Huaiyin He¹, Longqing Zou¹, Yanchao Li¹, Yixuan Wang¹, Junxiang Li¹, Huan Wen¹, Bei Chang¹, Lijun Liu^2,*

Energy Engineering, Vol.121, No.1, pp. 111-123, 2024, DOI:10.32604/ee.2023.041010

Abstract Multistage multi-cluster hydraulic fracturing has enabled the economic exploitation of shale reservoirs, but the interpretation of hydraulic fracture parameters is challenging. The pressure signals after pump shutdown are influenced by hydraulic fractures, which can reflect the geometric features of hydraulic fracture. The shutdown pressure can be used to interpret the hydraulic fracture parameters in a real-time and cost-effective manner. In this paper, a mathematical model for shutdown pressure evolution is developed considering the effects of wellbore friction, perforation friction and fluid loss in fractures. An efficient numerical simulation method is established by using the method of characteristics. Based on this… More >

Yang Yang¹, Yuhan Long¹, Yijing Lin², Zhipeng Gao¹, Lanlan Rui¹, Peng Yu^1,3,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3623-3651, 2023, DOI:10.32604/cmc.2023.040250

Abstract With the rapid development of the Internet of Things (IoT), the automation of edge-side equipment has emerged as a significant trend. The existing fault diagnosis methods have the characteristics of heavy computing and storage load, and most of them have computational redundancy, which is not suitable for deployment on edge devices with limited resources and capabilities. This paper proposes a novel two-stage edge-side fault diagnosis method based on double knowledge distillation. First, we offer a clustering-based self-knowledge distillation approach (Cluster KD), which takes the mean value of the sample diagnosis results, clusters them, and takes the clustering results as the… More >

S M Hasan Mahmud^1,2, Md Mamun Ali³, Mohammad Fahim Shahriar¹, Fahad Ahmed Al-Zahrani⁴, Kawsar Ahmed^5,6,*, Dip Nandi¹, Francis M. Bui⁵

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3933-3948, 2023, DOI:10.32604/cmc.2023.039020

Abstract Alzheimer’s disease (AD) is a neurodevelopmental impairment that results in a person’s behavior, thinking, and memory loss. The most common symptoms of AD are losing memory and early aging. In addition to these, there are several serious impacts of AD. However, the impact of AD can be mitigated by early-stage detection though it cannot be cured permanently. Early-stage detection is the most challenging task for controlling and mitigating the impact of AD. The study proposes a predictive model to detect AD in the initial phase based on machine learning and a deep learning approach to address the issue. To build… More >

Dehai Zhang^*, Yu Ma, Qing Liu, Haoxing Wang, Anquan Ren, Jiashu Liang

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2901-2920, 2023, DOI:10.32604/cmc.2023.038264

Abstract Traffic scene captioning technology automatically generates one or more sentences to describe the content of traffic scenes by analyzing the content of the input traffic scene images, ensuring road safety while providing an important decision-making function for sustainable transportation. In order to provide a comprehensive and reasonable description of complex traffic scenes, a traffic scene semantic captioning model with multi-stage feature enhancement is proposed in this paper. In general, the model follows an encoder-decoder structure. First, multi-level granularity visual features are used for feature enhancement during the encoding process, which enables the model to learn more detailed content in the… More >

Huiru Zhao¹, Manyu Yao^1,*, Zhenqi Bai¹, Yue Zhang², Zhihua Ding³, Zhenda Hu⁴

Energy Engineering, Vol.120, No.10, pp. 2211-2231, 2023, DOI:10.32604/ee.2023.029371

Abstract As an essential infrastructure, the rural power grid is vital in promoting agricultural and rural carbon sequestration and improving rural energy electrification. It is necessary to carry out in-depth research on its comprehensive efficiency. Based on the requirements of “double carbon” and rural revitalization strategy for the rural Power Grid, this paper focuses on the modernization and low-carbon transformation of the rural Power Grid. It constructs an input-output index system for the investment efficiency of the rural Power Grid in China under the new situation. It uses the primary data of the rural Power Grid of 30 prefecture-level cities in… More >

Cheng Wang¹, Haoran Zhu^2,*, Congjun Rao^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 691-718, 2024, DOI:10.32604/cmes.2023.029258

Abstract Cardiovascular disease (CVD) has gradually become one of the main causes of harm to the life and health of residents. Exploring the influencing factors and risk assessment methods of CVD has become a general trend. In this paper, a machine learning-based decision-making mechanism for risk assessment of CVD is designed. In this mechanism, the logistics regression analysis method and factor analysis model are used to select age, obesity degree, blood pressure, blood fat, blood sugar, smoking status, drinking status, and exercise status as the main pathogenic factors of CVD, and an index system of risk assessment for CVD is established.… More >

Xiaolin Lu^1,*, Xiaolei Miao²

International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1041-1052, 2023, DOI:10.32604/ijmhp.2023.030232

Abstract Background: During the early stages of the COVID-19 pandemic in China, social interactions shifted to online spaces due to lock-downs and social distancing measures. As a result, the impact of online social networking on users’ emotional status has become stronger than ever. This study examines the association between online social networking and Internet users’ emotional status and how offline reality affects this relationship. Methods: The study utilizes cross-sectional online survey data (n = 3004) and Baidu Migration big data from the first 3 months of the pandemic. Two dimensions of online networking are measured: social support and information sources. Results:… More > Graphic Abstract

Xiangcun Qi^a , Mo Yang^a,* , Yuwen Zhang^b

Frontiers in Heat and Mass Transfer, Vol.8, pp. 1-8, 2017, DOI:10.5098/hmt.8.3

Abstract The formation of thermal NO and fuel type NO emission under the air staged combustion in a tower pulverized coal fired boiler that burners are arranged in the front and the rear wall are investigated in this paper. Effects of the distribution of oxygen in the main combustion zone on NO_X are then analyze qualitatively. The results show that when the SOFA ratio is 34.98%, NO_X yield is at the minimum; thermal NO is not only related to temperature, but also by the influence of oxygen distribution. When oxygen is more and the temperature is high, it is conducive to… More >

R. Vanalakshmi¹, S. Maragathasundari^1,*, M. Kameswari¹, B. Balamurugan², C. Swedheetha³

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1399-1419, 2023, DOI:10.32604/iasc.2023.038506

Abstract Queuing models are used to assess the functionality and aesthetics of SCADA systems for supervisory control and data collection. Here, the main emphasis is on how the queuing theory can be used in the system’s design and analysis. The analysis’s findings indicate that by using queuing models, cost-performance ratios close to the ideal might be attained. This article discusses a novel methodology for evaluating the service-oriented survivability of SCADA systems. In order to evaluate the state of service performance and the system’s overall resilience, the framework applies queuing theory to an analytical model. As a result, the SCADA process is… More >

Deepthi K. Oommen^*, J. Arunnehru

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 793-811, 2023, DOI:10.32604/cmc.2023.038640

Abstract Alzheimer’s Disease (AD) is a progressive neurological disease. Early diagnosis of this illness using conventional methods is very challenging. Deep Learning (DL) is one of the finest solutions for improving diagnostic procedures’ performance and forecast accuracy. The disease’s widespread distribution and elevated mortality rate demonstrate its significance in the older-onset and younger-onset age groups. In light of research investigations, it is vital to consider age as one of the key criteria when choosing the subjects. The younger subjects are more susceptible to the perishable side than the older onset. The proposed investigation concentrated on the younger onset. The research used… More >