Khalil Khan¹, Jehad Ali², Kashif Ahmad³, Asma Gul⁴, Ghulam Sarwar⁵, Sahib Khan⁶, Qui Thanh Hoai Ta⁷, Tae-Sun Chung⁸, Muhammad Attique^9,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1757-1770, 2021, DOI:10.32604/cmc.2020.013590 - 26 November 2020

Abstract Face image analysis is one among several important cues in computer vision. Over the last five decades, methods for face analysis have received immense attention due to large scale applications in various face analysis tasks. Face parsing strongly benefits various human face image analysis tasks inducing face pose estimation. In this paper we propose a 3D head pose estimation framework developed through a prior end to end deep face parsing model. We have developed an end to end face parts segmentation framework through deep convolutional neural networks (DCNNs). For training a deep face parts parsing… More >

G. Arun Sampaul Thomas¹, Y. Harold Robinson², E. Golden Julie³, Vimal Shanmuganathan⁴, Seungmin Rho⁵, Yunyoung Nam^6,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1613-1629, 2021, DOI:10.32604/cmc.2020.013443 - 26 November 2020

Abstract Retinopathy is a human eye disease that causes changes in retinal blood vessels that leads to bleed, leak fluid and vision impairment. Symptoms of retinopathy are blurred vision, changes in color perception, red spots, and eye pain and it cannot be detected with a naked eye. In this paper, a new methodology based on Convolutional Neural Networks (CNN) is developed and proposed to intelligent retinopathy prediction and give a decision about the presence of retinopathy with automatic diabetic retinopathy screening with accurate diagnoses. The CNN model is trained by different images of eyes that have More >

K. Shankar^1,*, Eswaran Perumal¹, Mohamed Elhoseny², Phong Thanh Nguyen³

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1665-1680, 2021, DOI:10.32604/cmc.2020.013251 - 26 November 2020

Abstract Diabetic retinopathy (DR) is a disease with an increasing prevalence and the major reason for blindness among working-age population. The possibility of severe vision loss can be extensively reduced by timely diagnosis and treatment. An automated screening for DR has been identified as an effective method for early DR detection, which can decrease the workload associated to manual grading as well as save diagnosis costs and time. Several studies have been carried out to develop automated detection and classification models for DR. This paper presents a new IoT and cloud-based deep learning for healthcare diagnosis… More >

Ruaa A. Al-Falluji^1,*, Zainab Dalaf Katheeth², Bashar Alathari²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1301-1313, 2021, DOI:10.32604/cmc.2020.013232 - 26 November 2020

Abstract The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019 (COVID-19). The usage of sophisticated artificial intelligence technology (AI) and the radiological images can help in diagnosing the disease reliably and addressing the problem of the shortage of trained doctors in remote villages. In this research, the automated diagnosis of Coronavirus disease was performed using a dataset of X-ray images of patients with severe bacterial pneumonia, reported COVID-19 disease, and normal cases. The goal of the study is to analyze the achievements for medical image recognition… More >

Iftikhar Ahmad^1,*, Mohammed A. Alqarni², Abdulwahab Ali Almazroi³, Laiba Alam¹

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1813-1822, 2021, DOI:10.32604/cmc.2020.013048 - 26 November 2020

Abstract Blockchain technology is one of the key technological breakthroughs of the last decade. It has the ability to revolutionize numerous aspects of society, including financial systems, healthcare, e-government and many others. One such area that is able to reap the benefits of blockchain technology is the real estate industry. Like many other industries, real estate faces major administrative problems such as high transaction fees, a lack of transparency, fraud and the effects of a middleman including undue influence and commissions. Blockchain enables supporting technologies to overcome the obstacles inherent within the real estate investment market.… More >

Zia Ul Rehman^1,2, Sagheer Abbas¹, Muhammad Adnan Khan^3,*, Ghulam Mustafa², Hira Fayyaz⁴, Muhammad Hanif^1,2, Muhammad Anwar Saeed⁵

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1075-1090, 2021, DOI:10.32604/cmc.2020.012770 - 26 November 2020

Abstract The internet, particularly online social networking platforms have revolutionized the way extremist groups are influencing and radicalizing individuals. Recent research reveals that the process initiates by exposing vast audiences to extremist content and then migrating potential victims to confined platforms for intensive radicalization. Consequently, social networks have evolved as a persuasive tool for extremism aiding as recruitment platform and psychological warfare. Thus, recognizing potential radical text or material is vital to restrict the circulation of the extremist chronicle. The aim of this research work is to identify radical text in social media. Our contributions are… More >

Srinath Doss¹, Jothi Paranthaman², Suseendran Gopalakrishnan³, Akila Duraisamy³, Souvik Pal⁴, Balaganesh Duraisamy⁵, Chung Le Van^6,*, Dac-Nhuong Le⁷

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1577-1594, 2021, DOI:10.32604/cmc.2020.012379 - 26 November 2020

Abstract In the healthcare system, the Internet of Things (IoT) based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests. This datum is sensitive, and hence security is a must in transforming the sensational contents. In this paper, an Evolutionary Algorithm, namely the Memetic Algorithm is used for encrypting the text messages. The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels. The reverse method of the Memetic Algorithm is implemented when extracting More >

Xiubing Gao^1,3, Jiejie Lv², Can Guo¹, Anlong Hu³, Xiaomao Wu³, Zengping Li^4,*

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 179-192, 2021, DOI:10.32604/phyton.2021.012968 - 20 November 2020

Abstract Hevea brasiliensis is one of the important economic trees with a great economic value for natural rubber production. Symbiosis between roots of H. brasiliensis and arbuscular mycorrhizal fungi (AMF) is widely recognized, and can provide a range of benefits for both of them. Hainan Island harbors is one of the largest plantations of H. brasiliensis in China, whereas the information regarding the diversity of AMF in the rhizosphere of H. brasiliensis on this island is scarce. The diversity of AMF species in the rhizosphere of rubber tree plantations in Hainan was investigated in this study. A total of 72… More >

Kai Sheng¹, Saichao Wei¹, Jun Mei^1,2,3,4,*, Jing Xie^1,2,3,4,*

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 291-305, 2021, DOI:10.32604/phyton.2020.012985 - 20 November 2020

Abstract Low-temperature storage is extensively used to optimize the postharvest life of various fresh fruits. However, red pitahaya (Hylocereus polyrhizus) fruits are sensitive to chilling injury (CI), which leads to the limitation of low-temperature storage. In this study, red pitahaya fruits were stored at 2, 4, 6, 8, and 10°C, respectively, for 27 days to determine the appropriate storage temperature. During the storage of red pitahaya fruits, storage at 8°C was more effective in suppressing decay and maintaining quality than other low temperatures. Low-temperature (2, 4, and 6°C) storage decreased weight loss (WL) and maintained higher content… More >

Shi-er Dong¹, Yiqing He^1,*, Jingya Dong², Zhouyu Peng³, Guohua Fu³

Energy Engineering, Vol.118, No.1, pp. 103-118, 2021, DOI:10.32604/EE.2020.012362 - 17 November 2020

Abstract Based on the analysis of the whole process of LNG spill on land, the research methods of LNG pool expansion and heavy gas diffusion are summarized and analyzed. This paper reviews the experimental and analytical work performed to data on spill of LNG. Specifically, experiments on the spill of LNG onshore, as well as experiments and numerical study on heavy gas dispersion. Pool boiling and turbulence model are described and discussed, as well as models used to predict dispersion. Although there have been significant progress in understanding the behavior of LNG spills, technical knowledge gaps More >