Prasanalakshmi Balaji^1,*, B. Sri Revathi², Praveetha Gobinathan³, Shermin Shamsudheen³, Thavavel Vaiyapuri⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2275-2291, 2022, DOI:10.32604/cmc.2022.028560

Abstract Recently medical image classification plays a vital role in medical image retrieval and computer-aided diagnosis system. Despite deep learning has proved to be superior to previous approaches that depend on handcrafted features; it remains difficult to implement because of the high intra-class variance and inter-class similarity generated by the wide range of imaging modalities and clinical diseases. The Internet of Things (IoT) in healthcare systems is quickly becoming a viable alternative for delivering high-quality medical treatment in today’s e-healthcare systems. In recent years, the Internet of Things (IoT) has been identified as one of the most interesting research subjects in… More >

Yalan Gao, Yanqiong Zhang, Xianwei Jiang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 95-117, 2022, DOI:10.32604/cmes.2022.019970

Abstract (Aim) Chinese sign language is an essential tool for hearing-impaired to live, learn and communicate in deaf communities. Moreover, Chinese sign language plays a significant role in speech therapy and rehabilitation. Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society. Similar to the research of many biomedical image processing (such as automatic chest radiograph processing, diagnosis of chest radiological images, etc.), with the rapid development of artificial intelligence, especially deep learning technologies and algorithms, sign language image recognition ushered in the spring. This… More >

P. Renukadevi^1,*, A. Rajiv Kannan²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 629-645, 2023, DOI:10.32604/csse.2023.024217

Abstract About 170 nations have been affected by the COvid VIrus Disease-19 (COVID-19) epidemic. On governing bodies across the globe, a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive, and they feel challenging to tackle this situation. Most researchers concentrate on COVID-19 data analysis using the machine learning paradigm in these situations. In the previous works, Long Short-Term Memory (LSTM) was used to predict future COVID-19 cases. According to LSTM network data, the outbreak is expected to finish by June 2020. However, there is a chance of an over-fitting problem in… More >

Huanli Wang, Lingjun Yan, Xi Huang, Zhongwei Wang, Yuanhao Yue, Shijie Tang^*

Phyton-International Journal of Experimental Botany, Vol.91, No.10, pp. 2191-2210, 2022, DOI:10.32604/phyton.2022.020735

Abstract Quantitative real-time polymerase chain reaction (qRT-PCR) is a rapid and effective approach toward detecting the expression patterns of target genes. The selection of a stable reference gene under specific test condition is essential for expressing levels of target genes accurately. Tilia miqueliana, considered endangered, is a prominent native ornamental and honey tree in East China. No study has evaluated the optimal endogenous reference gene for qRT-PCR analysis in T. miqueliana systematically. In this study, fifteen commonly used reference genes were selected as candidate genes, and the stabilities of their expressions were assessed using four algorithms (GeNorm, NormFiner, BestKeeper, and DeltaCt)… More >

Mohamed W. Abo El-Soud^1,2,*, Tarek Gaber^2,3, Mohamed Tahoun², Abdullah Alourani¹

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1109-1123, 2022, DOI:10.32604/cmc.2022.028561

Abstract The prevalence of melanoma skin cancer has increased in recent decades. The greatest risk from melanoma is its ability to broadly spread throughout the body by means of lymphatic vessels and veins. Thus, the early diagnosis of melanoma is a key factor in improving the prognosis of the disease. Deep learning makes it possible to design and develop intelligent systems that can be used in detecting and classifying skin lesions from visible-light images. Such systems can provide early and accurate diagnoses of melanoma and other types of skin diseases. This paper proposes a new method which can be used for… More >

Rajkumar Sarma¹, Cherry Bhargava², Ketan Kotecha^3,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 481-495, 2022, DOI:10.32604/cmc.2022.024516

Abstract In the era of digital signal processing, like graphics and computation systems, multiplication-accumulation is one of the prime operations. A MAC unit is a vital component of a digital system, like different Fast Fourier Transform (FFT) algorithms, convolution, image processing algorithms, etcetera. In the domain of digital signal processing, the use of normalization architecture is very vast. The main objective of using normalization is to perform comparison and shift operations. In this research paper, an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer, Adder etc. The proposed normalization algorithm is further… More >

Mingxing Zhu, Yansong Wang, Ruyun Zhang, Tianning Zhang, Heyuan Li, Hanguang Luo, Shunbin Li^*

Journal on Internet of Things, Vol.3, No.3, pp. 99-107, 2021, DOI:10.32604/jiot.2021.014921

Abstract The Mimic Defense (MD) is an endogenous security technology with the core technique of Dynamic Heterogeneous Redundancy (DHR) architecture. It can effectively resist unknown vulnerabilities, backdoors, and other security threats by schedule strategy, negative feedback control, and other mechanisms. To solve the problem that Cyber Mimic Defense devices difficulty of supporting the TCP protocol. This paper proposes a TCP protocol normalization scheme for DHR architecture. Theoretical analysis and experimental results show that this scheme can realize the support of DHR-based network devices to TCP protocol without affecting the security of mimicry defense architecture. More >

Shouming Hou, Ji Han^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 855-869, 2022, DOI:10.32604/cmes.2022.016621

Abstract Many people around the world have lost their lives due to COVID-19. The symptoms of most COVID-19 patients are fever, tiredness and dry cough, and the disease can easily spread to those around them. If the infected people can be detected early, this will help local authorities control the speed of the virus, and the infected can also be treated in time. We proposed a six-layer convolutional neural network combined with max pooling, batch normalization and Adam algorithm to improve the detection effect of COVID-19 patients. In the 10-fold cross-validation methods, our method is superior to several state-of-the-art methods. In… More >

K. S. Bhuvaneshwari¹, K. Venkatachalam², S. Hubálovský^3,*, P. Trojovský⁴, P. Prabu⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5949-5965, 2022, DOI:10.32604/cmc.2022.020769

Abstract With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because of the features space grows… More >

Tao Zhang^1,2, Zhanjie Zhang^1,2,*, Wenjing Jia³, Xiangjian He³, Jie Yang⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2733-2747, 2021, DOI:10.32604/cmc.2021.019305

Abstract The generative adversarial network (GAN) is first proposed in 2014, and this kind of network model is machine learning systems that can learn to measure a given distribution of data, one of the most important applications is style transfer. Style transfer is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image. CYCLE-GAN is a classic GAN model, which has a wide range of scenarios in style transfer. Considering its unsupervised learning characteristics, the mapping is easy to be learned between an input image and an output… More >