels. The core idea is to losslessly preprocess boundary pixels so that it can significantly reduce the side information. Experimental results have shown the superiority and applicability of our work

Brueckner-Hartree-Fock and its renormalized calculations for finite nuclei

We have performed self-consistent Brueckner-Hartree-Fock (BHF) and its renormalized theory to the structure calculations of finite nuclei. The $G$-matrix is calculated within the BHF basis, and the exact Pauli exclusion operator is determined by the BHF spectrum. Self-consistent occupation probabilities are included in the renormalized Brueckner-Hartree-Fock (RBHF). Various systematics and convergences are studies. Good results are obtained for the ground-state energy and radius. RBHF can give a more reasonable single-particle spectrum and radius. We present a first benchmark calculation with other {\it ab initio} methods using the same effective Hamiltonian. We find that the BHF and RBHF results are in good agreement with other $\it{ab}$ $\it{initio}$ methods

Spin Polarisability of the Nucleon in the Heavy Baryon Effective Field Theory

We have constructed a heavy baryon effective field theory with photon as an external field in accordance with the symmetry requirements similar to the heavy quark effective field theory. By treating the heavy baryon and anti-baryon equally on the same footing in the effective field theory, we have calculated the spin polarisabilities $\gamma_i, i=1...4$ of the nucleon at third order and at fourth-order of the spin-dependent Compton scattering. At leading order (LO), our results agree with the corresponding results of the heavy baryon chiral perturbation theory, at the next-to-leading order(NLO) the results show a large correction to the ones in the heavy baryon chiral perturbation theory due to baryon-antibaryon coupling terms. The low energy theorem is satisfied both at LO and at NLO. The contributions arising from the heavy baryon-antibaryon vertex were found to be significant and the results of the polarisabilities obtained from our theory is much closer to the experimental data.Comment: 21pages, title changed, minimal correction

Heavy quarkonium 2S states in light-front quark model

We study the charmonium 2S states $\psi'$ and $\eta_c'$, and the bottomonium 2S states $\Upsilon'$ and $\eta_b'$, using the light-front quark model and the 2S state wave function of harmonic oscillator as the approximation of the 2S quarkonium wave function. The decay constants, transition form factors and masses of these mesons are calculated and compared with experimental data. Predictions of quantities such as Br$(\psi' \to \gamma \eta_c')$ are made. The 2S wave function may help us learn more about the structure of these heavy quarkonia.Comment: 5 latex pages, final version for journal publicatio

The IPIN 2019 Indoor Localisation Competition - Description and Results

IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks

An Adaptive Human Activity-Aided Hand-Held Smartphone-Based Pedestrian Dead Reckoning Positioning System

Pedestrian dead reckoning (PDR), enabled by smartphones’ embedded inertial sensors, is widely applied as a type of indoor positioning system (IPS). However, traditional PDR faces two challenges to improve its accuracy: lack of robustness for different PDR-related human activities and positioning error accumulation over elapsed time. To cope with these issues, we propose a novel adaptive human activity-aided PDR (HAA-PDR) IPS that consists of two main parts, human activity recognition (HAR) and PDR optimization. (1) For HAR, eight different locomotion-related activities are divided into two classes: steady-heading activities (ascending/descending stairs, stationary, normal walking, stationary stepping, and lateral walking) and non-steady-heading activities (door opening and turning). A hierarchical combination of a support vector machine (SVM) and decision tree (DT) is used to recognize steady-heading activities. An autoencoder-based deep neural network (DNN) and a heading range-based method to recognize door opening and turning, respectively. The overall HAR accuracy is over 98.44%. (2) For optimization methods, a process automatically sets the parameters of the PDR differently for different activities to enhance step counting and step length estimation. Furthermore, a method of trajectory optimization mitigates PDR error accumulation utilizing the non-steady-heading activities. We divided the trajectory into small segments and reconstructed it after targeted optimization of each segment. Our method does not use any a priori knowledge of the building layout, plan, or map. Finally, the mean positioning error of our HAA-PDR in a multilevel building is 1.79 m, which is a significant improvement in accuracy compared with a baseline state-of-the-art PDR system

Finite dimensional integrable Hamiltonian systems associated with DSI equation by Bargmann constraints

The Davey-Stewartson I equation is a typical integrable equation in 2+1 dimensions. Its Lax system being essentially in 1+1 dimensional form has been found through nonlinearization from 2+1 dimensions to 1+1 dimensions. In the present paper, this essentially 1+1 dimensional Lax system is further nonlinearized into 1+0 dimensional Hamiltonian systems by taking the Bargmann constraints. It is shown that the resulting 1+0 dimensional Hamiltonian systems are completely integrable in Liouville sense by finding a full set of integrals of motion and proving their functional independence.Comment: 10 pages, in LaTeX, to be published in J. Phys. Soc. Jpn. 70 (2001