Yuanbang Li^*, Wengang Zhou, Chi Xu, Yuchun Shi

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1365-1386, 2022, DOI:10.32604/cmes.2022.019656

Abstract With the widespread use of mobile phones, users can share their location and activity anytime, anywhere, as a form of check-in data. These data reflect user features. Long-term stability and a set of user-shared features can be abstracted as user roles. This role is closely related to the users’ social background, occupation, and living habits. This study makes four main contributions to the literature. First, user feature models from different views for each user are constructed from the analysis of the check-in data. Second, the K-means algorithm is used to discover user roles from user features. Third, a reinforcement learning… More >

Yanfei Sun¹, Feng Qiao², Wei Wang¹, Bin Xu¹, Jianming Zhu¹, Romany Fouad Mansour³, Jin Qi^1,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2825-2843, 2022, DOI:10.32604/cmc.2022.026574

Abstract As a new mode and means of smart manufacturing, smart cloud manufacturing (SCM) faces great challenges in massive supply and demand, dynamic resource collaboration and intelligent adaptation. To address the problem, this paper proposes an SCM-oriented dynamic supply-demand (S-D) intelligent adaptation model for massive manufacturing services. In this model, a collaborative network model is established based on the properties of both the supply-demand and their relationships; in addition, an algorithm based on deep graph clustering (DGC) and aligned sampling (AS) is used to divide and conquer the large adaptation domain to solve the problem of the slow computational speed caused… More >

Yanbin Tan¹, Xingwen He^1,*, Lei Shi², Shi Zheng³, Zhe Zhang¹, Xinshan Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1041-1061, 2022, DOI:10.32604/cmes.2022.018543

Abstract To numerically evaluate the reinforcement effect on dynamic characteristics of a concrete-filled steel tube arch bridge with vibration problems, a 12-degree-of-freedom sprung-mass dynamic vehicle model and a 3D finite element bridge model were established. Then, the coupled equations of vehicle-bridge interaction were derived and a computer program was developed using the FORTRAN language. This program can accurately simulate vehicle-bridge coupled vibration considering the bumping effect and road surface irregularity during motion of the vehicle. The simulated results were compared with those of relevant literatures to verify the correctness of the self-developed program. Then, three reinforcement schemes for the bridge (Addition… More >

Kexin Zhang^*, Tianyu Qi, Dachao Li, Xingwei Xue, Yanfeng Li

Structural Durability & Health Monitoring, Vol.16, No.1, pp. 53-80, 2022, DOI:10.32604/sdhm.2021.016130

Abstract This paper presents the method of reinforcing main girder of reinforced concrete cable-stayed bridge with prestressed steel strands. To verify the effectiveness of external prestressed strand reinforcement method. Static load tests and health monitoring-based assessment were carried out before and after reinforcement. Field load test shows that the deflection and stress values of the main girder are reduced by 10%~20% after reinforcement, and the flexural strength and stiffness of the strengthened beam are improved. The deflection and strain data of health monitoring of the specified section are collected. The deflection of the second span is 4 mm~10 mm, the strain… More >

Mesfer Al Duhayyim¹, Taiseer Abdalla Elfadil Eisa², Fahd N. Al-Wesabi^3,4, Abdelzahir Abdelmaboud⁵, Manar Ahmed Hamza^6,*, Abu Sarwar Zamani⁶, Mohammed Rizwanullah⁶, Radwa Marzouk^7,8

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5699-5715, 2022, DOI:10.32604/cmc.2022.024431

Abstract The Smart City concept revolves around gathering real time data from citizen, personal vehicle, public transports, building, and other urban infrastructures like power grid and waste disposal system. The understandings obtained from the data can assist municipal authorities handle assets and services effectually. At the same time, the massive increase in environmental pollution and degradation leads to ecological imbalance is a hot research topic. Besides, the progressive development of smart cities over the globe requires the design of intelligent waste management systems to properly categorize the waste depending upon the nature of biodegradability. Few of the commonly available wastes are… More >

Moath Alsafasfeh^1,*, Zaid A. Arida², Omar A. Saraereh³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5355-5380, 2022, DOI:10.32604/cmc.2022.024093

Abstract Deep neural networks (DNN) are widely employed in a wide range of intelligent applications, including image and video recognition. However, due to the enormous amount of computations required by DNN. Therefore, performing DNN inference tasks locally is problematic for resource-constrained Internet of Things (IoT) devices. Existing cloud approaches are sensitive to problems like erratic communication delays and unreliable remote server performance. The utilization of IoT device collaboration to create distributed and scalable DNN task inference is a very promising strategy. The existing research, on the other hand, exclusively looks at the static split method in the scenario of homogeneous IoT… More >

S. Lakshmi Durga¹, Ch. Rajeshwari¹, Khalid Hamed Allehaibi², Nishu Gupta^3,*, Nasser Nammas Albaqami⁴, Isha Bharti⁵, Ahmad Hoirul Basori⁶

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 1-19, 2022, DOI:10.32604/iasc.2022.022536

Abstract In recent years, the demand for smart wireless communication technology has increased tremendously, and it urges to extend internet services globally with high reliability, less cost and minimal delay. In this connection, low earth orbit (LEO) satellites have played prominent role by reducing the terrestrial infrastructure facilities and providing global coverage all over the earth with the help of satellite internet of things (SIoT). LEO satellites provide wide coverage area to dynamically accessing network with limited resources. Presently, most resource allocation schemes are designed only for geostationary earth orbit (GEO) satellites. For LEO satellites, resource allocation is challenging due to… More >

Faizan Rasheed¹, Kok-Lim Alvin Yau², Rafidah Md Noor³, Yung-Wey Chong^4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2225-2247, 2022, DOI:10.32604/cmc.2022.022952

Abstract This paper investigates the use of multi-agent deep Q-network (MADQN) to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning (MARL) approach. The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions, particularly rainfall. MADQN is based on deep Q-network (DQN), which is an integration of the traditional reinforcement learning (RL) and the newly emerging deep learning (DL) approaches. MADQN enables traffic light controllers to learn, exchange knowledge with neighboring agents, and select optimal joint actions in a collaborative manner. A case study based on a real traffic… More >

Xin Liu¹, Siya Xu¹, Chao Yang², Zhili Wang^1,*, Hao Zhang³, Jingye Chi¹, Qinghan Li⁴

Computer Systems Science and Engineering, Vol.42, No.1, pp. 271-287, 2022, DOI:10.32604/csse.2022.022103

Abstract With the development of internet of vehicles, the traditional centralized content caching mode transmits content through the core network, which causes a large delay and cannot meet the demands for delay-sensitive services. To solve these problems, on basis of vehicle caching network, we propose an edge collaborative caching scheme. Road side unit (RSU) and mobile edge computing (MEC) are used to collect vehicle information, predict and cache popular content, thereby provide low-latency content delivery services. However, the storage capacity of a single RSU severely limits the edge caching performance and cannot handle intensive content requests at the same time. Through… More >

R. Kanthavel^1,*, R. Dhaya²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 257-269, 2022, DOI:10.32604/csse.2022.021606

Abstract Osteoarthritis is the most common class of arthritis that involves tears down the soft cartilage between the joints of the knee. The regeneration of this cartilage tissue is not possible, and thus physicians typically suggest therapeutic measures to prevent further deterioration over time. Normally, bringing about joint replacement is a remedial course of action. Expose itself in joint pain recognized with a normal X-ray. Deep learning plays a vital role in predicting the early stages of osteoarthritis by using the MRI pictures of muscles of the knee muscle. It can be used to accurately measure the shape and texture of… More >