Marwa M. Eid^1,*, Fawaz Alassery², Abdelhameed Ibrahim³, Mohamed Saber⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4627-4641, 2022, DOI:10.32604/cmc.2022.024043 - 14 January 2022

Abstract Digital signal processing of electroencephalography (EEG) data is now widely utilized in various applications, including motor imagery classification, seizure detection and prediction, emotion classification, mental task classification, drug impact identification and sleep state classification. With the increasing number of recorded EEG channels, it has become clear that effective channel selection algorithms are required for various applications. Guided Whale Optimization Method (Guided WOA), a suggested feature selection algorithm based on Stochastic Fractal Search (SFS) technique, evaluates the chosen subset of channels. This may be used to select the optimum EEG channels for use in Brain-Computer Interfaces More >

El-Sayed M. El-kenawy^1,2, Abdelhameed Ibrahim^3,*, Seyedali Mirjalili^4,5, Yu-Dong Zhang⁶, Shaima Elnazer^7,8, Rokaia M. Zaki^9,10

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4989-5003, 2022, DOI:10.32604/cmc.2022.023884 - 14 January 2022

Abstract Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance. Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas. Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas. Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today's technology. The accuracy of the forecast is mostly determined by the model used. The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of… More >

Faisal Saeed^1,2,*, Mohammad Al-Sarem^1,3, Muhannad Al-Mohaimeed¹, Abdelhamid Emara^1,4, Wadii Boulila^1,5, Mohammed Alasli¹, Fahad Ghabban¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5639-5658, 2022, DOI:10.32604/cmc.2022.023124 - 14 January 2022

Abstract Several millions of people suffer from Parkinson's disease globally. Parkinson's affects about 1% of people over 60 and its symptoms increase with age. The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners, but which could be analyzed using recorded speech signals. With the huge advancements of technology, the medical data has increased dramatically, and therefore, there is a need to apply data mining and machine learning methods to extract new knowledge from this data. Several classification methods were used to analyze medical data sets and diagnostic… More >

Salaheddine Kably^1,2,*, Mounir Arioua¹, Nabih Alaoui²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5271-5291, 2022, DOI:10.32604/cmc.2022.020833 - 14 January 2022

Abstract Blockchain technology is regarded as the emergent security solution for many applications related to the Internet of Things (IoT). In concept, blockchain has a linear structure that grows with the number of transactions entered. This growth in size is the main obstacle to the blockchain, which makes it unsuitable for resource-constrained IoT environments. Moreover, conventional consensus algorithms such as PoW, PoS are very computationally heavy. This paper solves these problems by introducing a new lightweight blockchain structure and lightweight consensus algorithm. The Multi-Zone Direct Acyclic Graph (DAG) Blockchain (Multizone-DAG-Blockchain) framework is proposed for the fog-based IoT… More >

Huizhong Sun¹, Guosheng Xu^1,*, Zhimin Wu², Ruijie Quan³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 585-600, 2022, DOI:10.32604/iasc.2022.023874 - 05 January 2022

Abstract With the rapid development of Android devices, Android is currently one of the most popular mobile operating systems. However, it is also believed to be an entry point of many attack vectors. The existing Android malware detection method does not fare well when dealing with complex and intelligent malware applications, especially those based on feature detection systems which have become increasingly elusive. Therefore, we propose a novel feature selection algorithm called frequency differential selection (FDS) and weight measurement for Android malware detection. The purpose is to solve the shortcomings of the existing feature selection algorithms… More >

S. Aravindkumar^*, P. Varalakshmi

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 601-617, 2022, DOI:10.32604/iasc.2022.023783 - 05 January 2022

Abstract

Traffic related accidents and route congestions remain to dwell significant issues in the globe. To overcome this, VANET was proposed to enhance the traffic management. However, there are several drawbacks in VANET such as collision of vehicles, data transmission in high probability of network fragmentation and data congestion. To overcome these issues, the Enhanced Pigeon Inspired Optimization (EPIO) and the Adaptive Neuro Fuzzy Inference System (ANFIS) based methods have been proposed. The Cluster Head (CH) has been selected optimally using the EPIO approach, and then the ANFIS has been used for updating and validating the

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M. T. Mastura^1,*, R. Nadlene², R. Jumaidin¹, S. I. Abdul Kudus¹, M. R. Mansor², H. M. S. Firdaus¹

Journal of Renewable Materials, Vol.10, No.5, pp. 1221-1238, 2022, DOI:10.32604/jrm.2022.018082 - 22 December 2021

Abstract The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments. Moreover, selection of suitable natural fibres for fused deposition modeling should be performed before the development of the composites. It could not be performed without identifying selection criteria that comprehend both materials and fused deposition modeling process requirements. Therefore, in this study, integration of the Analytic Hierarchy Process (AHP)/Analytic Network Process (ANP) has been introduced in selecting the natural fibres based in different clusters of selection concurrently. The selection… More >

CANGZHI JIA¹, DONG JIN¹, XIN WANG¹, QI ZHAO^2,*

BIOCELL, Vol.46, No.4, pp. 1105-1121, 2022, DOI:10.32604/biocell.2022.016655 - 15 December 2021

Abstract N⁶-Methyladenine is a dynamic and reversible post translational modification, which plays an essential role in various biological processes. Because of the current inability to identify m6A-containing mRNAs, computational approaches have been developed to identify m6A sites in DNA sequences. Aiming to improve prediction performance, we introduced a novel ensemble computational approach based on three hybrid deep neural networks, including a convolutional neural network, a capsule network, and a bidirectional gated recurrent unit (BiGRU) with the self-attention mechanism, to identify m6A sites in four tissues of three species. Across a total of 11 datasets, we selected different More >

D. Ajay¹, J. Aldring¹, G. Rajchakit², P. Hammachukiattikul³, N. Boonsatit^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1033-1076, 2022, DOI:10.32604/cmes.2022.018267 - 13 December 2021

Abstract In this paper, sine trigonometry operational laws (ST-OLs) have been extended to neutrosophic sets (NSs) and the operations and functionality of these laws are studied. Then, extending these ST-OLs to complex neutrosophic sets (CNSs) forms the core of this work. Some of the mathematical properties are proved based on ST-OLs. Fundamental operations and the distance measures between complex neutrosophic numbers (CNNs) based on the ST-OLs are discussed with numerical illustrations. Further the arithmetic and geometric aggregation operators are established and their properties are verified with numerical data. The general properties of the developed sine trigonometry… More >

D. Palanikkumar¹, Kamal Upreti², S. Venkatraman^3,*, J. Roselin Suganthi⁴, Sridharan Kannan⁵, S. Srinivasan⁶

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1843-1854, 2022, DOI:10.32604/iasc.2022.023350 - 09 December 2021

Abstract The Selection of the mining method for underground minerals extraction is the crucial task for the mining engineers. Underground minerals extraction is a multi-criteria decision making problem due to many criteria to be considered in the selection process. There are many studies on selection of underground mining method using Multi Criteria Decision Making (MCDM) techniques or approaches. Extracting minerals from the underground involves many geological characteristics also called as input parameters. The geological characteristics of any mineral deposit vary from one location to another location. Thus only one mineral extraction method is not suitable for… More >