Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Mohamed K. Nour⁴, Mashael M. Asiri⁵, Ali M. Al-Sharafi⁶, Mahmoud Othman⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 607-621, 2023, DOI:10.32604/cmc.2023.031371

Abstract Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation,… More >

Saud S. Alotaibi¹, Eatedal Alabdulkreem², Sami Althahabi³, Manar Ahmed Hamza^4,*, Mohammed Rizwanullah⁴, Abu Sarwar Zamani⁴, Abdelwahed Motwakel⁴, Radwa Marzouk⁵

Computer Systems Science and Engineering, Vol.45, No.1, pp. 737-751, 2023, DOI:10.32604/csse.2023.030170

Abstract Sentiment analysis or opinion mining (OM) concepts become familiar due to advances in networking technologies and social media. Recently, massive amount of text has been generated over Internet daily which makes the pattern recognition and decision making process difficult. Since OM find useful in business sectors to improve the quality of the product as well as services, machine learning (ML) and deep learning (DL) models can be considered into account. Besides, the hyperparameters involved in the DL models necessitate proper adjustment process to boost the classification process. Therefore, in this paper, a new Artificial Fish Swarm Optimization with Bidirectional Long… More >

Basim Aljabhan¹, Mahmoud Ragab^2,3,4,*, Sultanah M. Alshammari^4,5, Abdullah S. Al-Malaise Al-Ghamdi^4,6,7

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5269-5282, 2022, DOI:10.32604/cmc.2022.030694

Abstract Traffic flow prediction becomes an essential process for intelligent transportation systems (ITS). Though traffic sensor devices are manually controllable, traffic flow data with distinct length, uneven sampling, and missing data finds challenging for effective exploitation. The traffic data has been considerably increased in recent times which cannot be handled by traditional mathematical models. The recent developments of statistic and deep learning (DL) models pave a way for the effectual design of traffic flow prediction (TFP) models. In this view, this study designs optimal attention-based deep learning with statistical analysis for TFP (OADLSA-TFP) model. The presented OADLSA-TFP model intends to effectually… More >

Medhat A. Tawfeek^1,2,*, Saad Alanazi¹, A. A. Abd El-Aziz^3,4

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6091-6106, 2022, DOI:10.32604/cmc.2022.028391

Abstract The alignment operation between many protein sequences or DNA sequences related to the scientific bioinformatics application is very complex. There is a trade-off in the objectives in the existing techniques of Multiple Sequence Alignment (MSA). The techniques that concern with speed ignore accuracy, whereas techniques that concern with accuracy ignore speed. The term alignment means to get the similarity in different sequences with high accuracy. The more growing number of sequences leads to a very complex and complicated problem. Because of the emergence; rapid development; and dependence on gene sequencing, sequence alignment has become important in every biological relationship analysis… More >

Ganeshan Keerthana^1,*, Panneerselvam Anandan², Nandhagopal Nachimuthu³

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 903-917, 2021, DOI:10.32604/cmc.2020.012255

Abstract Due to the recent proliferation of cyber-attacks, highly robust wireless sensor networks (WSN) become a critical issue as they survive node failures. Scale-free WSN is essential because they endure random attacks effectively. But they are susceptible to malicious attacks, which mainly targets particular significant nodes. Therefore, the robustness of the network becomes important for ensuring the network security. This paper presents a Robust Hybrid Artificial Fish Swarm Simulated Annealing Optimization (RHAFS-SA) Algorithm. It is introduced for improving the robust nature of free scale networks over malicious attacks (MA) with no change in degree distribution. The proposed RHAFS-SA is an enhanced… More >

Sheng Bai, Feng Bao^*, Fengzhi Zhao, Miaomiao Liu

FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.5, pp. 935-946, 2020, DOI:10.32604/fdmp.2020.010113

Abstract The main objective of the present study is the development of a new algorithm that can adapt to complex and changeable environments. An artificial fish swarm algorithm is developed which relies on a wireless sensor network (WSN) in a hydrodynamic background. The nodes of this algorithm are viscous fluids and artificial fish, while related ‘events’ are directly connected to the food available in the related virtual environment. The results show that the total processing time of the data by the source node is 6.661 ms, of which the processing time of crosstalk data is 3.789 ms, accounting for 56.89%. The… More >