Mamouni El Mamoun^1,*, Zennaki Mahmoud¹, Sadouni Kaddour¹

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 995-1008, 2019, DOI:10.32604/cmc.2019.08081

Abstract Using Support Vector Machine (SVM) requires the selection of several parameters such as multi-class strategy type (one-against-all or one-against-one), the regularization parameter C, kernel function and their parameters. The choice of these parameters has a great influence on the performance of the final classifier. This paper considers the grid search method and the particle swarm optimization (PSO) technique that have allowed to quickly select and scan a large space of SVM parameters. A comparative study of the SVM models is also presented to examine the convergence speed and the results of each model. SVM is applied to handwritten Arabic characters… More >

K. A. Gepreel^1,2, A. M. S. Mahdy^1,2,*, M. S. Mohamed^1,3, A. Al-Amiri⁴

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 979-994, 2019, DOI:10.32604/cmc.2019.07701

Abstract In this paper, we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model. The reduced differential transforms method (RDTM) is one of the interesting methods for finding the approximate solutions for nonlinear problems. We apply the RDTM to discuss the analytic approximate solutions to the SI1I2R model for the spread of virus HCV-subtype and SIR childhood disease model. We discuss the numerical results at some special values of parameters in the approximate solutions. We use the computer software package such… More >

Duyen Le Hien Nguyen¹, Dieu Thi Thanh Do², Jaehong Lee², Timon Rabczuk³, Hung Nguyen-Xuan^1,4,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 951-977, 2019, DOI:10.32604/cmc.2019.08001

Abstract We in this paper exploit time series algorithm based deep learning in forecasting damage mechanics problems. The methodologies that are able to work accurately for less computational and resolving attempts are a significant demand nowadays. Relied on learning an amount of information from given data, the long short-term memory (LSTM) method and multi-layer neural networks (MNN) method are applied to predict solutions. Numerical examples are implemented for predicting fracture growth rates of L-shape concrete specimen under load ratio, single-edge-notched beam forced by 4-point shear and hydraulic fracturing in permeable porous media problems such as storage-toughness fracture regime and fracture-height growth… More >

I-Ching Hsu^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 929-950, 2019, DOI:10.32604/cmc.2019.07876

Abstract Considering cloud computing from an organizational and end user computing point of view, it is a new paradigm for deploying, managing and offering services through a shared infrastructure. Current development of cloud computing applications, however, are the lack of a uniformly approach to cope with the heterogeneous information fusion. This leads cloud computing to inefficient development and a low potential reuse. This study addresses these issues to propose a novel Web 2.0 Mashups as a Service, called WMaaS, which is a fundamental cloud service model. The WMaaS is developed based on a XML-based Mashups Architecture (XMA) that is composed of… More >

Hyun Kyu Shin¹, Yong Han Ahn², Sang Hyo Lee³, Ha Young Kim^4,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 911-928, 2019, DOI:10.32604/cmc.2019.08269

Abstract Compressive strength of concrete is a significant factor to assess building structure health and safety. Therefore, various methods have been developed to evaluate the compressive strength of concrete structures. However, previous methods have several challenges in costly, time-consuming, and unsafety. To address these drawbacks, this paper proposed a digital vision based concrete compressive strength evaluating model using deep convolutional neural network (DCNN). The proposed model presented an alternative approach to evaluating the concrete strength and contributed to improving efficiency and accuracy. The model was developed with 4,000 digital images and 61,996 images extracted from video recordings collected from concrete samples.… More >

P. S. Anoop¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 191-208, 2017, DOI:10.3970/sdhm.2017.011.191

Abstract Tyre pressure monitoring system (TPMS) is compulsory in most countries like the United States and European Union. The existing systems depend on pressure sensors strapped on the tyre or on wheel speed sensor data. A difference in wheel speed would trigger an alarm based on the algorithm implemented. In this paper, machine learning approach is proposed as a new method to monitor tyre pressure by extracting the vertical vibrations from a wheel hub of a moving vehicle using an accelerometer. The obtained signals will be used to compute through statistical features and histogram features for the feature extraction process. The… More >

Guozhong Dai^1,*, Jia Zhu², Guicai Shi³, Yanmin Sheng⁴, Shujin Li⁵

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 169-190, 2017, DOI:10.3970/sdhm.2017.011.169

Abstract As the landfill leachate has strong pollution on the underground water, surface water and soil. This paper develops the formula of impervious slurry with low permeability, good durability, strong adsorption and retardant based on the bentonite which is modified by polyvinyl alcohol. Through the simulation experiment, the optimum formula of polyvinyl alcohol is 0.2%. Its osmotic coefficient for 28 days is 0.53×10-8~1.86×10-8 cm/s and compressive strength is 0.5~1.5 MPa as well. This paper study on the retardant rule of the consolidation of slurry against the pollution in the leachate by self-made percolation instrument. The experiment shows that the retardant rate… More >

T. M. Alamelu Manghai¹, R. Jegadeeshwaran²

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 149-167, 2017, DOI:10.3970/sdhm.2017.011.149

Abstract Hydraulic brakes in automobiles are an important control component used not only for the safety of the passenger but also for others moving on the road. Therefore, monitoring the condition of the brake components is inevitable. The brake elements can be monitored by studying the vibration characteristics obtained from the brake system using a proper signal processing technique through machine learning approaches. The vibration signals were captured using an accelerometer sensor under a various fault condition. The acquired vibration signals were processed for extracting meaningful information as features. The condition of the brake system can be predicted using a feature… More >

Amafabia, Daerefa-a Mitsheal¹, Montalvão, Diogo², David-West, Opukuro¹, Haritos, George¹

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 91-147, 2017, DOI:10.3970/sdhm.2017.011.091

Abstract Structural Health Monitoring (SHM) is the process of collecting, interpreting and analysing data from structures in order to determine its health status and the remaining life span. Composite materials have been extensively use in recent years in several industries with the aim at reducing the total weight of structures while improving their mechanical properties. However, composite materials are prone to develop damage when subjected to low to medium impacts (i.e. 1-10 m/s and 11-30 m/s respectively). Hence, the need to use SHM techniques to detect damage at the incipient initiation in composite materials is of high importance. Despite the availability… More >

K.N. Song¹, S. D. Hong¹

Structural Durability & Health Monitoring, Vol.9, No.2, pp. 155-165, 2013, DOI:10.32604/sdhm.2013.009.155

Abstract The IHX (Intermediate Heat Exchanger) of a VHTR (Very High Temperature Reactor) transfers 950° heat generated from the VHTR to a hydrogen production plant. The Korea Atomic Energy Research Institute (KAERI) has manufactured a lab-scale PCHE (Printed Circuit Heat Exchanger) prototype made of SUS316L under consideration as a candidate. In this study, as a part of a hightemperature structural integrity evaluation of the lab-scale PCHE prototype, a macroscopic structural behavior analysis including structural analysis modeling and a thermal/elastic structural analysis was carried out under the test conditions of a helium experimental loop (HELP) as a precedent study for a performance… More >