Kashif Iqbal^1,2, Sagheer Abbas¹, Muhammad Adnan Khan^3,*, Atifa Athar⁴, Muhammad Saleem Khan¹, Areej Fatima³, Gulzar Ahmad¹

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1595-1612, 2021, DOI:10.32604/cmc.2020.013231 - 26 November 2020

Abstract The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic… More >

Mengcheng Sun^1,2, Weiya Xu^1,2,*, Huanling Wang^1,3, Qingxiang Meng^1,2, Long Yan^1,2, Wei-Chau Xie⁴

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1057-1074, 2021, DOI:10.32604/cmc.2020.012537 - 30 October 2020

Abstract The narrowing deformation of reservoir valley during the initial operation period threatens the long-term safety of the dam, and an accurate prediction of valley deformation (VD) remains a challenging part of risk mitigation. In order to enhance the accuracy of VD prediction, a novel hybrid model combining Ensemble empirical mode decomposition based interval threshold denoising (EEMD-ITD), Differential evolutions—Shuffled frog leaping algorithm (DE-SFLA) and Least squares support vector machine (LSSVM) is proposed. The non-stationary VD series is firstly decomposed into several stationary subseries by EEMD; then, ITD is applied for redundant information denoising on special sub-series,… More >

Basharat Ullah¹, Umar Khan¹, Hafiz Abdul Wahab¹, Ilyas Khan^2,*, Dumitru Baleanu^3,4,5, Kottakkaran Sooppy Nisar⁶

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 947-960, 2021, DOI:10.32604/cmc.2020.012430 - 30 October 2020

Abstract The investigation of Thermal performance in nanofluids and hybrid nanofluids over a curved stretching infinite region strengthens its roots in engineering and industry. Therefore, the comparative thermal analysis in SiO₂–H₂O and (MoS₂–SiO₂)–H₂O is conducted over curved stretching surface. The model is reduced in the dimensional version via similarity transformation and then treated numerically. The velocity and thermal behavior for both the fluids is decorated against the preeminent parameters. From the analysis, it is examined that the motion of under consideration fluids declines against Fr and λ. The thermal performance enhances for higher volumetric fraction and λ. More >

Rizwan Ali Naqvi¹, Dildar Hussain², Woong-Kee Loh^3,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 715-732, 2021, DOI:10.32604/cmc.2020.013249 - 30 October 2020

Abstract Multiple ocular region segmentation plays an important role in different applications such as biometrics, liveness detection, healthcare, and gaze estimation. Typically, segmentation techniques focus on a single region of the eye at a time. Despite the number of obvious advantages, very limited research has focused on multiple regions of the eye. Similarly, accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur, ghost effects low resolution, off-angles, and unusual glints. Currently, the available segmentation methods cannot address these constraints. In this paper, to address the accurate segmentation of multiple eye regions in… More >

Alaa K. Khamis^a , Allal Bakali^a, A. A. El-Bary^b,c,*, Haitham M. Atef^d

Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-6, 2020, DOI:10.5098/hmt.15.24

Abstract In this paper the effect of the magnetic field and Seebeck parameter was investigated. Modified Ohm's law that includes effects of the temperature gradient (Seebeck effect More >

Hai Liu^1,*, Xiangchao Zhou^2,3

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1493-1501, 2020, DOI:10.32604/iasc.2020.012159 - 24 December 2020

Abstract Aiming at the problems of poor brightness control effect and low registration accuracy in traditional multi focus image registration, a wavelet multi-scale multi focus image region fusion registration method is proposed. The multi-scale Retinex algorithm is used to enhance the image, the wavelet decomposition similarity analysis is used for image interpolation, and the EMD method is used to decompose the multi focus image. Finally, the image reconstruction is completed and the multi focus image registration is realized. In order to verify the multi focus image fusion registration effect of different methods, a comparative experiment was More >

Liang Ce, Yongchen Pan^*

FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.6, pp. 1115-1128, 2020, DOI:10.32604/fdmp.2020.010829 - 17 December 2020

Abstract Two flow cases for scaled high speed train models with different length are numerically analyzed in the framework of the improved delayed detachededdy simulation model. Specific attention is paid to the shear flows and related mechanisms in the near turbulent wake created by these moving models. In particular, a comparative analysis is made on the distributions of turbulent kinetic energy (TKE) and turbulence production (TP) in planes perpendicular to the streamwise direction. The numerical results suggest that, in the wake region very close to the tail, significant TKE and TP can be ascribed to the More >

Kun Liu^*

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 749-754, 2020, DOI:10.32604/iasc.2020.010109

Abstract In the English network examination system, the big data distribution is highly coupled, the cost of data query is large, and the precision is not good. In order to improve the ability of the data classification and query in the English network examination system, a method of data classification and query in the English network examination system is proposed based on the grid region clustering and frequent itemset feature extraction of the association rules. Using the grid image analysis to improve the statistical analysis of the English performance analysis, the collection and storage structure analysis… More >

Lan Yang¹, Shun Qi^2,3,#, Chen Qiao^1,*, Yanmei Kang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 215-237, 2020, DOI:10.32604/cmes.2020.010796 - 18 September 2020

Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both… More >

Malik Javed Akhtar¹, Zahur Ahmad¹, Rashid Amin^{1, *}, Sultan H. Almotiri², Mohammed A. Al Ghamdi², Hamza Aldabbas³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2639-2663, 2020, DOI:10.32604/cmc.2020.011485 - 16 September 2020

Abstract A large amount of data is present on the web which can be used for useful purposes like a product recommendation, price comparison and demand forecasting for a particular product. Websites are designed for human understanding and not for machines. Therefore, to make data machine-readable, it requires techniques to grab data from web pages. Researchers have addressed the problem using two approaches, i.e., knowledge engineering and machine learning. State of the art knowledge engineering approaches use the structure of documents, visual cues, clustering of attributes of data records and text processing techniques to identify data… More >