ABSTRACT
This paper presented a simple and easy-To-use intelligent mirror with the activated function by face recognition. Firstly, the function of face recognition was realized by the OpenMV platform, and the recognition information was transmitted to the main controller, i.e., Loongson 1C Zhilong development board. The main controller connected to the Django server through the distant communication function of ESP8266 module. The user's schedules were acquisitioned by such a communication pathway and analyzed by the main controller. Finally, the recognized user's business or traveling schedule was shown on a screen located in the rear of a semitransparent mirror. For strangers of this smart mirror, the successful rate of strangers was 100%. For the user, the successful rate of strangers was 90% and accuracy of user's recognition was 100% in 120 times of tests. Furthermore, Adaptive Neuro Fuzzy Inference System supports a nice performance for Automatic classification in computer simulation. The COVID-19 pandemic is still threatening human beings. A smart mirror with the function of face recognition activation is a non-Touching solution for avoiding the infections to support an idea for elevating human health. © 2023 Global IT Research Institute (GiRI).
ABSTRACT
The recent outbreak of COVID-19 is taking the fashion industry through a challenging period. The industry's activities are now being more facilitated by digital platforms/influencers in the dispensation of products than ever before. This study seeks to investigate digital platforms/influencers in developing countries and their impact on the fashion industry. The study also explores the challenges of information asymmetry online, drawing on the lemon market theory (LMT), as the theoretical lens. Qualitative data was collected from twenty-two respondents;the research findings indicate that the use of digital platforms/influencers is essential in reaching the industry's vital consumers. Also, information asymmetry is the greatest challenge as far as e-business is concerned.-The contribution of this study reposes the use of LMT to determine how information asymmetry is leveraged. In terms of the policy, this research provides strategies for discussions on security and trust for policymakers to secure payment and delivery in e-business. Copyright © 2022, IGI Global.
ABSTRACT
The coronavirus disease 2019 (COVID-19) continues to have a negative impact on healthcare systems around the world, though the vaccines have been developed and national vaccination coverage rate is steadily increasing. At the current stage, automatically segmenting the lung infection area from CT images is essential for the diagnosis and treatment of COVID-19. Thanks to the development of deep learning technology, some deep learning solutions for lung infection segmentation have been proposed. However, due to the scattered distribution, complex background interference and blurred boundaries, the accuracy and completeness of the existing models are still unsatisfactory. To this end, we propose a boundary guided semantic learning network (BSNet) in this paper. On the one hand, the dual-branch semantic enhancement module that combines the top-level semantic preservation and progressive semantic integration is designed to model the complementary relationship between different high-level features, thereby promoting the generation of more complete segmentation results. On the other hand, the mirror-symmetric boundary guidance module is proposed to accurately detect the boundaries of the lesion regions in a mirror-symmetric way. Experiments on the publicly available dataset demonstrate that our BSNet outperforms the existing state-of-the-art competitors and achieves a real-time inference speed of 44 FPS. The code and results of our BSNet can be found from the link of https://github.com/rmcong/BSNet. IEEE
ABSTRACT
Humans start their day by looking in the mirror at least once before leaving their homes every morning. In addition, they waste some considerable time of their busy workload in front of the mirror. To make this time more productive and useful, there ought to be a system that can be readily conducted, user-friendly, and smart according to the constant progress on the Internet of Things. The intelligent mirror is a new addition to the smart device family, which is a straightforward concept. There will be a screen placed behind a two-way mirror, and this Intelligent Mirror turns our room or bathroom mirror into a personal assistant with artificial intelligence. The purpose is to develop a smart mirror that can automate working humans' busy daily routines and manage their tasks when they spend their time in front of a mirror. To make the most of this moment, users can securely access all the relevant details of the day by looking in the mirror simultaneously. The intelligent mirror, which a single voice command can activate, will significantly help disabled persons and the general. Raspberry Pi has been used to build the proposed intelligent mirror, linked to the digital world via the Internet. The mirror can communicate with the user through voice commands and reply appropriately. The monitoring of emotions and health measuring function will provide a distinctive experience to the users. The mirror will reflect important elements such as weather, date & time, covid-19 situation reports, local news, To-do list, water reminder, home workouts, and meal plans. The mirror can also handle specialized functions such as automating and controlling home IoT devices. © 2021 IEEE.
ABSTRACT
In Europe, heavy goods vehicles (HGVs) are disproportionately involved in serious and fatal collisions with vulnerable road users (VRUs). An interrogation of 2019 national crash data for Great Britain (Stats19) suggested that detection of cyclists and pedestrians in the nearside and front blind spots of HGVs is still a significant problem during forward or left-turn manoeuvres of the HGV. To improve detection, Transport for London introduced Direct Vision and Safe System Standards in 2021 for HGVs entering the Greater London area. This research assessed the efficacy of one of the Safe System requirements—the fitment of sensors to detect vulnerable road users on the nearside of the vehicle. A physical testing procedure was developed to determine the performance of a sensor system meeting the Transport for London Safe System requirements. Overall, the Safe System compliant sensor system missed 52% of expected detection nodes on the nearside of the vehicle. A total of 56% of the “stop vehicle” nodes, 45% of the “slow down” and 48% of the “proceed with caution” nodes were not recognised. The most forward sensor did not fully cover the front-left corner blind spot, missing 70% of the desired detection nodes. Nearside sensor systems fitted to Safe System requirements may cover a reasonable area but could still leave many undetected zones to the left and front of the vehicle. Standardising sensor range and location could help to eliminate sensor blind spots. Mandating additional front sensors would help cover the blind spot at the front-left corner of the HGV.
ABSTRACT
Research pertaining to SARS-CoV-2 is in full swing to understand the origin and evolution of this deadly virus that can lead to its rapid detection. To achieve this, atypical genomic sequences which may be unique to SARS-CoV-2 or Coronaviridae family in general may be investigated. Such sequences in virus genomes may be responsible for target prediction, replication, defence mechanisms and viral packaging. This fact has motivated us to explore the different types of repeats such as palindromes, mirror repeats and inverted repeats in SARS-CoV-2, MERS-CoV and SARS-CoV-1. For this purpose, the respective reference sequence of SARS-CoV-2, MERS-CoV and SARS-CoV-1 is divided into descriptors of sequences of length k using k-mer technique. Thereafter, these descriptors are represented as a collection of tokens which are subsequently used for the identification of palindrome, mirror repeat and inverted repeat in the respective reference sequence. The highest number of palindromes, mirror repeats and inverted repeats are identified for descriptor length 10. As a result, for palindromes such values are 38, 42 and 33 and for mirror repeats they are 52, 38 and 33 for SARS-CoV-2, MERS-CoV and SARS-CoV-1 respectively. For inverted repeats, with a descriptor length 10 and intervening length 5, the values are 59, 56 and 70 respectively. Moreover, the identified repeats are then searched for in 108246, 291 and 340 SARS-CoV-2, MERS-CoV and SARS-CoV-1 virus sequences respectively to find the population coverage of such repeats. It surpasses 99% in most cases and even 100% for some. Furthermore, GC contents which mostly lie between 20%-50% are evaluated for these repeats as well in order to understand their binding efficacy. Author