K. Lakshmi¹, Srinivas Nagineni², E. Laxmi Lydia³, A. Francis Saviour Devaraj⁴, Sachi Nandan Mohanty⁵, Irina V. Pustokhina^6,*, Denis A. Pustokhin⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 19-35, 2022, DOI:10.32604/cmc.2022.020244 - 24 February 2022

Abstract Cooperative Intelligent Transport System (C-ITS) plays a vital role in the future road traffic management system. A vital element of C-ITS comprises vehicles, road side units, and traffic command centers, which produce a massive quantity of data comprising both mobility and service-related data. For the extraction of meaningful and related details out of the generated data, data science acts as an essential part of the upcoming C-ITS applications. At the same time, prediction of short-term traffic flow is highly essential to manage the traffic accurately. Due to the rapid increase in the amount of traffic… More >

S. Rajasekaran^1,*, G. Kousalya²

Computer Systems Science and Engineering, Vol.42, No.3, pp. 985-1000, 2022, DOI:10.32604/csse.2022.022234 - 08 February 2022

Abstract The demand for better health services has resulted in the advancement of remote monitoring health, i.e., virtual nursing systems, to watch and support the elderly with innovative concepts such as being patient-centric, easier to use, and having smarter interactions and more accurate conclusions. While virtual nursing services attempt to provide consumers and medical practitioners with continuous medical and health monitoring services, access to allied healthcare experts such as nurses remains a challenge. In this research, we present Virtual Nursing Using Deep Belief Networks for Elderly People (DBN-EP), a new framework that provides a virtual nurse… More >

K. Babu^1,*, C. Kumar², C. Kannaiyaraju³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756 - 05 January 2022

Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component… More >

Yabin Xu^1,*, Lulu Cui¹, Xiaowei Xu²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 121-132, 2022, DOI:10.32604/csse.2022.022758 - 02 December 2021

Abstract Fracture toughness plays a vital role in damage tolerance design of materials and assessment of structural integrity. To solve these problems of complexity, time-consuming, and low accuracy in obtaining the fracture toughness value of nickel-based superalloys through experiments. A combination prediction model is proposed based on the principle of materials genome engineering, the fracture toughness values of nickel-based superalloys at different temperatures, and different compositions can be predicted based on the existing experimental data. First, to solve the problem of insufficient feature extraction based on manual experience, the Deep Belief Network (DBN) is used to… More >

A. S. Al-Waisy¹, Mazin Abed Mohammed¹, Shumoos Al-Fahdawi¹, M. S. Maashi², Begonya Garcia-Zapirain³, Karrar Hameed Abdulkareem⁴, S. A. Mostafa⁵, Nallapaneni Manoj Kumar⁶, Dac-Nhuong Le^7,8,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2409-2429, 2021, DOI:10.32604/cmc.2021.012955 - 05 February 2021

Abstract Coronavirus (COVID-19) epidemic outbreak has devastating effects on daily lives and healthcare systems worldwide. This newly recognized virus is highly transmissible, and no clinically approved vaccine or antiviral medicine is currently available. Early diagnosis of infected patients through effective screening is needed to control the rapid spread of this virus. Chest radiography imaging is an effective diagnosis tool for COVID-19 virus and follow-up. Here, a novel hybrid multimodal deep learning system for identifying COVID-19 virus in chest X-ray (CX-R) images is developed and termed as the COVID-DeepNet system to aid expert radiologists in rapid and… More >

Yongmei Zhang^{1, *}, Jianzhe Ma², Lei Hu³, Keming Yu⁴, Lihua Song^{1, 5}, Huini Chen¹

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1929-1944, 2020, DOI:10.32604/cmc.2020.010556 - 30 June 2020

Abstract The prediction of particles less than 2.5 micrometers in diameter (PM2.5) in fog and haze has been paid more and more attention, but the prediction accuracy of the results is not ideal. Haze prediction algorithms based on traditional numerical and statistical prediction have poor effects on nonlinear data prediction of haze. In order to improve the effects of prediction, this paper proposes a haze feature extraction and pollution level identification pre-warning algorithm based on feature selection and integrated learning. Minimum Redundancy Maximum Relevance method is used to extract low-level features of haze, and deep confidence More >

Chen Zhang¹, Jieren Cheng^1,2,3,*, Xiangyan Tang¹, Victor S. Sheng⁴, Zhe Dong¹, Junqi Li¹

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 657-675, 2019, DOI:10.32604/cmc.2019.06207

Abstract Distributed denial of service (DDoS) attacks launch more and more frequently and are more destructive. Feature representation as an important part of DDoS defense technology directly affects the efficiency of defense. Most DDoS feature extraction methods cannot fully utilize the information of the original data, resulting in the extracted features losing useful features. In this paper, a DDoS feature representation method based on deep belief network (DBN) is proposed. We quantify the original data by the size of the network flows, the distribution of IP addresses and ports, and the diversity of packet sizes of More >