Lanyao Zhang¹, Shichao Kan², Yigang Cen³, Xiaoling Chen¹, Linna Zhang^1,*, Yansen Huang^4,5

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1631-1648, 2024, DOI:10.32604/cmc.2024.046924

Abstract Unsupervised methods based on density representation have shown their abilities in anomaly detection, but detection performance still needs to be improved. Specifically, approaches using normalizing flows can accurately evaluate sample distributions, mapping normal features to the normal distribution and anomalous features outside it. Consequently, this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network (NF-BMR). It utilizes pre-trained Convolutional Neural Networks (CNN) and normalizing flows to construct discriminative source and target domain feature spaces. Additionally, to better learn feature information in both domain spaces, we propose the Bidirectional Mapping Residual Network (BMR), which maps sample features to these two spaces… More > Graphic Abstract

Matthew R. Coburn¹, Charlie Young², Chris Smith², Graham Schultz², Miguel Robayo³, Zheng-Tong Xie^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 547-562, 2024, DOI:10.32604/fdmp.2023.028601

Abstract A prototype cleanroom for hazardous testing and handling of satellites prior to launcher encapsulation, satisfying the ISO8 standard has been designed and analyzed in terms of performances. Unsteady Reynolds Averaged Navier-Stokes (URANS) models have been used to study the related flow field and particulate matter (PM) dispersion. The outcomes of the URANS models have been validated through comparison with equivalent large-eddy simulations. Special attention has been paid to the location and shape of the air intakes and their orientation in space, in order to balance the PM convection and diffusion inside the cleanroom. Forming a cyclone-type flow pattern inside the… More >

Doaa Sami Khafaga¹, Zongming Lv², Imran Khan^3,4, Shebnam M. Sefat⁵, Amel Ali Alhussan^1,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3723-3740, 2023, DOI:10.32604/cmc.2023.039956

Abstract With the capacities of self-learning, acquainted capacities, high-speed looking for ideal arrangements, solid nonlinear fitting, and mapping self-assertively complex nonlinear relations, neural systems have made incredible advances and accomplished broad application over the final half-century. As one of the foremost conspicuous methods for fake insights, neural systems are growing toward high computational speed and moo control utilization. Due to the inborn impediments of electronic gadgets, it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage. Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways to break the bottleneck. This… More >

Sheetal Sharma^1,2, Kamali Gupta¹, Deepali Gupta¹, Shalli Rani^1,*, Gaurav Dhiman^3,4,5,6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2029-2059, 2024, DOI:10.32604/cmes.2023.029997

Abstract The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making them more intelligent and connected. However, this advancement comes with challenges related to the effectiveness of IoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensure their proper functionality. The success of smart systems relies on their seamless operation and ability to handle faults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore, sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments. To address these concerns, various techniques and… More > Graphic Abstract

Frédéric Roulier^*

Revue Internationale de Géomatique, Vol.32, pp. 17-37, 2023, DOI:10.32604/RIG.2023.045458

Abstract The morphological differences between two geographical maps can be highlighted by a polycentric distance cartogram resulting from a bidimensional regression. Beyond the communicational interest of the transformations thus produced, the method makes it possible to reveal the differences in structure and therefore constitutes a real research tool. However, bidimensional regression can only compare the shape of two maps. Since the 1990s, geometric morphometrics has revolutionized the morphological analysis of natural structures (and others). It has since been applied in many fields of research but not in cartography. This article describes the theoretical and methodological bases of a method combining bidimensional… More > Graphic Abstract

Mudassir Khalil¹, Muhammad Imran Sharif^2,*, Ahmed Naeem³, Muhammad Umar Chaudhry¹, Hafiz Tayyab Rauf^4,*, Adham E. Ragab⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2031-2047, 2023, DOI:10.32604/cmc.2023.043687

Abstract Early detection of brain tumors is critical for effective treatment planning. Identifying tumors in their nascent stages can significantly enhance the chances of patient survival. While there are various types of brain tumors, each with unique characteristics and treatment protocols, tumors are often minuscule during their initial stages, making manual diagnosis challenging, time-consuming, and potentially ambiguous. Current techniques predominantly used in hospitals involve manual detection via MRI scans, which can be costly, error-prone, and time-intensive. An automated system for detecting brain tumors could be pivotal in identifying the disease in its earliest phases. This research applies several data augmentation techniques… More >

J. N. Chung^*, Kun Yuan

Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-7, 2015, DOI:10.5098/hmt.6.1

Abstract Chilldown or quenching is a complicated process that initiates the cryogenic fluid line transport, and it involves unsteady two-phase heat and mass transfer. To advance our understanding of this process, we have reviewed recent experimental investigations. The chilldown process can be generally divided into three regimes: film boiling, transition boiling and nucleate boiling, and each regime is associated with a different flow pattern and heat transfer mechanism. Under low flow rate conditions, it is concluded that the two-phase flow regime is dispersed flow in the film boiling regime. The dispersed liquid phase is in the form of long filaments as… More >

D. Lourdu Immaculate^a , R. Muthuraj^b,*, Anant Kant Shukla^c, S. Srinivas^d

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-14, 2016, DOI:10.5098/hmt.7.12

Abstract This article aims to examine the MHD unsteady flow of Williamson nanofluid in a vertical channel filled with a porous material and oscillating wall temperature. The modeling of this problem is transformed to ordinary differential equations by collecting the non-periodic and periodic terms and then series solutions are obtained by using a powerful method known as the homotopy analysis method (HAM). The influence of involved parameters on heat and mass transfer characteristics of the fluid flow is computed and presented graphically. Further, variations on volume flow rate, coefficient of skin friction, heat transfer rate and mass transfer rate are also… More >

Kun Zhang^*, Liang Bi Wang

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-7, 2016, DOI:10.5098/hmt.7.18

Abstract Detailed numerical analysis is presented for the effect of spaceship orbital transfer on solution convection during protein crystal growth under microgravity. The results show that the flow and mass transfer during protein crystal growth are unsteady in the process of orbital transfer. For the case of quasi-steady acceleration, the flow is so weak that the effect of flow on concentration field can be negligible. For the case of position adjustment, the convection is enhanced with protein crystal diameter d_c > 0.2 mm and slightly alters the purely diffusive concentration distribution under zero gravity condition. For the case of motor working,… More >

Hongyan Xia, Jin Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1637-1661, 2024, DOI:10.32604/cmes.2023.029576

Abstract Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to cope with the development trend of large-scale ships. In order to improve the solution efficiency of the existing space-time network (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guided vehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balance constraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added to acquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added to… More >