Talha Imran¹, Muhammad Attique Khan², Muhammad Sharif¹, Usman Tariq³, Yu-Dong Zhang⁴, Yunyoung Nam^5,*, Yunja Nam⁵, Byeong-Gwon Kang⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1875-1891, 2022, DOI:10.32604/cmc.2022.018946 - 07 September 2021

Abstract Malaria is a critical health condition that affects both sultry and frigid region worldwide, giving rise to millions of cases of disease and thousands of deaths over the years. Malaria is caused by parasites that enter the human red blood cells, grow there, and damage them over time. Therefore, it is diagnosed by a detailed examination of blood cells under the microscope. This is the most extensively used malaria diagnosis technique, but it yields limited and unreliable results due to the manual human involvement. In this work, an automated malaria blood smear classification model is More >

Abdul Majid¹, Muhammad Attique Khan¹, Yunyoung Nam^2,*, Usman Tariq³, Sudipta Roy⁴, Reham R. Mostafa⁵, Rasha H. Sakr⁶

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 319-337, 2021, DOI:10.32604/cmc.2021.016816 - 04 June 2021

Abstract The recent COVID-19 pandemic caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a significant impact on human life and the economy around the world. A reverse transcription polymerase chain reaction (RT-PCR) test is used to screen for this disease, but its low sensitivity means that it is not sufficient for early detection and treatment. As RT-PCR is a time-consuming procedure, there is interest in the introduction of automated techniques for diagnosis. Deep learning has a key role to play in the field of medical imaging. The most important issue… More >

J. Jayanthi^1,*, M. Kavitha², T. Jayasankar³, A. Sagai Francis Britto⁴, N. B. Prakash⁵, Mohamed Yacin Sikkandar⁶, C. Bharathiraja⁷

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4191-4203, 2021, DOI:10.32604/cmc.2021.012252 - 06 May 2021

Abstract Image recognition is considered to be the pre-eminent paradigm for the automatic detection of tumor diseases in this era. Among various cancers identified so far, glioma, a type of brain tumor, is one of the deadliest cancers, and it remains challenging to the medicinal world. The only consoling factor is that the survival rate of the patient is increased by remarkable percentage with the early diagnosis of the disease. Early diagnosis is attempted to be accomplished with the changes observed in the images of suspected parts of the brain captured in specific interval of time.… More >

Yunzuo Zhang^*, Yi Li, Wei Guo, Lei Huo, Jiayu Zhang, Kaina Guo

Journal of Cyber Security, Vol.3, No.1, pp. 45-54, 2021, DOI:10.32604/jcs.2021.017071 - 30 April 2021

Abstract In the field of educational examination, automatic marking technology plays an essential role in improving the efficiency of marking and liberating the labor force. At present, the implementation of the policy of expanding erolments has caused a serious decline in the teacher-student ratio in colleges and universities. The traditional marking system based on Optical Mark Reader technology can no longer meet the requirements of liberating the labor force of teachers in small and medium-sized examinations. With the development of image processing and artificial neural network technology, the recognition of handwritten character in the field of… More >

Anfeng Zhu, Zhao Xiao, Qiancheng Zhao^*

Energy Engineering, Vol.118, No.3, pp. 549-563, 2021, DOI:10.32604/EE.2021.014177 - 22 March 2021

Abstract Due to the frequent changes of wind speed and wind direction, the accuracy of wind turbine (WT) power prediction using traditional data preprocessing method is low. This paper proposes a data preprocessing method which combines POT with DBSCAN (POT-DBSCAN) to improve the prediction efficiency of wind power prediction model. Firstly, according to the data of WT in the normal operation condition, the power prediction model of WT is established based on the Particle Swarm Optimization (PSO) Arithmetic which is combined with the BP Neural Network (PSO-BP). Secondly, the wind-power data obtained from the supervisory control More >

Daniel Sierra-Sosa^1,*, Juan D. Arcila-Moreno², Begonya Garcia-Zapirain³, Adel Elmaghraby¹

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1849-1861, 2021, DOI:10.32604/cmc.2021.013196 - 05 February 2021

Abstract Quantum Machine Learning (QML) techniques have been recently attracting massive interest. However reported applications usually employ synthetic or well-known datasets. One of these techniques based on using a hybrid approach combining quantum and classic devices is the Variational Quantum Classifier (VQC), which development seems promising. Albeit being largely studied, VQC implementations for “real-world” datasets are still challenging on Noisy Intermediate Scale Quantum devices (NISQ). In this paper we propose a preprocessing pipeline based on Stokes parameters for data mapping. This pipeline enhances the prediction rates when applying VQC techniques, improving the feasibility of solving classification More >

Abderrahmane Saidi^*, Abdelmouneim Moulay Lakhdar, Mohammed Beladgham

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2875-2889, 2021, DOI:10.32604/cmc.2021.013744 - 28 December 2020

Abstract Handwriting recognition is one of the most significant problems in pattern recognition, many studies have been proposed to improve this recognition of handwritten text for different languages. Yet, Fewer studies have been done for the Arabic language and the processing of its texts remains a particularly distinctive problem due to the variability of writing styles and the nature of Arabic scripts compared to other scripts. The present paper suggests a feature extraction technique for offline Arabic handwriting recognition. A handwriting recognition system for Arabic words using a few important structural features and based on a… More >

Zhong Liu^1,2, Xin’an Wang¹, Chengjun Sun¹, Ken Lu³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 653-664, 2019, DOI:10.32604/cmc.2019.04597

Abstract With the high-speed development of transportation industry, highway traffic safety has become a considerable problem. Meanwhile, with the development of embedded system and hardware chip, in recent years, human eye detection eye tracking and positioning technology have been more and more widely used in man-machine interaction, security access control and visual detection.
In this paper, the high parallelism of FPGA was utilized to realize an elliptical approximate real-time human eye tracking system, which was achieved by the series register structure and random sample consensus (RANSAC), thus improving the speed of image processing without using external memory. Because… More >

Wentao Ma¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Yuanjing Luo¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 665-677, 2019, DOI:10.32604/cmc.2019.05683

Abstract As the first barrier to protect cyberspace, the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks. By researching the CAPTCHA, we can find its vulnerability and improve the security of CAPTCHA. Recently, many studies have shown that improving the image preprocessing effect of the CAPTCHA, which can achieve a better recognition rate by the state-of-the-art machine learning algorithms. There are many kinds of noise and distortion in the CAPTCHA images of this experiment. We propose an adaptive median filtering algorithm based on divide and conquer in this paper. Firstly, the More >

Raju R. Namburu¹, Eric R. Mark, Jerry A. Clarke

CMES-Computer Modeling in Engineering & Sciences, Vol.5, No.5, pp. 443-454, 2004, DOI:10.3970/cmes.2004.005.443

Abstract Computational electromagnetic (CEM) simulations of full-range military vehicles play a critical role in enhancing the survivability and target recognition of combat systems. Modeling of full-range military systems subjected to high frequencies may involve generating large-scale meshes, solving equations, visualization, and analysis of results in the range of billions of unknowns or grid points. Hence, the overall objective of this research is to develop and demonstrate a scalable CEM software environment to address accurate prediction of radar cross sections (RCS) for full- range armored vehicles with realistic material treatments and complex geometric configurations. A software environment… More >