An algorithm using YOLOv4 and DeepSORT for tracking vehicle speed on highway

Currently, expressways are increasingly developed and expanded. Several highways of Vietnam allow vehicles to travel up to 120 kilometers per hour helping to transport goods quickly and bring a lot of socio-economic benefits. Vehicle monitoring plays an important role in reducing traffic accidents helping to handle violations.The paper proposes a model to identify and monitor car speed on highways. The proposal method uses YOLOv4 combining with DeepSORT for vehicle identification and tracking. We then calculate the speed of car based on video recording and sending back from highway. The execution context is highway where vehicles move very fast. The results show that system meets set requirements with over 90% accuracy and execution times for up to 70 frames per second that is suitable for real systems

Proposal of Image generation model using cGANs for sketching faces

The transition from sketches to realistic images of human faces has an important application in criminal investigation science to find criminals as depicted by witnesses. However, due to the difference between the sketch image and the real face image in terms of image detail and color, it is challenging and takes time to transform from hand-drawn sketches to actual faces. To solve this problem, we propose an image generation model using the conditional generative adversarial network with autoencoder (cGANs-AE) model to generate synthetic samples for variable length and multi-feature sequence datasets. The goal of the model is to learn how to encode a dataset that reduces its vector size. Using a vector with reducing the dimension, the autoencoder will have to recreate the image similar to the original image. The autoencoder aims to produce output as input and focus only on the essential features. Raw sketches over the cGANS create realistic images that quickly and easily make the sketch images raw images. The results show that the model achieves high accuracy of up to 75%, and PSNR is 25.5 dB that is potentially applicable for practice with only 606 face images. The performance of our proposed architecture is compared with other solutions, and the results show that our proposal obtains competitive performance in terms of output quality (25.5 dB) and efficiency (above 75%)

PROPOSING MODEL OF HANDLING LANGUAGE FOR SMART HOME SYSTEM CONTROLLED BY VOICE

Voice interaction control is a useful solution for smart homes. Now it helps bring the house closer to people. In recent years, many smart home-based voice control solutions have been introduced (for example: Google Assistant, Alexa Amazon etc.). However, most of these solutions do not really serve Vietnamese people. In this paper, we study and develop Vietnamese language processing model to apply to smart home system. Specifically, we propose language processing methods and create databases for smart homes. Our main contribution of the paper is the Vietnamese language processing database for smart-home system

Topological Lifshitz phase transition in effective model of QCD with chiral symmetry non-restoration

The topological Lifshitz phase transition is studied systematically within an effective model of QCD, in which the chiral symmetry, broken at zero temperature, is not restored at high temperature and/or baryon chemical potential. It is found that during phase transition the quark system undergoes a first-order transition from low density fully-gapped state to high density state with Fermi sphere which is protected by momentum-space topology. The Lifshitz phase diagram in the plane of temperature and baryon chemical potential is established. The critical behaviors of various equations of state are determined.Comment: 8 pages, 10 figure

On the holographic phase transitions at finite topological charge

Exploring the significant impacts of topological charge on the holographic phase transitions and conductivity we start from an Einstein - Maxwell system coupled with a charged scalar field in Anti - de Sitter spacetime. In our set up, the corresponding black hole (BH) is chosen to be the topological AdS one where the pressure is identified with the cosmological constant. Our numerical computation shows that the process of condensation is favored at finite topological charge and, in particular, the pressure variation in the bulk generates a mechanism for changing the order of phase transitions in the boundary: the second order phase transitions occur at pressures higher than the critical pressure of the phase transition from small to large BHs while they become first order at lower pressures. This property is confirmed with the aid of holographic free energy. Finally, the frequency dependent conductivity exhibits a gap when the phase transition is second order and when the phase transition becomes first order this gap is either reduced or totally lost.Comment: 8 pages, 9 figure

Investigating Effects of Teacher’s Using Authentic Texts on Cognitive Reading Engagement of Vietnamese EFL Students

The study examines the effects of teacher’s using authentic texts on EFL students’ cognitive reading engagement related to four variables including (i) reading comprehension, (ii) oral response to reading, (iii) reaction paragraph, and (iv) students’ perceptions of learning to read. Participants included 52 Vietnamese undergraduate students of EFL pre-intermediate level. The data of the study were collected through reading tests for the first three variables and a 32- item questionnaire for the fourth variable. Results revealed that students in the experimental condition achieved significantly better understanding of reading comprehension after the intervention course. In terms of reflection after reading and creating a reaction paragraph, the holistic quality of oral response and the reaction paragraph was significantly improved for both groups from a peer rating. However, students in the experimental group showed a more dramatic increase. Moreover, the findings of the questionnaire showed that students in the intervention course achieved a more positive perception of their learning to read

Vietnamese Text Classification Algorithm using Long Short Term Memory and Word2Vec

In the context of the ongoing forth industrial revolution and fast computer science development the amount of textual information becomes huge. So, prior to applying the seemingly appropriate methodologies and techniques to the above data processing their nature and characteristics should be thoroughly analyzed and understood. At that, automatic text processing incorporated in the existing systems may facilitate many procedures. So far, text classification is one of the basic applications to natural language processing accounting for such factors as emotions’ analysis, subject labeling etc. In particular, the existing advancements in deep learning networks demonstrate that the proposed methods may fit the documents’ classifying, since they possess certain extra efficiency; for instance, they appeared to be effective for classifying texts in English. The thorough study revealed that practically no research effort was put into an expertise of the documents in Vietnamese language. In the scope of our study, there is not much research for documents in Vietnamese. The development of deep learning models for document classification has demonstrated certain improvements for texts in Vietnamese. Therefore, the use of long short term memory network with Word2vec is proposed to classify text that improves both performance and accuracy. The here developed approach when compared with other traditional methods demonstrated somewhat better results at classifying texts in Vietnamese language. The evaluation made over datasets in Vietnamese shows an accuracy of over 90%; also the proposed approach looks quite promising for real applications

Phase Structure of Linear Sigma Model without Neutrality Constraint (I)

The pion condensation and chiral phase transition are studied within the linear sigma model with constituent quarks (LSMq). In the chiral limit the pion condensation is always the first-order phase transition and the phase diagrams of the pion condensate are established respectively in the $(\mu,T) , (\mu_I,T)$ and $(\mu_I,\mu)$-planes, here $T, \mu$ and $\mu_I$ are temperature, baryon chemical and isospin chemical potentials. In the physical world, where the chiral symmetry is explicitly broken we investigate systematically the phase structure of pion and chiral condensates in the $(T-\mu-\mu_I)$-space. The obtained results are mainly compared to the existing data derived from the lattice QCD (LQCD) and the Polyakov-loop extended Nambu-Jona-Lasinio (PNJL) model

On the loop expansion of the effective action

Based on the DeWitt formula the loop expansion of the effective action is easily established. Extending to the system with finite density we develop the in-medium DeWitt formula, which is the starting point for setting up loop expansion of the in-medium effective action

Phase structure of linear sigma model with neutrality constraint (II)

The phase structure of the linear sigma model with constituent quarks and the electric neutrality is systematically studied in the mean field theory. It results that in the chiral limit, as function of $T$ and chemical potential \\mu\, the pion condensate undergoes a first-order phase transition. In the physical world, the phase diagram of chiral condensate exhibits a first-order phase transition, which ends at a critical end point (CEP) for $\alpha 0.3$, where $\alpha$ is the fraction of $\pi^+$  contribution to the condensate