Mesfer AI Duhayyim¹, Fahd N. Al-Wesabi², Radwa Marzouk³, Abdalla Ibrahim Abdalla Musa⁴, Noha Negm⁵, Anwer Mustafa Hilal⁶, Manar Ahmed Hamza^6,*, Mohammed Rizwanullah⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4135-4149, 2022, DOI:10.32604/cmc.2022.022336 - 07 December 2021

Abstract Internet of Medical Things (IoMT) is a breakthrough technology in the transfer of medical data via a communication system. Wearable sensor devices collect patient data and transfer them through mobile internet, that is, the IoMT. Recently, the shift in paradigm from manual data storage to electronic health recording on fog, edge, and cloud computing has been noted. These advanced computing technologies have facilitated medical services with minimum cost and available conditions. However, the IoMT raises a high concern on network security and patient data privacy in the health care system. The main issue is the… More >

Xiaorui Zhang^1,2,*, Xun Sun¹, Xingming Sun¹, Wei Sun³, Sunil Kumar Jha⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3035-3050, 2022, DOI:10.32604/cmc.2022.022304 - 07 December 2021

Abstract The leakage of medical audio data in telemedicine seriously violates the privacy of patients. In order to avoid the leakage of patient information in telemedicine, a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data. The scheme decomposes the medical audio into two independent embedding domains, embeds the robust watermark and the reversible watermark into the two domains respectively. In order to ensure the audio quality, the Hurst exponent is used to find a suitable position for watermark embedding. Due to the independence of the two embedding domains, the embedding of… More >

Anwer Mustafa Hil¹, Fahd N. Al-Wesabi², Hadeel Alsolai³, Ola Abdelgney Omer Ali⁴, Nadhem Nemri⁵, Manar Ahmed Hamza^1,*, Abu Sarwar Zamani¹, Mohammed Rizwanullah¹

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3921-3936, 2022, DOI:10.32604/cmc.2022.022301 - 07 December 2021

Abstract Social media is a platform in which user can create, share and exchange the knowledge/information. Social media marketing is to identify the different consumer's demands and engages them to create marketing resources. The popular social media platforms are Microsoft, Snapchat, Amazon, Flipkart, Google, eBay, Instagram, Facebook, Pin interest, and Twitter. The main aim of social media marketing deals with various business partners and build good relationship with millions of customers by satisfying their needs. Disruptive technology is replacing old approaches in the social media marketing to new technology-based marketing. However, this disruptive technology creates some… More >

Baowei Wang^1,2,3,*, Weishen Wang¹, Peng Zhao¹, Naixue Xiong⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2633-2652, 2022, DOI:10.32604/cmc.2022.022291 - 07 December 2021

Abstract Most of the existing zero-watermark schemes for medical images are only appropriate for a single grayscale image. When they protect a large number of medical images, repeating operations will cause a significant amount of time and storage costs. Hence, this paper proposes an efficient zero-watermark scheme for multiple color medical images based on quaternion generalized Fourier descriptor (QGFD). Firstly, QGFD is utilized to compute the feature invariants of each color image, then the representative features of each image are selected, stacked, and reshaped to generate a feature matrix, which is then binarized to get a… More >

Ahmed Elaraby^1,*, Walid Hamdy², Madallah Alruwaili³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4019-4031, 2022, DOI:10.32604/cmc.2022.022161 - 07 December 2021

Abstract Plant diseases are a major impendence to food security, and due to a lack of key infrastructure in many regions of the world, quick identification is still challenging. Harvest losses owing to illnesses are a severe problem for both large farming structures and rural communities, motivating our mission. Because of the large range of diseases, identifying and classifying diseases with human eyes is not only time-consuming and labor intensive, but also prone to being mistaken with a high error rate. Deep learning-enabled breakthroughs in computer vision have cleared the road for smartphone-assisted plant disease and… More >

Md. Mushfiqur Rahman^1,*, Md. Shabiul Islam¹, Mohammad Tariqul Islam², Samir Salem Al-Bawri³, Wong Hin Yong¹

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2383-2399, 2022, DOI:10.32604/cmc.2022.022150 - 07 December 2021

Abstract In this paper, a unit cell of a single-negative metamaterial structure loaded with a meander line and defected ground structure (DGS) is investigated as the principle radiating element of an antenna. The unit cell antenna causes even or odd mode resonances similar to the unit cell structure depending on the orientation of the microstrip feed used to excite the unit cell. However, the orientation which gives low-frequency resonance is considered here. The unit cell antenna is then loaded with a meander line which is parallel to the split bearing side and connects the other two… More >

M. Bharathidasan¹, V. Indragandhi¹, Ramya Kuppusamy², Yuvaraja Teekaraman³, Shabana Urooj^4,*, Norah Alwadi⁵

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4069-4084, 2022, DOI:10.32604/cmc.2022.021846 - 07 December 2021

Abstract Renewable electricity options, such as fuel cells, solar photovoltaic, and batteries, are being integrated, which has made DC micro-grids famous. For DC micro-grid systems, a multi input interleaved non-isolated dc-dc converter is suggested by the use of coupled inductor techniques. Since it compensates for mismatches in photovoltaic devices and allows for separate and continuous power flow from these sources. The proposed converter has the benefits of high gain, a low ripple in the output voltage, minimal stress voltage across the power semiconductor devices, a low ripple in inductor current, high power density, and high efficiency.… More >

Ahmed R. Abas¹, Ibrahim Elhenawy¹, Mahinda Zidan^2,*, Mahmoud Othman²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2943-2961, 2022, DOI:10.32604/cmc.2022.021671 - 07 December 2021

Abstract Due to the widespread usage of social media in our recent daily lifestyles, sentiment analysis becomes an important field in pattern recognition and Natural Language Processing (NLP). In this field, users’ feedback data on a specific issue are evaluated and analyzed. Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research. Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature. Emotions describe a state of mind of distinct behaviors, feelings, thoughts and experiences. The main objective… More >

Khaled M. Fouad^1,3, Sahar F. Sabbeh^1,2,*, Walaa Medhat^1,3

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3647-3665, 2022, DOI:10.32604/cmc.2022.021449 - 07 December 2021

Abstract Nowadays, an unprecedented number of users interact through social media platforms and generate a massive amount of content due to the explosion of online communication. However, because user-generated content is unregulated, it may contain offensive content such as fake news, insults, and harassment phrases. The identification of fake news and rumors and their dissemination on social media has become a critical requirement. They have adverse effects on users, businesses, enterprises, and even political regimes and governments. State of the art has tackled the English language for news and used feature-based algorithms. This paper proposes a… More >

Imran Ahmed¹, Iqbal Khan¹, Misbah Ahmad¹, Awais Adnan¹, Hanan Aljuaid^2,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2559-2577, 2022, DOI:10.32604/cmc.2022.021259 - 07 December 2021

Abstract The Internet of Things (IoT) has been transformed almost all fields of life, but its impact on the healthcare sector has been notable. Various IoT-based sensors are used in the healthcare sector and offer quality and safe care to patients. This work presents a deep learning-based automated patient discomfort detection system in which patients’ discomfort is non-invasively detected. To do this, the overhead view patients’ data set has been recorded. For testing and evaluation purposes, we investigate the power of deep learning by choosing a Convolution Neural Network (CNN) based model. The model uses confidence… More >