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 >

A. Baseera¹, Abeer Abdullah Alsadhan^2,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4713-4726, 2022, DOI:10.32604/cmc.2022.029538

Abstract In the development of technology in various fields like big data analysis, data mining, big data, cloud computing, and blockchain technology, security become more constrained. Blockchain is used in providing security by encrypting the sharing of information. Blockchain is applied in the peer-to-peer (P2P) network and it has a decentralized ledger. Providing security against unauthorized breaches in the distributed network is required. To detect unauthorized breaches, there are numerous techniques were developed and those techniques are inefficient and have poor data integrity. Hence, a novel technique needs to be implemented to tackle the new breaches in the distributed network. This… More >

M. Usharani^1,*, B. Sakthivel², S. Gayathri Priya³, T. Nagalakshmi⁴, J. Shirisha⁵

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1647-1657, 2023, DOI:10.32604/csse.2023.027744

Abstract Approximate computing is a popular field for low power consumption that is used in several applications like image processing, video processing, multimedia and data mining. This Approximate computing is majorly performed with an arithmetic circuit particular with a multiplier. The multiplier is the most essential element used for approximate computing where the power consumption is majorly based on its performance. There are several researchers are worked on the approximate multiplier for power reduction for a few decades, but the design of low power approximate multiplier is not so easy. This seems a bigger challenge for digital industries to design an… More >

Kavitha Muthukumaran^*, K. Hariharanath

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 521-536, 2023, DOI:10.32604/iasc.2023.025968

Abstract Recently, data science techniques utilize artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to take an influence and grow their businesses. For SMEs, owing to the inexistence of consistent data and other features, evaluating credit risks is difficult and costly. On the other hand, it becomes necessary to design efficient models for predicting business failures or financial crises of SMEs. Various data classification approaches for financial crisis prediction (FCP) have been presented for predicting the financial status of the organization by the use of past data. A major process involved in the design of FCP… More >

Weijian Zhang^1,*, Hao Wang², Hao Hua³, Qirun Wang⁴

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1861-1875, 2022, DOI:10.32604/iasc.2022.030274

Abstract As a kind of distributed, decentralized and peer-to-peer transmitted technology, blockchain technology has gradually changed people’s lifestyle. However, blockchain technology also faces many problems including selfish mining attack, which causes serious effects to the development of blockchain technology. Selfish mining is a kind of mining strategy where selfish miners increase their profit by selectively publishing hidden blocks. This paper builds the selfish mining model from the perspective of node state conversion and utilize the function extremum method to figure out the optimal profit of this model. Meanwhile, based on the experimental data of honest mining, the author conducts the simulation… 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 >

Siyuan Mei^1,2, Yingyi Chen^1,2,*, Hanxiang Qin^1,2, Huihui Yu³, Daoliang Li^1,2, Boyang Sun^1,2, Ling Yang^1,2, Yeqi Liu^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1315-1335, 2022, DOI:10.32604/cmes.2022.019378

Abstract Fish behavior analysis for recognizing stress is very important for fish welfare and production management in aquaculture. Recent advances have been made in fish behavior analysis based on deep learning. However, most existing methods with top performance rely on considerable memory and computational resources, which is impractical in the real-world scenario. In order to overcome the limitations of these methods, a new method based on knowledge distillation is proposed to identify the stress states of fish schools. The knowledge distillation architecture transfers additional inter-class information via a mixed relative loss function, and it forces a lightweight network (GhostNet) to mimic… More >

Marwah Mohammad Almasri^1,*, Abrar Mohammed Alajlan²

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1687-1710, 2022, DOI:10.32604/iasc.2022.023240

Abstract Wireless Sensor Networks (WSN) comprise numerous sensor nodes for monitoring specific areas. Great deals of efforts have been achieved to obtain effective routing approaches using clustering methods. Clustering is considered an effective way to provide a better route for transmitting the data, but cluster head selection and route generation is considered as a complicated task. To manage such complex issues and to enhance network lifetime and energy consumption, an energy-effective cluster-based routing approach is proposed. As the major intention of this paper is to select an optimal cluster head, this paper proposes a modified golden eagle optimization (M-GEO) algorithm to… More >

S. Premkumar Deepak^*, M. B. Mukeshkrishnan

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 963-978, 2022, DOI:10.32604/iasc.2022.022126

Abstract Underwater wireless sensor networks (UWSNs) are promising, emerging technologies for the applications in oceanic research. UWSN contains high number of sensor nodes and autonomous underwater vehicles that are deployed to perform the data transmission in the sea. In UWSN networks, the sensors are placed in the buoyant which are highly vulnerable to selfish behavioural attack. In this paper, the major challenges in finding secure and optimal route navigation in UWSN are identified and in order to address them, Entropy based ACO algorithm (E-ACO) is proposed for secure route selection. Moreover, the Selfish Node Recovery (SNR) using the Grasshopper Optimisation Algorithm… More >