Huaxiang Song^*

Intelligent Automation & Soft Computing, Vol., , DOI:10.32604/iasc.2023.039315

Abstract Recently, the convolutional neural network (CNN) has been dominant in studies on interpreting remote sensing images (RSI). However, it appears that training optimization strategies have received less attention in relevant research. To evaluate this problem, the author proposes a novel algorithm named the Fast Training CNN (FST-CNN). To verify the algorithm’s effectiveness, twenty methods, including six classic models and thirty architectures from previous studies, are included in a performance comparison. The overall accuracy (OA) trained by the FST-CNN algorithm on the same model architecture and dataset is treated as an evaluation baseline. Results show that there is a maximal OA… More >

Jinshuo Wang, Lida Xing, Fulong Zhang, Chuanfu Liu^*

Journal of Renewable Materials, Vol., , DOI:10.32604/jrm.2023.029057

Abstract Wood-based functional materials have developed rapidly. But the flammability significantly limits its further application. To improve the flame retardancy, the balsa wood was delignified by NaClO₂ solution to create a cellulose scaffold, and then alternately immersed in CaCl₂ ethanol solution and NaHCO₃ aqueous solution under vacuum. The high porosity and wettability resulting from delignification benefited the following mineralization process, changing the thermal properties of balsa wood significantly. The organic-inorganic wood composite showed abundant CaCO₃ spherical particles under scanning electron microscopy. The peak of the heat release rate of delignified balsa-CaCO₃ was reduced by 33% compared to the native balsa, according… More > Graphic Abstract

Cut Rahmawati^1,2,*, Lia Handayani³, Muhtadin⁴, Muhammad Faisal⁴, Muhammad Zardi¹, S. M. Sapuan⁵, Agung Efriyo Hadi⁶, Jawad Ahmad⁷, Haytham F. Isleem⁸

Journal of Renewable Materials, Vol., , DOI:10.32604/jrm.2023.028987

Abstract Waste Glass (WGs) and Coir Fiber (CF) are not widely utilized, even though their silica and cellulose content can be used to create construction materials. This study aimed to optimize mortar compressive strength using Response Surface Methodology (RSM). The Central Composite Design (CCD) was applied to determine the optimization of WGs and CF addition to the mortar compressive strength. Compressive strength and microstructure testing with Scanning Electron Microscope (SEM), Fourier-transform Infrared Spectroscopy (FT-IR), and X-Ray Diffraction (XRD) were conducted to specify the mechanical ability and bonding between the matrix, CF, and WGs. The results showed that the chemical treatment of… More >

Baoqiang Zhang^1,2, Ling Xiang^3,4,*

International Journal of Mental Health Promotion, Vol., , DOI:10.32604/ijmhp.2023.027303

Abstract Social media has become increasingly popular and is now a significant tool for daily communication for many people. The use of social media can cause anxiety and have detrimental impacts on mental health. Cognitive impairment is more likely to affect individuals with anxiety. Investigating the cognitive abilities and mental health of social media users requires the development of new methodologies. This study employed the AX-Continuous Performance Test (AX-CPT) paradigm and the Stroop paradigm to study the cognitive control characteristics of trait anxiety, drawing on psychological experimental methods. Previous studies on whether trait anxiety impairs cognitive control remain controversial, possibly because… More >

Lei Ling¹, Lijun Huang², Jie Wang², Li Zhang², Yue Wu², Yizhang Jiang¹, Kaijian Xia^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028828

Abstract In recent years, the soft subspace clustering algorithm has shown good results for high-dimensional data, which can assign different weights to each cluster class and use weights to measure the contribution of each dimension in various features. The enhanced soft subspace clustering algorithm combines interclass separation and intraclass tightness information, which has strong results for image segmentation, but the clustering algorithm is vulnerable to noisy data and dependence on the initialized clustering center. However, the clustering algorithm is susceptible to the influence of noisy data and reliance on initialized clustering centers and falls into a local optimum; the clustering effect… More >

Muzi Li^*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.026827

Abstract Modular construction as an innovative method aids the construction industry in transforming to off-site construction production with high efficiency and environmental friendliness. Despite the obvious advantages, the uptake of modular construction is not booming as expected. However, previous studies have investigated and summarized the barriers to the adoption of modular construction. In this research, a Large-Scale Group Decision Making (LSGDM)- based analysis is first made of the severity of barriers to modular construction adoption from the perspective of construction stakeholders. In addition, the Technology-Organization-Environment (TOE) framework is utilized to identify the barriers based on three contexts (technology, organization, and environment).… More >

Wadhah Mohammed M. Aqlan¹, Ghassan Ahmed Ali^2,*, Khairan Rajab², Adel Rajab², Asadullah Shaikh², Fekry Olayah², Shehab Abdulhabib Saeed Alzaeemi^3,*, Kim Gaik Tay³, Mohd Adib Omar¹, Ernest Mangantig⁴

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.039228

Abstract Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production, resulting in a drop in the size of red blood cells. In severe forms, it can lead to death. This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival. Therefore, controlling thalassemia is extremely important and is made by promoting screening to the general population, particularly among thalassemia carriers. Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like… More >

Pingping Li^*, Jiuxin Cao

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.039076

Abstract Virtual machine (VM) consolidation is an effective way to improve resource utilization and reduce energy consumption in cloud data centers. Most existing studies have considered VM consolidation as a bin-packing problem, but the current schemes commonly ignore the long-term relationship between VMs and hosts. In addition, there is a lack of long-term consideration for resource optimization in the VM consolidation, which results in unnecessary VM migration and increased energy consumption. To address these limitations, a VM consolidation method based on multi-step prediction and affinity-aware technique for energy-efficient cloud data centers (MPaAFVMC) is proposed. The proposed method uses an improved linear… More >

Huaxin Zhou^1,2, Ziying Fang³, Yilin Wang⁴, Mengjun Tong^1,2,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.037342

Abstract Plant diseases have become a challenging threat in the agricultural field. Various learning approaches for plant disease detection and classification have been adopted to detect and diagnose these diseases early. However, deep learning entails extensive data for training, and it may be challenging to collect plant datasets. Even though plant datasets can be collected, they may be uneven in quantity. As a result, the problem of classification model overfitting arises. This study targets this issue and proposes an auxiliary classifier GAN (small-ACGAN) model based on a small number of datasets to extend the available data. First, after comparing various attention… More >

Sara Khalid¹, Jamal Hussain Shah^1,*, Muhammad Sharif¹, Muhammad Rafiq², Gyu Sang Choi^3,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.035595

Abstract Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians. Consequently, traffic signs have been of great importance for every civilized country, which makes researchers give more focus on the automatic detection of traffic signs. Detecting these traffic signs is challenging due to being in the dark, far away, partially occluded, and affected by the lighting or the presence of similar objects. An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues. This technique aimed to devise an efficient, robust and accurate… More >