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  • Open Access

    ARTICLE

    The Acute Effects of Aerobic Dance Exercise with and without Face Mask Use on Attention, Perceived Exertion and Mood States

    Maamer Slimani1,2,*, Nicola Bragazzi3, Amri Hammami2, Hela Znazen4, Qian Yu5,6, Zhaowei Kong6, Liye Zou5

    International Journal of Mental Health Promotion, Vol.23, No.4, pp. 513-520, 2021, DOI:10.32604/IJMHP.2021.017639

    Abstract The present study aimed to determine the effect of wearing a face mask during aerobic dance exercise on cognitive function, more specifically on attention, as well as on perceived exertion and mood states. Thirteen healthy college students (9 males and 4 females: mean age = 17.5 years, height = 1.72 m, weight = 71.00 kg) volunteered to participate in this study. They were randomized to perform aerobic dance exercise while wearing a cloth face mask or no mask or a control condition (sitting on a comfortable chair and reading information about the health benefits of aerobic dance exercise) on three separate occasions (with at least one week of… More >

  • Open Access

    ARTICLE

    Real Time Feature Extraction Deep-CNN for Mask Detection

    Hanan A. Hosni Mahmoud, Norah S. Alghamdi, Amal H. Alharbi*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1423-1434, 2022, DOI:10.32604/iasc.2022.020586

    Abstract COVID-19 pandemic outbreak became one of the serious threats to humans. As there is no cure yet for this virus, we have to control the spread of Coronavirus through precautions. One of the effective precautions as announced by the World Health Organization is mask wearing. Surveillance systems in crowded places can lead to detection of people wearing masks. Therefore, it is highly urgent for computerized mask detection methods that can operate in real-time. As for now, most countries demand mask-wearing in public places to avoid the spreading of this virus. In this paper, we are presenting an object detection technique… More >

  • Open Access

    ARTICLE

    Conductive Polymer Composites Fabricated by Disposable Face Masks and Multi-Walled Carbon Nanotubes: Crystalline Structure and Enhancement Effect

    Meng Xiang1, Zhou Yang1, Jingjing Yang1, Tong Lu1, Danqi Wu1, Zhijun Liu1, Rongjie Xue1, Shuang Dong2,*

    Journal of Renewable Materials, Vol.10, No.3, pp. 821-831, 2022, DOI:10.32604/jrm.2022.017347

    Abstract Influenced by recent COVID-19, wearing face masks to block the spread of the epidemic has become the simplest and most effective way. However, after the people wear masks, thousands of tons of medical waste by used disposable masks will be generated every day in the world, causing great pressure on the environment. Herein, conductive polymer composites are fabricated by simple melt blending of mask fragments (mask polypropylene, short for mPP) and multi-walled carbon nanotubes (MWNTs). MWNTs were used as modifiers for composites because of their high strength and high conductivity. The crystalline structure, mechanical, electrical and thermal enhancement effect of… More >

  • Open Access

    ARTICLE

    An Enhanced Deep Learning Model for Automatic Face Mask Detection

    Qazi Mudassar Ilyas1, Muneer Ahmad2,*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 241-254, 2022, DOI:10.32604/iasc.2022.018042

    Abstract The recent COVID-19 pandemic has had lasting and severe impacts on social gatherings and interaction among people. Local administrative bodies enforce standard operating procedures (SOPs) to combat the spread of COVID-19, with mandatory precautionary measures including use of face masks at social assembly points. In addition, the World Health Organization (WHO) strongly recommends people wear a face mask as a shield against the virus. The manual inspection of a large number of people for face mask enforcement is a challenge for law enforcement agencies. This work proposes an automatic face mask detection solution using an enhanced lightweight deep learning model.… More >

  • Open Access

    ARTICLE

    Intelligent Segmentation and Measurement Model for Asphalt Road Cracks Based on Modified Mask R-CNN Algorithm

    Jiaxiu Dong1,2,3, Jianhua Liu4, Niannian Wang1,2,3,*, Hongyuan Fang1,2,3, Jinping Zhang1, Haobang Hu1,2,3, Duo Ma1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 541-564, 2021, DOI:10.32604/cmes.2021.015875

    Abstract Nowadays, asphalt road has dominated highways around the world. Among various defects of asphalt road, cracks have been paid more attention, since cracks often cause major engineering and personnel safety incidents. Current manual crack inspection methods are time-consuming and labor-intensive, and most segmentation methods cannot detect cracks at the pixel level. This paper proposes an intelligent segmentation and measurement model based on the modified Mask R-CNN algorithm to automatically and accurately detect asphalt road cracks. The model proposed in this paper mainly includes a convolutional neural network (CNN), an optimized region proposal network (RPN), a region of interest (RoI) Align… More >

  • Open Access

    ARTICLE

    A Real-Time Integrated Face Mask Detector to Curtail Spread of Coronavirus

    Shilpa Sethi1, Mamta Kathuria1,*, Trilok Kaushik2

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 389-409, 2021, DOI:10.32604/cmes.2021.014478

    Abstract Effective strategies to control COVID-19 pandemic need high attention to mitigate negatively impacted communal health and global economy, with the brim-full horizon yet to unfold. In the absence of effective antiviral and limited medical resources, many measures are recommended by WHO to control the infection rate and avoid exhausting the limited medical resources. Wearing mask is among the non-pharmaceutical intervention measures that can be used as barrier to primary route of SARS-CoV2 droplets expelled by presymptomatic or asymptomatic individuals. Regardless of discourse on medical resources and diversities in masks, all countries are mandating coverings over nose and mouth in public… More >

  • Open Access

    ARTICLE

    Speech Intelligibility Enhancement Algorithm Based on Multi-Resolution Power-Normalized Cepstral Coefficients (MRPNCC) for Digital Hearing Aids

    Xia Wang1, Xing Deng2,3, Hongming Shen1,*, Guodong Zhang1, Shibing Zhang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 693-710, 2021, DOI:10.32604/cmes.2021.013186

    Abstract Speech intelligibility enhancement in noisy environments is still one of the major challenges for hearing impaired in everyday life. Recently, Machine-learning based approaches to speech enhancement have shown great promise for improving speech intelligibility. Two key issues of these approaches are acoustic features extracted from noisy signals and classifiers used for supervised learning. In this paper, features are focused. Multi-resolution power-normalized cepstral coefficients (MRPNCC) are proposed as a new feature to enhance the speech intelligibility for hearing impaired. The new feature is constructed by combining four cepstrum at different time–frequency (T–F) resolutions in order to capture both the local and… More >

  • Open Access

    ARTICLE

    The Development and Application of Quantum Masking

    Tao Chen1,2, Zhiguo Qu1,2,*, Yi Chen1,2

    Journal of Quantum Computing, Vol.2, No.3, pp. 151-156, 2020, DOI:10.32604/jqc.2020.015855

    Abstract To solve the problem of hiding quantum information in simplified subsystems, Modi et al. [1] introduced the concept of quantum masking. Quantum masking is the encoding of quantum information by composite quantum states in such a way that the quantum information is hidden to the subsystem and spreads to the correlation of the composite systems. The concept of quantum masking was developed along with a new quantum impossibility theorem, the quantum no-masking theorem. The question of whether a quantum state can be masked has been studied by many people from the perspective of the types of quantum states, the number… More >

  • Open Access

    ARTICLE

    Road Damage Detection and Classification Using Mask R-CNN with DenseNet Backbone

    Qiqiang Chen1, *, Xinxin Gan2, Wei Huang1, Jingjing Feng1, H. Shim3

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2201-2215, 2020, DOI:10.32604/cmc.2020.011191

    Abstract Automatic road damage detection using image processing is an important aspect of road maintenance. It is also a challenging problem due to the inhomogeneity of road damage and complicated background in the road images. In recent years, deep convolutional neural network based methods have been used to address the challenges of road damage detection and classification. In this paper, we propose a new approach to address those challenges. This approach uses densely connected convolution networks as the backbone of the Mask R-CNN to effectively extract image feature, a feature pyramid network for combining multiple scales features, a region proposal network… More >

  • Open Access

    ARTICLE

    Validating the Correct Wearing of Protection Mask by Taking a Selfie: Design of a Mobile Application “CheckYourMask” to Limit the Spread of COVID-19

    Karim Hammoudi1,2,*, Adnane Cabani3, Halim Benhabiles4, Mahmoud Melkemi1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1049-1059, 2020, DOI:10.32604/cmes.2020.011663

    Abstract In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019–2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting everyone having a smartphone and… More >

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