Xing Guo^1,#, Yu-Dong Zhang^2,#, Siyuan Lu², Zhihai Lu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 23-71, 2022, DOI:10.32604/cmes.2021.017679 - 29 November 2021

Abstract Since Corona Virus Disease 2019 outbreak, many expert groups worldwide have studied the problem and proposed many diagnostic methods. This paper focuses on the research of Corona Virus Disease 2019 diagnosis. First, the procedure of the diagnosis based on machine learning is introduced in detail, which includes medical data collection, image preprocessing, feature extraction, and image classification. Then, we review seven methods in detail: transfer learning, ensemble learning, unsupervised learning and semi-supervised learning, convolutional neural networks, graph neural networks, explainable deep neural networks, and so on. What’s more, the advantages and limitations of different diagnosis More >

S. Ushasukhanya^*, M. Karthikeyan

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1261-1275, 2022, DOI:10.32604/iasc.2022.022654 - 17 November 2021

Abstract Electricity conservation systems are designed to conserve electricity to manage the bridge between the high raising demand and the production. Such systems have been so far using sensors to detect the necessity which adds an additional cost to the setup. Closed-circuit Television (CCTV) has been installed in almost everywhere around us especially in commercial places. Interpretation of these CCTV images is being carried out for various reasons to elicit the information from it. Hence a framework for electricity conservation that enables the electricity supply only when required, using existing resources would be a cost effective… More >

V. V. S. Vijaya Krishna^1,*, N. Pappa¹, S. P. Joy Vasantharani²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 781-794, 2022, DOI:10.32604/iasc.2022.022181 - 17 November 2021

Abstract Industries use soft sensors for estimating output parameters that are difficult to measure on-line. These parameters can be determined by laboratory analysis which is an offline task. Now a days designing Soft sensors for complex nonlinear systems using deep learning training techniques has become popular, because of accuracy and robustness. There is a need to find pertinent hardware for realizing soft sensors to make it portable and can be used in the place of general purpose PC. This paper aims to propose a new strategy for realizing a soft sensor using deep neural networks (DNN)… More >

Erssa Arif^1,*, Syed Khuram Shahzad², Rehman Mustafa¹, Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 909-922, 2022, DOI:10.32604/iasc.2022.021061 - 17 November 2021

Abstract The conventional surveillance and control system of Closed-Circuit Television (CCTV) cameras require human resource supervision. Almost all the criminal activities take place using weapons mostly handheld gun, revolver, or pistol. Automatic gun detection is a vital requirement now-a-days. The use of real-time object detection system for the improvement of surveillance is a promising application of Convolutional Neural Networks (CNN). We are concerned about the real-time detection of weapons for the surveillance cameras, so we focused on the implementation and comparison of faster approaches such as Region (R-CNN) and Region Fully Convolutional Networks (R-FCN) with feature… More >

Ali Sami Al-Itbi^*, Ahmed Bahaaulddin A. Alwahhab, Ali Mohammed Sahan

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1255-1271, 2022, DOI:10.32604/csse.2022.021980 - 10 November 2021

Abstract Notwithstanding the discovery of vaccines for Covid-19, the virus's rapid spread continues due to the limited availability of vaccines, especially in poor and emerging countries. Therefore, the key issues in the present COVID-19 pandemic are the early identification of COVID-19, the cautious separation of infected cases at the lowest cost and curing the disease in the early stages. For that reason, the methodology adopted for this study is imaging tools, particularly computed tomography, which have been critical in diagnosing and treating the disease. A new method for detecting Covid-19 in X-rays and CT images has… More >

Mohd Anul Haq, Mohd Abdul Rahim Khan^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1729-1750, 2022, DOI:10.32604/cmc.2022.020938 - 03 November 2021

Abstract The evolution and expansion of IoT devices reduced human efforts, increased resource utilization, and saved time; however, IoT devices create significant challenges such as lack of security and privacy, making them more vulnerable to IoT-based botnet attacks. There is a need to develop efficient and faster models which can work in real-time with efficiency and stability. The present investigation developed two novels, Deep Neural Network (DNN) models, DNNBoT1 and DNNBoT2, to detect and classify well-known IoT botnet attacks such as Mirai and BASHLITE from nine compromised industrial-grade IoT devices. The utilization of PCA was made… More >

Muhammad Shahid Bhatti^1,*, Azmat Ullah¹, Rohaya Latip², Abid Sohail¹, Anum Riaz¹, Rohail Hassan³

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 125-141, 2022, DOI:10.32604/cmc.2022.020083 - 03 November 2021

Abstract Text classification of low resource language is always a trivial and challenging problem. This paper discusses the process of Urdu news classification and Urdu documents similarity. Urdu is one of the most famous spoken languages in Asia. The implementation of computational methodologies for text classification has increased over time. However, Urdu language has not much experimented with research, it does not have readily available datasets, which turn out to be the primary reason behind limited research and applying the latest methodologies to the Urdu. To overcome these obstacles, a medium-sized dataset having six categories is… More >

P. N. Palanisamy^*, N. Malmurugan

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 791-808, 2022, DOI:10.32604/cmc.2022.019921 - 03 November 2021

Abstract In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real… More >

Kuntha Pin¹, Jee Ho Chang², Yunyoung Nam^3,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5821-5834, 2022, DOI:10.32604/cmc.2022.021943 - 11 October 2021

Abstract While the usage of digital ocular fundus image has been widespread in ophthalmology practice, the interpretation of the image has been still on the hands of the ophthalmologists which are quite costly. We explored a robust deep learning system that detects three major ocular diseases: diabetic retinopathy (DR), glaucoma (GLC), and age-related macular degeneration (AMD). The proposed method is composed of two steps. First, an initial quality evaluation in the classification system is proposed to filter out poor-quality images to enhance its performance, a technique that has not been explored previously. Second, the transfer learning… More >

Mohamed Ali¹, Ibrahim A. Abd El-Moghith², Mohamed N. El-Derini³, Saad M. Darwish^2,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6127-6140, 2022, DOI:10.32604/cmc.2022.021305 - 11 October 2021

Abstract Routing is a key function in Wireless Sensor Networks (WSNs) since it facilitates data transfer to base stations. Routing attacks have the potential to destroy and degrade the functionality of WSNs. A trustworthy routing system is essential for routing security and WSN efficiency. Numerous methods have been implemented to build trust between routing nodes, including the use of cryptographic methods and centralized routing. Nonetheless, the majority of routing techniques are unworkable in reality due to the difficulty of properly identifying untrusted routing node activities. At the moment, there is no effective way to avoid malicious… More >