Xiangmiao Wan, Yan Tan^*, Xiong Long

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 505-524, 2024, DOI:10.32604/sdhm.2024.049363

Abstract In this study, we assessed the impact of substituting natural fine aggregates with municipal solid waste incineration bottom ash (MSWI-BA) in steel fiber (SF)-reinforced concrete on its compressive properties post high-temperature exposure. The concrete specimens incorporating MSWI-BA as the fine aggregate and SFs for reinforcement underwent uniaxial compression tests after exposure to high temperatures. Through the tests, we investigated the impact of high-temperature exposure on mechanical properties, such as mass loss rate, stress-strain full curve, compressive strength, peak strain, elastic modulus, and so on, over different thermostatic durations. The analysis revealed that with the increasing… More >

Xiabin Zhang^1,2, Zhongyi Hu^1,2,*, Lei Xiao^1,2, Hui Huang^1,2

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2879-2905, 2024, DOI:10.32604/cmc.2024.048725

Abstract Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease (AD). Most studies predominantly employ Convolutional Neural Networks (CNNs), which focus solely on local features, thus encountering difficulties in handling global features. In contrast to natural images, Structural Magnetic Resonance Imaging (sMRI) images exhibit a higher number of channel dimensions. However, during the Position Embedding stage of Multi Head Self Attention (MHSA), the coded information related to the channel dimension is disregarded. To tackle these issues, we propose the RepBoTNet-CESA network, an advanced AD-aided diagnostic model that is capable… More >

Deming Lei, Surui Duan, Mingbo Li^*, Jing Wang

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 47-63, 2024, DOI:10.32604/cmc.2024.049481

Abstract Bottleneck stage and reentrance often exist in real-life manufacturing processes; however, the previous research rarely addresses these two processing conditions in a scheduling problem. In this study, a reentrant hybrid flow shop scheduling problem (RHFSP) with a bottleneck stage is considered, and an elite-class teaching-learning-based optimization (ETLBO) algorithm is proposed to minimize maximum completion time. To produce high-quality solutions, teachers are divided into formal ones and substitute ones, and multiple classes are formed. The teacher phase is composed of teacher competition and teacher teaching. The learner phase is replaced with a reinforcement search of the More >

Yutao Hu¹, Yuntao Zhao^1,*, Yongxin Feng², Xiangyu Ma¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 509-530, 2024, DOI:10.32604/cmc.2024.042216

Abstract In the face of the increasingly severe Botnet problem on the Internet, how to effectively detect Botnet traffic in real-time has become a critical problem. Although the existing deep Q network (DQN) algorithm in Deep reinforcement learning can solve the problem of real-time updating, its prediction results are always higher than the actual results. In Botnet traffic detection, although it performs well in the training set, the accuracy rate of predicting traffic is as high as%; however, in the test set, its accuracy has declined, and it is impossible to adjust its prediction strategy on… More >

Andrei Vasiliev, Andrei Sukhanovskii^*, Elena Popova

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 739-748, 2024, DOI:10.32604/fdmp.2024.048092

Abstract The formation of convective flows in a rotating cylindrical layer with an inclined bottom and free surface is studied. Convection is driven by localized cooling at the center of the upper free surface and by rim heating at the bottom near the sidewall. The horizontal temperature difference in a rotating layer leads to the formation of a convective flow with a complex structure. The mean meridional circulation, consisting of three cells, provides a strongly non-uniform differential rotation. As a result of the instability of the main cyclonic zonal flow, the train of baroclinic waves appears… More >

Xiaoying Chen^1,*, Jie Kang¹, Cong Hu²

Journal of New Media, Vol.6, pp. 1-16, 2024, DOI:10.32604/jnm.2024.045833

Abstract With the development of cities and the prevalence of networks, interpersonal relationships have become increasingly distant. When people crave communication, they hope to find someone to confide in. With the rapid advancement of deep learning and big data technologies, an enabling environment has been established for the development of intelligent chatbot systems. By effectively combining cutting-edge technologies with human-centered design principles, chatbots hold the potential to revolutionize our lives and alleviate feelings of loneliness. A multi-topic chat companion robot based on a state machine has been proposed, which can engage in fluent dialogue with humans… More >

Zhongping Chen, Weigong Zhang^*

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 111-124, 2024, DOI:10.32604/sdhm.2023.043563

Abstract Automatic control technology is the basis of road robot improvement, according to the characteristics of construction equipment and functions, the research will be input type perception from positioning acquisition, real-world monitoring, the process will use RTK-GNSS positional perception technology, by projecting the left side of the earth from Gauss-Krueger projection method, and then carry out the Cartesian conversion based on the characteristics of drawing; steering control system is the core of the electric drive unmanned module, on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles, the steering… More >

Xinlong Diao, Xiao Wang^*, Junkang Qin, Qinmu Wu, Zhiqin He, Xinghong Fan

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2617-2665, 2024, DOI:10.32604/cmc.2024.047377

Abstract In recent years, Artificial Intelligence (AI) has revolutionized people’s lives. AI has long made breakthrough progress in the field of surgery. However, the research on the application of AI in orthopedics is still in the exploratory stage. The paper first introduces the background of AI and orthopedic diseases, addresses the shortcomings of traditional methods in the detection of fractures and orthopedic diseases, draws out the advantages of deep learning and machine learning in image detection, and reviews the latest results of deep learning and machine learning applied to orthopedic image detection in recent years, describing… More >

Ashraf S. Mashaleh^1,2,*, Noor Farizah Binti Ibrahim¹, Mohammad Alauthman³, Mohammad Almseidin⁴, Amjad Gawanmeh⁵

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2245-2267, 2024, DOI:10.32604/cmc.2023.047323

Abstract Increasing Internet of Things (IoT) device connectivity makes botnet attacks more dangerous, carrying catastrophic hazards. As IoT botnets evolve, their dynamic and multifaceted nature hampers conventional detection methods. This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization (PSO) to address the risks associated with IoT botnets. Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically. Fuzzy component settings are optimized using PSO to improve accuracy. The methodology allows for more complex thinking by transitioning from binary to continuous assessment. Instead of expert inputs, PSO data-driven tunes rules and membership More >

Lieping Zhang^1,2, Xiaoxu Shi^1,2, Liu Tang^1,2, Yilin Wang³, Jiansheng Peng⁴, Jianchu Zou^4,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2111-2136, 2024, DOI:10.32604/cmc.2024.047235

Abstract A Rapid-exploration Random Tree (RRT) autonomous detection algorithm based on the multi-guide-node deflection strategy and Karto Simultaneous Localization and Mapping (SLAM) algorithm was proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile robot. Firstly, an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward, which introduces the reference value of guide nodes’ deflection probability into the random sampling function so that the global… More >