Tianmin Deng^*, Xiyue Zhang, Xinxin Cheng

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 533-549, 2024, DOI:10.32604/cmc.2023.044639

Abstract Vehicle detection plays a crucial role in the field of autonomous driving technology. However, directly applying deep learning-based object detection algorithms to complex road scene images often leads to subpar performance and slow inference speeds in vehicle detection. Achieving a balance between accuracy and detection speed is crucial for real-time object detection in real-world road scenes. This paper proposes a high-precision and fast vehicle detector called the feature-guided bidirectional pyramid network (FBPN). Firstly, to tackle challenges like vehicle occlusion and significant background interference, the efficient feature filtering module (EFFM) is introduced into the deep network, which amplifies the disparities between… More >

Tohid Adibi¹, Shams Forruque Ahmed^2,*, Omid Adibi³, Hassan Athari⁴, Irfan Anjum Badruddin⁵, Syed Javed⁵

Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 103-103, 2023, DOI:10.32604/iasc.2023.047521

Abstract This article has no abstract. More >

Zongjun Yin^*, Rong Su, Hui Xu

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 487-504, 2024, DOI:10.32604/fdmp.2023.042631

Abstract In this study, numerical simulations of the pinching-off phenomena displayed by the dispersed phase in a continuous phase have been conducted using COMSOL Multiphysics (level-set method). Four flow patterns, namely “drop flow”, “jet flow”, “squeeze flow”, and “co-flow”, have been obtained for different flow velocity ratios, channel diameter ratios, density ratios, viscosity ratios, and surface tension. The flow pattern map of two-phase flow in coaxial microchannels has been obtained accordingly, and the associated droplet generation process has been critically discussed considering the related frequency, diameter, and pinch-off length. In particular, it is shown that the larger the flow velocity ratio,… More > Graphic Abstract

Chaoqian He^1,2, Runfang Hao^1,2,*, Kun Yang^1,2, Zhongyun Yuan^1,2, Shengbo Sang^1,2, Xiaorui Wang^1,2

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3423-3442, 2023, DOI:10.32604/cmc.2023.045718

Abstract Intelligent fault diagnosis in modern mechanical equipment maintenance is increasingly adopting deep learning technology. However, conventional bearing fault diagnosis models often suffer from low accuracy and unstable performance in noisy environments due to their reliance on a single input data. Therefore, this paper proposes a dual-channel convolutional neural network (DDCNN) model that leverages dual data inputs. The DDCNN model introduces two key improvements. Firstly, one of the channels substitutes its convolution with a larger kernel, simplifying the structure while addressing the lack of global information and shallow features. Secondly, the feature layer combines data from different sensors based on their… More >

Muhammad Mumtaz Ali, Faiqa Maqsood, Shiqi Liu, Weiyan Hou, Liying Zhang, Zhenfei Wang^*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2699-2714, 2023, DOI:10.32604/cmc.2023.045310

Abstract Breast cancer, particularly Invasive Ductal Carcinoma (IDC), is a primary global health concern predominantly affecting women. Early and precise diagnosis is crucial for effective treatment planning. Several AI-based techniques for IDC-level classification have been proposed in recent years. Processing speed, memory size, and accuracy can still be improved for better performance. Our study presents ECAM, an Enhanced Channel-Wise Attention Mechanism, using deep learning to analyze histopathological images of Breast Invasive Ductal Carcinoma (BIDC). The main objectives of our study are to enhance computational efficiency using a Separable CNN architecture, improve data representation through hierarchical feature aggregation, and increase accuracy and… More >

Greg Ball, John Polansky, Tarik Kaya^*

Frontiers in Heat and Mass Transfer, Vol.4, No.1, pp. 1-9, 2013, DOI:10.5098/hmt.v4.1.3002

Abstract The fluid flow and heat transfer in an evaporating extended meniscus are numerically studied. Continuity, momentum, energy equations and the Kelvin-Clapeyron model are used to develop a third order, non-linear ordinary differential equation which governs the evaporating thin film. It is shown that the numerical results strongly depend on the choice of the accommodation coefficient and Hamaker constant as well as the initial perturbations. Therefore, in the absence of experimentally verified values, the numerical solutions should be considered as qualitative at best. It is found that the numerical results produce negative liquid pressures under certain specific conditions. This result may… More >

Shihong Zhang^*，Zhihua Wang

Frontiers in Heat and Mass Transfer, Vol.4, No.2, pp. 1-6, 2013, DOI:10.5098/hmt.v4.2.3005

Abstract This article discussed exhaust gas temperature and pollutant emissions characteristics of the combustion of rich natural gas-air mixtures in Pd metal based honeycomb monoliths burner during the period of start-up process. The burner needs to be ignited by gas phase combustion with the excessive air coefficient (a) at 1.3. The chemistry at work in the monoliths was then investigated using the stagnation point flow reactor or SPFR. The experimental results in catalytic monolith can be explained from SPFR. The exhaust gas temperature and pollutant emissions were measured by thermocouple K of diameter 0.5 and the analyser every 1 minute, respectively.… More >

B. V. K. Reddy, Matthew Barry, John Li, Minking K. Chyu^*

Frontiers in Heat and Mass Transfer, Vol.4, No.2, pp. 1-7, 2013, DOI:10.5098/hmt.v4.2.3001

Abstract In this study, the thermoelectric performance of an integrated thermoelectric device (iTED) with rectangular, round end slots, and circular flow channel designs applied to waste heat recovery for several hot stream flow rates has been investigated using numerical methods. An iTED is constructed with p- and n-type semiconductor materials bonded to the surfaces of an interconnector with flow channels drilled through it. This interconnector acts as an internal heat exchanger directing waste heat from the hot stream to thermoelectric elements. The quantity of heat extracted from the waste heat source and the subsequent amount of electrical power generated P₀ from… More >

Suripeddi Srinivas^a , Akshay Gupta^b,*, Ashish Kumar Kandoi^b

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-12, 2014, DOI:10.5098/hmt.5.21

Abstract The present work deals with the flow and thermal analysis of nanofluid in the wavy channels. The governing flow equations are solved numerically using CFD package assuming single phase approach. To study the effect of the concentration and size variation of the nanoparticle, the concentration and size are varied from 0% - 5% and 25 nm - 100 nm respectively over the Reynolds number range of 250-1500 for Au-water nanofluid. The effect on heat transfer enhancement because of corrugation of wavy channel is analyzed on four different shapes (sinusoidal, triangular, trapezoidal and square) channels. The effect of amplitude of the… More >

Muataz S. Alhassan¹, Ameer A. Alameri², Andrés Alexis Ramírez-Coronel³, I. B. Sapaev^4,5,6, Azher M. Abed^7,*, David-Juan Ramos-Huallpartupa⁸, Rahman S. Zabibah⁹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.2, pp. 311-323, 2024, DOI:10.32604/fdmp.2023.026782

Abstract In line with recent studies, where it has been shown that nanofluids containing graphene have a stronger capacity to boost the heat transfer coefficient with respect to ordinary nanofluids, experiments have been conducted using water with cobalt ferrite/graphene nanoparticles. In particular, a circular channel made of copper subjected to a constant heat flux has been considered. As nanoparticles are sensitive to the presence of a magnetic field, different conditions have been examined, allowing both the strength and the frequency of such a field to span relatively wide ranges and assuming different concentrations of nanoparticles. According to the findings, the addition… More >