Abidhan Bardhan¹, Priyadip Manna¹, Vinay Kumar¹, Avijit Burman¹, Bojan Žlender², Pijush Samui^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1033-1067, 2021, DOI:10.32604/cmes.2021.015885

Abstract In many civil engineering projects, Piled Raft Foundations (PRFs) are usually preferred where the incoming load from the superstructures is very high. In geotechnical engineering practice, the settlement of soil layers is a critical issue for the serviceability of the structures. Thus, assessment of risk associated with the structures corresponding to the maximum allowable settlement of soils needs to be carried out in the design phase. In this study, reliability analysis of PRF based on settlement criteria is performed using a high-performance hybrid soft computing model. The new approach is an integration of the artificial neural network (ANN) and a… More >

Ying Wang^*, Haoran Shi, Shibo Ren

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 967-983, 2021, DOI:10.32604/cmes.2021.015792

Abstract The corrosion of reinforcement in the concrete will cause the effective cross-sectional area of reinforcement to be weakened and the performance of reinforcement to change and lead to the degradation of the bond behavior between reinforcement and concrete, which can seriously affect the mechanical properties of the structural elements. Therefore, it is of great practical significance to accurately simulate the corrosion morphology and the corrosion products of reinforcement. This paper improves the previous cellular automata models and establishes a new cellular automata model framework for simulating the random pitting corrosion process of reinforcement in concrete. This model defines the detailed… More >

Rina Okuyama¹, Naoto Mitsume², Hideki Fujii¹, Hideaki Uchida^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 949-965, 2021, DOI:10.32604/cmes.2021.015773

Abstract As the number of automobiles continues to increase year after year, the associated problem of traffic congestion has become a serious societal issue. Initiatives to mitigate this problem have considered methods for optimizing traffic volumes in wide-area road networks, and traffic-flow simulation has become a focus of interest as a technique for advance characterization of such strategies. Classes of models commonly used for traffic-flow simulations include microscopic models based on discrete vehicle representations, macroscopic models that describe entire traffic-flow systems in terms of average vehicle densities and velocities, and mesoscopic models and hybrid (or multiscale) models incorporating both microscopic and… More >

Ming-Chih Chen, Yin-Ting Cheng^*, Ru-Wei Chen

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1103-1119, 2021, DOI:10.32604/cmes.2021.015589

Abstract This work presents a fall detection system based on artificial intelligence. The system incorporates miniature wearable devices for fall detection. Fall detection is achieved by integrating a three-axis gyroscope and a three-axis accelerometer. The system gathers the differential data collected by the gyroscope and accelerometer, applies artificial intelligence algorithms for model training and constructs an effective model for fall detection. To provide easy wearing and effective position detection, it is designed as a small device attached to the user’s waist. Experiment results have shown that the accuracy of the proposed fall detection model is up to 98%, demonstrating the effectiveness… More >

Ravi Shanker Dubey¹, Dumitru Baleanu^2,3, Manvendra Narayan Mishra^1,*, Pranay Goswami⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1247-1263, 2021, DOI:10.32604/cmes.2021.015224

Abstract Diabetes is a burning issue in the whole world. It is the imbalance between body glucose and insulin. The study of this imbalance is very much needed from a research point of view. For this reason, Bergman gave an important model named-Bergman minimal model. In the present work, using Caputo-Fabrizio (CF) fractional derivative, we generalize Bergman’s minimal blood glucose-insulin model. Further, we modify the old model by including one more component known as diet D(t), which is also essential for the blood glucose model. We solve the modified model with the help of Sumudu transform and fixed-point iteration procedures. Also,… More >

Sultan Alamri^1,*, Kartini Nurfalah², Kiki Adhinugraha³

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 927-948, 2021, DOI:10.32604/cmes.2021.014852

Abstract An indoor trajectory is the path of an object moving through corridors and stairs inside a building. There are various types of technologies that can be used to reconstruct the path of a moving object and detect its position. GPS has been used for reconstruction in outdoor environments, but for indoor environments, mobile devices with embedded sensors are used. An accelerometer sensor and a magnetometer sensor are used to detect human movement and reconstruct the trajectory on a single floor. In an indoor environment, there are many activities that will create the trajectory similar to an outdoor environment, such as… More >

Chaowei Lin^1,#, Feifei Lee^1,#,*, Jiawei Cai¹, Hanqing Chen¹, Qiu Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 985-1006, 2021, DOI:10.32604/cmes.2021.014522

Abstract Scene recognition is a fundamental task in computer vision, which generally includes three vital stages, namely feature extraction, feature transformation and classification. Early research mainly focuses on feature extraction, but with the rise of Convolutional Neural Networks (CNNs), more and more feature transformation methods are proposed based on CNN features. In this work, a novel feature transformation algorithm called Graph Encoded Local Discriminative Region Representation (GEDRR) is proposed to find discriminative local representations for scene images and explore the relationship between the discriminative regions. In addition, we propose a method using the multi-head attention module to enhance and fuse convolutional… More >

BIOCELL, Vol.45, Suppl.3, pp. 1-117, 2021

Abstract This article has no abstract. More >

Yu Xue^1,*, Asma Aouari¹, Romany F. Mansour², Shoubao Su³

Journal of Cyber Security, Vol.3, No.2, pp. 117-124, 2021, DOI:10.32604/jcs.2021.017018

Abstract One of the main problems of machine learning and data mining is to develop a basic model with a few features, to reduce the algorithms involved in classification’s computational complexity. In this paper, the collection of features has an essential importance in the classification process to be able minimize computational time, which decreases data size and increases the precision and effectiveness of specific machine learning activities. Due to its superiority to conventional optimization methods, several metaheuristics have been used to resolve FS issues. This is why hybrid metaheuristics help increase the search and convergence rate of the critical algorithms. A… More >

Prakhar Sahu^1,*, S. K. Singh¹, Arun Kumar Singh²

Journal of Cyber Security, Vol.3, No.2, pp. 107-115, 2021, DOI:10.32604/jcs.2021.020831

Abstract Industry 4.0 is one of the hot topic of today’s world where everything in the industry will be data driven and technological advancements will take place accordingly. In the fourth phase of industrial revolution, manufacturers are dependent upon data produced by the consumers to invent, innovate or change anything for the product. Internet of things devices like OBD, RFID, IIoT, Smart devices are the major source of data generation and represents trends in the industry. Since the IoT device are vulnerable to hackers due to its limitation, consumer data security should be tighten up and enhanced. This paper gives an… More >