ABSTRACT
In this paper, we present a new multimodal corpus called Biometric Russian Audio-Visual Extended MASKS (BRAVE-MASKS), which is designed to analyze voice and facial characteristics of persons wearing various masks, as well as to develop automatic systems for bimodal verification and identification of speakers. In particular, we tackle the multimodal mask type recognition task (6 classes). As a result, audio, visual and multimodal systems were developed, which showed UAR of 54.83%, 72.02% and 82.01%, respectively, on the Test set. These performances are the baseline for the BRAVE-MASKS corpus to compare the follow-up approaches with the proposed systems.
ABSTRACT
The paper focuses on some measures to improve the taxation of small- and medium-sized businesses. The legislation has many problems that should be solved in the field of taxation of business. The authors conclude that the discussed issue is problematic at the federal and regional levels because it is impossible to implement tasks and objectives for developing small and medium enterprises (including tax revenues) without state and regional support. The application of effective measures will increase the quantitative growth of entrepreneurs and the importance of their contribution to the regional and national economy. In scientific terms, a significant result is the application of a comprehensive and systemic method of the considered relationship with the use of the methodological tools of scientific research of the raised issues. The research confirms the need to further improve the practical activities of the subjects of commercial and entrepreneurial relations and their taxation, which is important in the current context of restrictions and the COVID-19 pandemics, which have considerably influenced the economic indicators of 2020–2021. The strategy for the development of small and medium entrepreneurship in the Russian Federation until 2030 clearly states that about 20% of the GRP in Russia and over one-third of GRP in some regions are created by small businesses. In a developed market economy, entrepreneurial activity is one of the fundamental segments of the market because it is one of the main indicators of economic growth. Consequently, the economy of Russia, like most developed countries in the world, is built on market principles directly regulated in the legislative acts of the national and international agreements. These principles include freedom of entrepreneurial activity, diversity of ownership, market pricing system, and limited government intervention in the entrepreneurial sphere. The country solves the issues considering all existing internal mechanisms. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Monitoring and evaluation of the safety level of individuals is one of the most important problems of the modern world, which was forced to change due to the emergence of the COVID-19 virus. To increase the safety level of individuals, new information technologies are needed that can stop the spread of infection by minimizing the threat of outbreaks and monitor compliance with recommended measures. These technologies, in particular, include intelligent tracking systems of the presence of protective face masks. For these systems, this article proposes a new method for generating training data that combines data augmentation techniques, such as Mixup and Insert. The proposed method is tested on two datasets, namely, the MAsked FAce dataset and the Real-World Masked Face Recognition Dataset. For these datasets, values of the unweighted average recalls of 98.51% and 98.50% are obtained. In addition, the effectiveness of the proposed method is tested on images with face mask imitation on people's faces, and an automated technique is proposed for reducing type I and II errors. Using the proposed automated technique, it is possible to reduce the number of type II errors from 174 to 32 for the Real-World Masked Face Recognition Dataset, and from 40 to 14 for images with painted protective face masks.
ABSTRACT
In the modern world, wearing masks, respirators and facial clothes is very popular. The novel coronavirus pandemic that began in 2019 has also significantly increased the applicability of masks in public places. The most affective person recognition methods are identification by face image and voice recording. However, person recognition systems are facing new challenges due to masks covering most of the subject’s face. Existence of new problems for intelligent systems determines the relevance of masked person recognition systems research, therefore the subject of the study is the systems and datasets for masked people recognition. The article discusses analysis of the main approaches to masked people identity recognition: masked face recognition, masked voice recognition and audiovisual methods. In addition, this article includes comparative analysis of images and recordings datasets required for person recognition systems. The results of the study showed that among the methods that use face images the most effective are methods based on convolutional neural networks and the mask area feature extraction. The methods of x-vector analysis showed a slight drop in efficiency which allows us to conclude that they are applicable in the tasks of recognizing the identity of a speaker in a mask. Results of this study help with formulation of requirements for perspective masked person recognition systems and determining directions for further research. © 2022, ITMO University. All rights reserved.
ABSTRACT
Objectives/Scope: Analysis of 15 years results of remote occupational health care in oil and gas production industries. Methods, Procedures, Process: Continuous observation, statistical analysis of morbidity, mortality, and treatment results in industrial personnel at different endpoints depending on the variability of care models. Cost-efficacy analysis of several occupational health interventions. Targeted polls of Customers. Dynamics of new Customers. Results, Observations, Conclusions: The best practices which provide the maximum efficacy include risk assessment and risk management, action planning for emergencies, telemedicine, education, registry maintenance. Each of all these gave a 10-100-fold rise in Customer satisfaction, seriously improved medical statistics. Telemedicine implies both: the delivery of highly specialized diagnostic technologies directly to the industrial production site, where a GP or paramedic is present, and it implements the direct replacement of medics with gadgets at the patient's bedside. Education involves hands-on training for both industrial personnel at remote sites and for medical professionals who provide care. The 2020-21 COVID19 pandemic was a great real stress test for remote health models when systemic integrated management procedures played a pivotal role in ensuring smooth industry operation due to the high quality of back medical services. Novel/Additive Information: Modern efficient models of medical care for remote industries are necessarily comprehensive, modular, adaptive, and rely on personnel health registers. Remote health practices gain a 5-15% rise in price every year, but it pays off in greater labor productivity and in improving the health of industry personnel. © Copyright 2021, Society of Petroleum Engineers
ABSTRACT
Since 2019 all countries of the world have faced the rapid spread of the pandemic caused by the COVID-19 coronavirus infection, the fight against which continues to the present day by the world community. Despite the obvious effectiveness of personal respiratory protection equipment against coronavirus infection, many people neglect the use of protective face masks in public places. Therefore, to control and timely identify violators of public health regulations, it is necessary to apply modern information technologies that will detect protective masks on people's faces using video and audio information. The article presents an analytical review of existing and developing intelligent information technologies for bimodal analysis of the voice and facial characteristics of a masked person. There are many studies on the topic of detecting masks from video images, and a significant number of cases containing images of faces both in and without masks obtained by various methods can also be found in the public access. Research and development aimed at detecting personal respiratory protection equipment by the acoustic characteristics of human speech is still quite small, since this direction began to develop only during the pandemic caused by the COVID-19 coronavirus infection. Existing systems allow to prevent the spread of coronavirus infection by recognizing the presence/absence of masks on the face, and these systems also help in remote diagnosis of COVID-19 by detecting the first symptoms of a viral infection by acoustic characteristics. However, to date, there is a number of unresolved problems in the field of automatic diagnosis of COVID-19 and the presence/absence of masks on people's faces. First of all, this is the low accuracy of detecting masks and coronavirus infection, which does not allow for performing automatic diagnosis without the presence of experts (medical personnel). Many systems are not able to operate in real time, which makes it impossible to control and monitor the wearing of protective masks in public places. Also, most of the existing systems cannot be built into a smartphone, so that users be able to diagnose the presence of coronavirus infection anywhere. Another major problem is the collection of data from patients infected with COVID-19, as many people do not agree to distribute confidential information. © 2021 St. Petersburg Federal Research Center of the Russian Academy of Sciences. All Rights Reserved.