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  • Open Access

    ARTICLE

    EFFECT OF RESIDUAL NON-CONDENSABLE GASES ON THE PERFORMANCE OF A CARBON DIOXIDE EVAPORATOR AND THE SYSTEM PERFORMANCE

    Jing Hua,* , Mingxing Dub

    Frontiers in Heat and Mass Transfer, Vol.14, pp. 1-7, 2020, DOI:10.5098/hmt.14.5

    Abstract Inert gases are conveniently used for leak detection. Relative to CO2, majority of the inert gases are non-condensable. It is of great significance to understand the effects of residual non-condensable gases on the performance of a refrigeration system. This paper investigates, both theoretically and experimentally, on the impact of residual non-condensable gases on the performance of a carbon dioxide (CO2) evaporator and the system performance. A theoretical analysis indicates that residual non-condensable gases can convert homogeneous nucleation into a heterogeneous nucleation process and accelerate phase change, thus, reducing superheat or incipient boiling temperature. To investigate the influence of residual non-condensable… More >

  • Open Access

    VIEWPOINT

    Liquid biopsy and blood-based minimal residual disease evaluation in multiple myeloma

    ALESSANDRO GOZZETTI*, MONICA BOCCHIA

    Oncology Research, Vol.31, No.3, pp. 271-274, 2023, DOI:10.32604/or.2023.028668

    Abstract Novel drug availability has increased the depth of response and revolutionised the outcomes of multiple myeloma patients. Minimal residual disease evaluation is a surrogate for progression-free survival and overall survival and has become widely used not-only in clinical trials but also in daily patient management. Bone marrow aspiration is the gold standard for response evaluation, but due to the patchy nature of myeloma, false negatives are possible. Liquid biopsy and blood-based minimal residual disease evaluation consider circulating plasma cells, mass spectrometry or circulating tumour DNA. This approach is less invasive, can provide a more comprehensive picture of the disease and… More >

  • Open Access

    ARTICLE

    Strategy for Rapid Diabetic Retinopathy Exposure Based on Enhanced Feature Extraction Processing

    V. Banupriya1,*, S. Anusuya2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5597-5613, 2023, DOI:10.32604/cmc.2023.038696

    Abstract In the modern world, one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy (DR), which will result in retinal damage, and, thus, lead to blindness. Diabetic retinopathy (DR) can be well treated with early diagnosis. Retinal fundus images of humans are used to screen for lesions in the retina. However, detecting DR in the early stages is challenging due to the minimal symptoms. Furthermore, the occurrence of diseases linked to vascular anomalies brought on by DR aids in diagnosing the condition. Nevertheless, the resources required for manually identifying the lesions are high. Similarly,… More >

  • Open Access

    ARTICLE

    A New Hybrid Model for Segmentation of the Skin Lesion Based on Residual Attention U-Net

    Saleh Naif Almuayqil1, Reham Arnous2,*, Noha Sakr3, Magdy M. Fadel3

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5177-5192, 2023, DOI:10.32604/cmc.2023.038625

    Abstract Skin segmentation participates significantly in various biomedical applications, such as skin cancer identification and skin lesion detection. This paper presents a novel framework for segmenting the skin. The framework contains two main stages: The first stage is for removing different types of noises from the dermoscopic images, such as hair, speckle, and impulse noise, and the second stage is for segmentation of the dermoscopic images using an attention residual U-shaped Network (U-Net). The framework uses variational Autoencoders (VAEs) for removing the hair noises, the Generative Adversarial Denoising Network (DGAN-Net), the Denoising U-shaped U-Net (D-U-NET), and Batch Renormalization U-Net (Br-U-NET) for… More >

  • Open Access

    ARTICLE

    Temperature-Triggered Hardware Trojan Based Algebraic Fault Analysis of SKINNY-64-64 Lightweight Block Cipher

    Lei Zhu, Jinyue Gong, Liang Dong*, Cong Zhang

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5521-5537, 2023, DOI:10.32604/cmc.2023.037336

    Abstract SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length, and it is mainly used on the Internet of Things (IoT). Currently, faults can be injected into cryptographic devices by attackers in a variety of ways, but it is still difficult to achieve a precisely located fault attacks at a low cost, whereas a Hardware Trojan (HT) can realize this. Temperature, as a physical quantity incidental to the operation of a cryptographic device, is easily overlooked. In this paper, a temperature-triggered HT (THT) is designed, which, when activated, causes a specific bit of the intermediate state… More >

  • Open Access

    ARTICLE

    Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

    Kun Yang1,2, Lei Zhao1, Xianghui Wang1, Mingyang Zhang1, Linyan Xue1,2, Shuang Liu1,2, Kun Liu1,2,3,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5159-5176, 2023, DOI:10.32604/cmc.2023.036401

    Abstract The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the resolution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images; and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion… More >

  • Open Access

    ARTICLE

    Multi-Classification of Polyps in Colonoscopy Images Based on an Improved Deep Convolutional Neural Network

    Shuang Liu1,2,3, Xiao Liu1, Shilong Chang1, Yufeng Sun4, Kaiyuan Li1, Ya Hou1, Shiwei Wang1, Jie Meng5, Qingliang Zhao6, Sibei Wu1, Kun Yang1,2,3,*, Linyan Xue1,2,3,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5837-5852, 2023, DOI:10.32604/cmc.2023.034720

    Abstract Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection. This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologically on white-light and narrow-band imaging (NBI) colonoscopy images based on World Health Organization (WHO) and Workgroup serrAted polypS and Polyposis (WASP) classification criteria for colorectal polyps. White-light and NBI colonoscopy images of colorectal polyps exhibiting pathological results were firstly collected and classified into four categories: conventional adenoma, hyperplastic polyp, sessile serrated adenoma/polyp (SSAP) and normal, among which conventional adenoma could be further divided into three sub-categories of tubular adenoma,… More >

  • Open Access

    ARTICLE

    Analysis of a Composite Admixture Based on Ready-Mixed Concrete Waste Residuals

    Jinfa Jiang1, Long Xiong2, Ming Bao2, Zihan Zhou2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 1983-1995, 2023, DOI:10.32604/fdmp.2023.026023

    Abstract Reasonable treatment and utilization of waste residuals discharged during the production of ready-mixed concrete is an important problem in the cement industry. In this study, a composite admixture was prepared by using ready-mixed concrete waste residuals, furnace slag, and water granulated slag. The grinding characteristics of such material were investigated. Moreover, the effect of such admixture on cement hydration and pore structure was analyzed by X-ray diffraction, thermogravimetric-differential scanning calorimetry, scanning electron microcopy and mercury intrusion porosimetry. As shown by the results: The grinding characteristics of the waste residuals can be improved significantly by mixing them with furnace slag and… More > Graphic Abstract

    Analysis of a Composite Admixture Based on Ready-Mixed Concrete Waste Residuals

  • Open Access

    ARTICLE

    A COVID-19 Detection Model Based on Convolutional Neural Network and Residual Learning

    Bo Wang1,*, Yongxin Zhang1, Shihui Ji2, Binbin Zhang1, Xiangyu Wang1, Jiyong Zhang1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3625-3642, 2023, DOI:10.32604/cmc.2023.036754

    Abstract A model that can obtain rapid and accurate detection of coronavirus disease 2019 (COVID-19) plays a significant role in treating and preventing the spread of disease transmission. However, designing such a model that can balance the detection accuracy and weight parameters of memory well to deploy a mobile device is challenging. Taking this point into account, this paper fuses the convolutional neural network and residual learning operations to build a multi-class classification model, which improves COVID-19 pneumonia detection performance and keeps a trade-off between the weight parameters and accuracy. The convolutional neural network can extract the COVID-19 feature information by… More >

  • Open Access

    ARTICLE

    Pre-Impact and Impact Fall Detection Based on a Multimodal Sensor Using a Deep Residual Network

    Narit Hnoohom1, Sakorn Mekruksavanich2, Anuchit Jitpattanakul3,4,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3371-3385, 2023, DOI:10.32604/iasc.2023.036551

    Abstract Falls are the contributing factor to both fatal and nonfatal injuries in the elderly. Therefore, pre-impact fall detection, which identifies a fall before the body collides with the floor, would be essential. Recently, researchers have turned their attention from post-impact fall detection to pre-impact fall detection. Pre-impact fall detection solutions typically use either a threshold-based or machine learning-based approach, although the threshold value would be difficult to accurately determine in threshold-based methods. Moreover, while additional features could sometimes assist in categorizing falls and non-falls more precisely, the estimated determination of the significant features would be too time-intensive, thus using a… More >

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