Improving bottleneck features for Vietnamese large vocabulary continuous speech recognition system using deep neural networks

In this paper, the pre-training method based on denoising auto-encoder is investigated and proved to be good models for initializing bottleneck networks of Vietnamese speech recognition system that result in better recognition performance compared to base bottleneck features reported previously. The experiments are carried out on the dataset containing speeches on Voice of Vietnam channel (VOV). The results show that the DBNF extraction for Vietnamese recognition decreases relative word error rate by 14 % and 39 % compared to the base bottleneck features and MFCC baseline, respectively

Study on outage performance gap of two destinations on CR-NOMA network

Non-orthogonal multiple access (NOMA) and cognitive radio (CR) are promising for solving the severe spectral scarcity problem encountered by the next generation of wireless communication systems. This study aims to improve spectral efficiency at two secondary destinations by investigating a CR-NOMA network under situation of the perfect successive interference cancellation (SIC). We also derive the exact outage probability for secondary users. Furthermore, an approximate computation method is applied to indicate more insights. It is confirmed that the performance achieved together with performance gap among two users can be obtained due to different power allocation factors assigned to users

Enabling Power Beacons and Wireless Power Transfers for Non-Orthogonal Multiple Access Networks, Journal of Telecommunications and Information Technology, 2021, nr 3

This paper studies downlink cellular networks relying on non-orthogonal multiple access (NOMA). Specifically, the access point (AP) is able to harvest wireless power from the power beacon (PB). In the context of an AP facilitated with multiple antennas, the transmit antenna selection procedure is performed to process the downlink signal, with the transmission guaranteed by energy harvesting. Therefore, a wireless power transfer-based network is introduced to overcome power outages at the AP. In particular, an energy-constrained AP harvests energy from the radio frequency signals transmitted by the PB in order to assist in transmitting user data. Outage performance and ergodic capacity are evaluated with the use of closed-form expressions. In order to highlight some insights, approximate computations are provided. Finally, numerical simulations are performed to confirm the benefits of combining the downlink NOMA transmission and the transmit power scheme at the AP in order to serve a multitude of user

Choosing the best machine tool in mechanical manufacturing

Machine tools are indispensable components and play an important role in mechanical manufacturing. The equipment of machine tools has a huge effect on the operational efficiency of businesses. Each machine tool type is described by many different criteria, such as cost, technological capabilities, accuracy, energy consumption, convenience in operation, safety for workers, working noise, etc. If the selection of machine is only based on one or several criteria, it will be really easy to make mistakes, which means it is not possible to choose the real best machine. A machine is considered to be the best only when it is chosen based on all of its criteria. This work is called multi-criteria decision-making (MCDM). In this study, the selection of machine tools has been done using two different multi-criteria decision-making methods, including the FUCA method (Faire Un Choix Adéquat) and the CURLI method (Collaborative Unbiased Rank List Intergration). These are two methods with very different characteristics. When using the FUCA method, it is necessary to normalize the data and determine the weights for the criteria. Meanwhile, if using the CURLI method, these two things are not necessary. The selection of these two distinct methods is intended to produce the most generalizable conclusions. Three types of machine tool, which are considered in this study, include grinding machine, drilling machine and milling machine. The number of grinders that were offered for selection was twelve, the number of drills that were surveyed in this study was thirteen, while nine were the number of milling machines that were given for selection. The objective of this study is to determine the best solution in each type of machine. The results of ranking the machines are very similar when using the two mentioned methods. Specially, in all the surveyed cases, the two methods FUCA and CURLI always find the same best alternative. Accordingly, it is possible to firmly come to a conclusion that the FUCA method and the CURLI method are equally effective in machine tool selection. In addition, this study has determined the best three machines corresponding to the three different machine type

Outage performance analysis of cell-center/edge users under two policies of energy harvesting

In this paper, two energy harvesting policies deploying in cooperative non-orthogonal multiple access (NOMA) systems are considered. After period of wireless power transfer, the NOMA users including cell-edge and cell-center users simultaneously transmit the superposition coded symbols to the base station (BS). In the last time slot, the BS decodes to achieve its signal based on superposition coded symbol with corresponding power allocation factors. This paper provides exact expressions of outage probability in two schemes. Performance gap of two NOMA users can be raised by providing different power allocation factors. It is confirmed by numerical result. Distance and data rate are main factors affecting outage performance. Scheme I exhibit scenario where power beacon transmits energy signal to NOMA user while the BS feeds energy to NOMA user in Scheme II. It is shown that outage performance of Scheme I is better than that of Scheme II.Web of Science254807

Applying the Theory of Planned Behavior (TPB) in Investigating Consumption Behavior in Vietnam

This study explored the consumer behavior based on TPB model in Vietnam. The hypotheses are empirically tested using survey data obtained from consumer who purchased green products of household appliances in Hanoi– the capital of Vietnam. During the study, the research team added the “trend” variable which is a characteristic variable in Vietnam. The results of the multiple regression analysis show that attitude, subjective norm, perceived behavioral control, trend have significant and positive effect on household appliances product. The research findings are discussed and implications for government, manufacturing businesses, retail businesses to embrace green consumption behavior Keywords: Consumption Behavior; Vietnam; TPB; Household appliances DOI: 10.7176/EJBM/12-18-16 Publication date:June 30th 202

The perspective of psychology students on the areas of psychology

Perception is defined as the result of an awareness process about phenomena, things (living animals, plants, or humans), connections between objects by activities including noticing, observing, differentiating, and acknowledging. A recent study was conducted to investigate the undergraduate’s perception of areas of psychology. This research used the Vietnamese version of the Scale of Interests by Areas of Psychology (EIAPsi), including ten subscales to survey 252 psychology students (57 males and 195 females) from four universities in Vietnam. The findings showed significant effects of university and major on psychology undergraduate’s perception of areas of psychology. Students majoring in Counseling and Clinical Psychology had more general knowledge about the functions and roles of Clinical and Health Psychology and Neuropsychology than other undergraduates. Industrial and Organizational Psychology students had more general knowledge about Organizational Psychology than students in other majors

Design of a smart doorbell for a leader’s office with availability status notification and visitor recognition features

Smart doorbells have become a critical component of smart homes and modern offices. However, a smart doorbell, particularly designed for a leader’s office, has not been introduced. In this study, a smart doorbell is developed for a leader’s office. The system includes an application that allows availability status notification on the doorbell module and voice communication with the visitor from inside the office based on a private Wi-Fi network without an Internet connection to prevent the leader from potential privacy and security issues. It also features a live video capture of the visitor with face recognition by implementing a MobileNet model. In training and testing this model, 1,549 free face images of 125 people were augmented to generate training, validation, and testing datasets of 9,185, 2,500, and 5,000 face images, respectively. An additional authentication testing dataset of 1,068 AI-generated face images was also used to evaluate the system’s False Acceptance Rate (FAR). A high confidence level of 0.945 was selected for the developed MobileNet model to obtain zero FAR and high accuracy, recall, and F-score values of 0.960, 0.960, and 0.978, respectively. Therefore, the proposed doorbell could be used for an office leader, showing potential use for biometric authentication