Md. Saiful Islam, Shuvo Jyoti Das, Md. Riajul Alam Khan, Sifat Momen^*, Nabeel Mohammed

Computer Systems Science and Engineering, Vol.44, No.1, pp. 519-534, 2023, DOI:10.32604/csse.2023.025282 - 01 June 2022

Abstract COVID-19 has created a panic all around the globe. It is a contagious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), originated from Wuhan in December 2019 and spread quickly all over the world. The healthcare sector of the world is facing great challenges tackling COVID cases. One of the problems many have witnessed is the misdiagnosis of COVID-19 cases with that of healthy and pneumonia cases. In this article, we propose a deep Convolutional Neural Network (CNN) based approach to detect COVID+ (i.e., patients with COVID-19), pneumonia and normal cases, from the… More >

Mustufa Haider Abidi^*, Hisham Alkhalefah, Muneer Khan Mohammed

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5367-5383, 2022, DOI:10.32604/cmc.2022.030018 - 28 July 2022

Abstract In modern scenarios, Industry 4.0 entails invention with various advanced technology, and blockchain is one among them. Blockchains are incorporated to enhance privacy, data transparency as well as security for both large and small scale enterprises. Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively. However, because numerous devices and machines are involved, data security and privacy are always concerns. To achieve intelligence in Industry 4.0, blockchain technologies can overcome potential cybersecurity constraints. Nowadays, the blockchain and internet of things (IoT) are gaining more attention… More >

Xinheng Yuan, Hao Yu, Houlin Zhang, Li Zheng, Erbao Dong^*, Heng’an Wu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 281-301, 2022, DOI:10.32604/cmes.2022.021383 - 21 July 2022

Abstract Robotic grasping is an essential problem at both the household and industrial levels, and unstructured objects have always been difficult for grippers. Parallel-plate grippers and algorithms, focusing on partial information of objects, are one of the widely used approaches. However, most works predict single-size grasp rectangles for fixed cameras and gripper sizes. In this paper, a multi-scale grasp detector is proposed to predict grasp rectangles with different sizes on RGB-D or RGB images in real-time for hand-eye cameras and various parallel-plate grippers. The detector extracts feature maps of multiple scales and conducts predictions on each… More >

Nasebah Almufadi¹, Ali Mustafa Qamar^1,2,*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1255-1270, 2022, DOI:10.32604/csse.2022.025029 - 09 May 2022

Abstract Currently, mobile communication is one of the widely used means of communication. Nevertheless, it is quite challenging for a telecommunication company to attract new customers. The recent concept of mobile number portability has also aggravated the problem of customer churn. Companies need to identify beforehand the customers, who could potentially churn out to the competitors. In the telecommunication industry, such identification could be done based on call detail records. This research presents an extensive experimental study based on various deep learning models, such as the 1D convolutional neural network (CNN) model along with the recurrent More >

Laiali Almazaydeh^1,*, Saleh Atiewi², Arar Al Tawil³, Khaled Elleithy⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5443-5458, 2022, DOI:10.32604/cmc.2022.025526 - 21 April 2022

Abstract Genres are one of the key features that categorize music based on specific series of patterns. However, the Arabic music content on the web is poorly defined into its genres, making the automatic classification of Arabic audio genres challenging. For this reason, in this research, our objective is first to construct a well-annotated dataset of five of the most well-known Arabic music genres, which are: Eastern Takht, Rai, Muwashshah, the poem, and Mawwal, and finally present a comprehensive empirical comparison of deep Convolutional Neural Networks (CNNs) architectures on Arabic music genres classification. In this work, More >

R. Kavitha^1,*, N. Viswanathan²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1305-1320, 2022, DOI:10.32604/iasc.2022.022816 - 08 February 2022

Abstract Bone marrow cancer is considered to be the most complex and dangerous disease which results due to an uncontrolled growth of white blood cells called leukocytes. Acute Lymphoblastic Leukemia (ALL) and Multiple Myeloma (MM) are considered to be important categories of bone cancers, which induces a larger number of cancer cells in the bone marrow, results in preventing the production of healthy blood cells. The advent of Artificial Intelligence, especially machine and deep learning, has expanded humanity’s capacity to analyze and detect these increasingly complex diseases. But, accurate detection of cancer cells and reducing the… More >

K. O. Mohammed Aarif^1,*, P. Sivakumar²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 275-289, 2022, DOI:10.32604/iasc.2022.022805 - 05 January 2022

Abstract Deep learning has achieved magnificent success in the field of pattern recognition. In recent years Urdu character recognition system has significantly benefited from the effectiveness of the deep convolutional neural network. Majority of the research on Urdu text recognition are concentrated on formal handwritten and printed Urdu text document. In this paper, we experimented the Challenging issue of text recognition in Urdu ancient literature documents. Due to its cursiveness, complex word formation (ligatures), and context-sensitivity, and inadequate benchmark dataset, recognition of Urdu text from the literature document is very difficult to process compared to the… 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 - 13 December 2021

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 More >

Yu Xue^1,2,*, Bernard-Marie Onzo¹, Romany F. Mansour^3,4, Shoubao Su⁴

Computer Systems Science and Engineering, Vol.42, No.1, pp. 201-211, 2022, DOI:10.32604/csse.2022.022158 - 02 December 2021

Abstract Coronavirus disease 2019 (Covid-19) is a life-threatening infectious disease caused by a newly discovered strain of the coronaviruses. As by the end of 2020, Covid-19 is still not fully understood, but like other similar viruses, the main mode of transmission or spread is believed to be through droplets from coughs and sneezes of infected persons. The accurate detection of Covid-19 cases poses some questions to scientists and physicians. The two main kinds of tests available for Covid-19 are viral tests, which tells you whether you are currently infected and antibody test, which tells if you… More >

Sitara Afzal, Imran Ullah Khan, Jong Weon Lee^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1903-1923, 2022, DOI:10.32604/cmc.2022.021930 - 03 November 2021

Abstract Cerebral microbleeds are small chronic vascular diseases that occur because of irregularities in the cerebrum vessels. Individuals and elderly people with brain injury and dementia can have small microbleeds in their brains. A recent study has shown that cerebral microbleeds could be remarkably risky in terms of life and can be riskier for patients with dementia. In this study, we proposed an efficient approach to automatically identify microbleeds by reducing the false positives in openly available susceptibility-weighted imaging (SWI) data samples. The proposed structure comprises two different pre-trained convolutional models with four stages. These stages… More >