SU(3)_LxU(1)_N Model for Right-Handed Neutrino Neutral Currents

A model based on the \mbox{SU(3)}_L\otimes \mbox{U(1)}_N gauge group, in which neutrinos have right-handed neutral currents is considered. We argue that in order to have a result consistent with low-energy one, the right-handed neutrino component must be treated as correction instead of an equivalent spin state.Comment: 6 pages, Latex, no figures, Accepted for publication in Phys. Rev.

The Higgs Sector of the Minimal 3 3 1 Model Revisited

The mass spectrum and the eigenstates of the Higgs sector of the minimal 3 3 1 model are revisited in detail. There are discrepancies between our results and previous results by another author.Comment: 20 pages, latex, two figures. One note and one reference are adde

Outage probability analysis of EH relay-assisted non-orthogonal multiple access (NOMA) systems over Block Rayleigh Fading Channel

Non-orthogonal multiple access (NOMA) has been identified as a promising multiple access technique for the fifth generation (5G) mobile networks due to its superior spectral efficiency. In this paper, we propose and investigate a Non-Orthogonal Multiple Access (NOMA) of energy harvesting (EH) relay assisted system over Block Rayleigh Fading Channel. In order to evaluate the performance of the proposed system, the integral expression of the outage probability is analyzed and derived. Numerical results confirm that our derived analytical results match well with the Monte Carlo simulations in connection with all possible system parameter

Half-duplex power beacon-assisted energy harvesting relaying networks: system performance analysis

In this work, the half-duplex (HF) power beacon-assisted (PB) energy harvesting (EH) relaying network, which consists of a source (S), Relay (R), destination (D) and a power beacon (PB) are introduced and investigated. Firstly, the analytical expressions of the system performance in term of outage probability (OP) and the system throughput (ST) are analyzed and derived in both amplify-and-forward (AF) and decode-and-forward (DF) modes. After that, we verify the correctness of the analytical analysis by using Monte-Carlo simulation in connection with the primary system parameters. From the numerical results, we can see that all the analytical and the simulation results are matched well with each other

A Vietnamese Handwritten Text Recognition Pipeline for Tetanus Medical Records

Machine learning techniques are successful for optical character recognition tasks, especially in recognizing handwriting. However, recognizing Vietnamese handwriting is challenging with the presence of extra six distinctive tonal symbols and vowels. Such a challenge is amplified given the handwriting of health workers in an emergency care setting, where staff is under constant pressure to record the well-being of patients. In this study, we aim to digitize the handwriting of Vietnamese health workers. We develop a complete handwritten text recognition pipeline that receives scanned documents, detects, and enhances the handwriting text areas of interest, transcribes the images into computer text, and finally auto-corrects invalid words and terms to achieve high accuracy. From experiments with medical documents written by 30 doctors and nurses from the Tetanus Emergency Care unit at the Hospital for Tropical Diseases, we obtain promising results of 2% and 12% for Character Error Rate and Word Error Rate, respectively

Label driven Knowledge Distillation for Federated Learning with non-IID Data

In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an environment with heterogeneous data. Realizing the first problem, we aim to design a novel FL framework named Full-stack FL (F2L). More specifically, F2L utilizes a hierarchical network architecture, making extending the FL network accessible without reconstructing the whole network system. Moreover, leveraging the advantages of hierarchical network design, we propose a new label-driven knowledge distillation (LKD) technique at the global server to address the second problem. As opposed to current knowledge distillation techniques, LKD is capable of training a student model, which consists of good knowledge from all teachers' models. Therefore, our proposed algorithm can effectively extract the knowledge of the regions' data distribution (i.e., the regional aggregated models) to reduce the divergence between clients' models when operating under the FL system with non-independent identically distributed data. Extensive experiment results reveal that: (i) our F2L method can significantly improve the overall FL efficiency in all global distillations, and (ii) F2L rapidly achieves convergence as global distillation stages occur instead of increasing on each communication cycle.Comment: 28 pages, 5 figures, 10 table

OmniShare : Encrypted Cloud Storage for the Multi-Device Era

Two attractive features of cloud storage services are (1) the automatic synchronization of files between multiple devices and (2) the possibility of sharing files with other users. However, many users are concerned about the security and privacy of data stored in the cloud. Client-side encryption is an effective safeguard, but it requires all client devices to have the decryption key. Current solutions derive these keys from user-chosen passwords, which are easily guessed. We present OmniShare, the first scheme to combine strong client-side encryption with intuitive key distribution mechanisms to enable access from multiple client devices and sharing between users. OmniShare uses a novel combination of out-of-band channels (including QR codes and ultrasonic communication), as well as the cloud storage service itself, to authenticate new devices. We describe the design and implementation of OmniShare and explain how we evaluated its security (using formal methods), its performance (benchmarks), and its usability (cognitive walkthrough).Two attractive features of cloud storage services are (1) the automatic synchronization of files between multiple devices and (2) the possibility of sharing files with other users. However, many users are concerned about the security and privacy of data stored in the cloud. Client-side encryption is an effective safeguard, but it requires all client devices to have the decryption key. Current solutions derive these keys from user-chosen passwords, which are easily guessed. We present OmniShare, the first scheme to combine strong client-side encryption with intuitive key distribution mechanisms to enable access from multiple client devices and sharing between users. OmniShare uses a novel combination of out-of-band channels (including QR codes and ultrasonic communication), as well as the cloud storage service itself, to authenticate new devices. We describe the design and implementation of OmniShare and explain how we evaluated its security (using formal methods), its performance (benchmarks), and its usability (cognitive walkthrough).Peer reviewe

The 331 model with right-handed neutrinos

We explore some more consequences of the $SU(3)_L\otimes U(1)_N$ electroweak model with right-handed neutrinos. By introducing the $Z - Z'$ mixing angle $\phi$, the {\it exact} physical eigenstates for neutral gauge bosons are obtained. Because of the mixing, there is a modification to the $Z^1$ coupling proportional to $\sin\phi$. The data from the $Z$-decay allows us to fix the limit for $\phi$ as $-0.0021 \leq \phi \leq 0.000132$. >From the neutrino neutral current scatterings, we estimate a bound for the new neutral gauge boson $Z^2$ mass in the range 300 GeV, and from symmetry-breaking hierarchy a bound for the new charged and neutral (non-Hermitian) gauge bosons $Y^{\pm}, X^o$ are obtained.Comment: Slight changes in section 5, Latex, 16 page