Tao Li¹, Yongjin Hu^1,*, Ankang Ju¹, Zhuoran Hu²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 407-420, 2021, DOI:10.32604/cmc.2020.012023

Abstract Owing to the continuous barrage of cyber threats, there is a massive amount of cyber threat intelligence. However, a great deal of cyber threat intelligence come from textual sources. For analysis of cyber threat intelligence, many security analysts rely on cumbersome and time-consuming manual efforts. Cybersecurity knowledge graph plays a significant role in automatics analysis of cyber threat intelligence. As the foundation for constructing cybersecurity knowledge graph, named entity recognition (NER) is required for identifying critical threat-related elements from textual cyber threat intelligence. Recently, deep neural network-based models have attained very good results in NER. However, the performance of these… More >

Jianjun Zhang^1,*, Yifu Sheng¹, Weida Chen², Haijun Lin¹, Guang Sun³, Peng Guo⁴

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 389-405, 2021, DOI:10.32604/cmc.2020.012384

Abstract Water is one of the basic resources for human survival. Water pollution monitoring and protection have been becoming a major problem for many countries all over the world. Most traditional water quality monitoring systems, however, generally focus only on water quality data collection, ignoring data analysis and data mining. In addition, some dirty data and data loss may occur due to power failures or transmission failures, further affecting data analysis and its application. In order to meet these needs, by using Internet of things, cloud computing, and big data technologies, we designed and implemented a water quality monitoring data intelligent… More >

Anju Asokan¹, J. Anitha¹, Bogdan Patrut², Dana Danciulescu³, D. Jude Hemanth^1,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 373-388, 2021, DOI:10.32604/cmc.2020.012364

Abstract Multispectral images contain a large amount of spatial and spectral data which are effective in identifying change areas. Deep feature extraction is important for multispectral image classification and is evolving as an interesting research area in change detection. However, many deep learning framework based approaches do not consider both spatial and textural details into account. In order to handle this issue, a Convolutional Neural Network (CNN) based multi-feature extraction and fusion is introduced which considers both spatial and textural features. This method uses CNN to extract the spatio-spectral features from individual channels and fuse them with the textural features. Then… More >

Abdul Waheed^1,2,*, Naila Habib Khan³, Mahdi Zareei⁴, Shahab Ul Islam⁵, Latif Jan^5,6, Arif Iqbal Umar¹, Ehab Mahmoud Mohamed^7,8

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 359-372, 2021, DOI:10.32604/cmc.2020.012196

Abstract Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four… More >

Zhimin Zhang, Tianhe Kang^*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 341-357, 2021, DOI:10.32604/cmc.2020.012104

Abstract In view of the three-dimensional dynamic abutment pressure, the influence of the far-field hard stratum (FHS) in deep, thick coal seams is indeterminant. Based on elastic foundation theory, a three-dimensional dynamic prediction model of the abutment pressure was established. Using this model, the dynamic change in the coal seam abutment pressure caused by the movement of the FHS was studied, and a method for determining the dynamic change range of the abutment pressure was developed. The results of the new prediction model of the abutment pressure are slightly higher than the measured values, with an error of 0.51%, which avoids… More >

Muhammad Adnan Khan^1,*, Wajhe Ul Husnain Abidi^1,2, Mohammed A. Al Ghamdi³, Sultan H. Almotiri³, Shazia Saqib¹, Tahir Alyas¹, Khalid Masood Khan¹, Nasir Mahmood⁴

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 331-340, 2021, DOI:10.32604/cmc.2020.012148

Abstract Forecasting future outbreaks can help in minimizing their spread. Influenza is a disease primarily found in animals but transferred to humans through pigs. In 1918, influenza became a pandemic and spread rapidly all over the world becoming the cause behind killing one-third of the human population and killing one-fourth of the pig population. Afterwards, that influenza became a pandemic several times on a local and global levels. In 2009, influenza ‘A’ subtype H1N1 again took many human lives. The disease spread like in a pandemic quickly. This paper proposes a forecasting modeling system for the influenza pandemic using a feed-forward… More >

Abdu Gumaei^1,2,*, Mabrook Al-Rakhami¹, Mohamad Mahmoud Al Rahhal³, Fahad Raddah H. Albogamy³, Eslam Al Maghayreh³, Hussain AlSalman¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 315-329, 2021, DOI:10.32604/cmc.2020.012045

Abstract The fast spread of coronavirus disease (COVID-19) caused by SARSCoV-2 has become a pandemic and a serious threat to the world. As of May 30, 2020, this disease had infected more than 6 million people globally, with hundreds of thousands of deaths. Therefore, there is an urgent need to predict confirmed cases so as to analyze the impact of COVID-19 and practice readiness in healthcare systems. This study uses gradient boosting regression (GBR) to build a trained model to predict the daily total confirmed cases of COVID-19. The GBR method can minimize the loss function of the training process and… More >

Pokpong Amornvit, Dinesh Rokaya, Chaimongkon Peampring, Sasiwimol Sanohkan^*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 303-314, 2021, DOI:10.32604/cmc.2020.011943

Abstract Several capture techniques are used in intraoral optical scanners in the dental market, such as Triangulation (Cerec Omnicam, Dentsply Sirona), Activewave front sampling (3M ESPE) and confocal technology (iTero, Align). The accuracy of intraoral scanners is the most significant focal point for developers to research. This in-vitro study studied the accuracy of confocal scanners launched from 2015-2020 (Trios 3, Trios 4, iTero Element; 3Shape Trios A/S, Copenhagen, Denmark, and iTero Element2, and iTero Element5D; Align Technologies, San Jose, CA, USA). A 3D printing model modified from the American National Standard No. 132 was scanned five times each scanner. Both Trios3… More >

Salman Ahmed^*, Muhammad Ali Khan

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 291-301, 2021, DOI:10.32604/cmc.2020.012066

Abstract One of the greatest factors that affects the economic condition of a country is its institutions. In the model of good governance, the primary elements for stronger institution include efficiency, transparency, and accountability; and technology plays a major role in improving these elements. However, there are myriad of challenges when it comes to practical integration of technology in these institutions for efficiency. It is more challenging when a country is developing and one that is already weak economically. It is also important to mention that the challenges of digitization in public sector is not limited to developing countries only. It… More >

Yuming Chu¹, Naila Rafiq², Mudassir Shams^3,*, Saima Akram⁴, Nazir Ahmad Mir³, Humaira Kalsoom⁵

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 275-290, 2021, DOI:10.32604/cmc.2020.011907

Abstract In this article, we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations. Convergence analysis proved that the order of convergence of the family of derivative free simultaneous iterative method is nine. Our main aim is to check out the most regularly used simultaneous iterative methods for finding all roots of non-linear equations by studying their dynamical planes, numerical experiments and CPU time-methodology. Dynamical planes of iterative methods are drawn by using MATLAB for the comparison of global convergence properties of simultaneous… More >