Yu Zhang^*, Lianmin Li, Zhongxiang Liu, Yuhu Wu

Energy Engineering, Vol.121, No.5, pp. 1209-1221, 2024, DOI:10.32604/ee.2024.046141

Abstract With the development of renewable energy technologies such as photovoltaics and wind power, it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage. To solve the problem of the interests of different subjects in the operation of the energy storage power stations (ESS) and the integrated energy multi-microgrid alliance (IEMA), this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game. In the upper layer, ESS optimizes charging and discharging decisions through a dynamic pricing mechanism.… More > Graphic Abstract

Wenlu Ji^*, Teng Tu, Nan Ma

Energy Engineering, Vol.121, No.5, pp. 1223-1243, 2024, DOI:10.32604/ee.2024.046112

Abstract To improve the resilience of a distribution system against extreme weather, a fuel-based distributed generator (DG) allocation model is proposed in this study. In this model, the DGs are placed at the planning stage. When an extreme event occurs, the controllable generators form temporary microgrids (MGs) to restore the load maximally. Simultaneously, a demand response program (DRP) mitigates the imbalance between the power supply and demand during extreme events. To cope with the fault uncertainty, a robust optimization (RO) method is applied to reduce the long-term investment and short-term operation costs. The optimization is formulated as a tri-level defender-attacker-defender (DAD)… More >

Qixiang Tong, Zhipeng Zhu, Min Zhang, Kerui Cao, Haihua Xing^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1353-1375, 2024, DOI:10.32604/cmc.2024.049187

Abstract High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presence of occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the difficulty of segmentation. In this paper, an improved network with a cross-region self-attention mechanism for multi-scale features based on DeepLabv3+ is designed to address the difficulties of small object segmentation and blurred target edge segmentation. First, we use CrossFormer as the backbone feature extraction network to achieve the interaction between large- and small-scale features, and establish self-attention associations between features at both large and small scales to capture global contextual… More >

Dingping Chen¹, Zhiheng Zhu², Jinyang Fu^1,3, Jilin He^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1679-1703, 2024, DOI:10.32604/cmc.2024.049048

Abstract The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safety and performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of road tunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combined with a deep neural network model is an effective means to realize the localization and identification of crack defects on the surface of road tunnels. We propose a complete set of automatic inspection methods for identifying cracks on the walls of road tunnels as a… More >

Supeng Yu¹, Fen Huang^1,*, Chengcheng Fan^2,3,4,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 549-562, 2024, DOI:10.32604/cmc.2024.048608

Abstract Significant advancements have been achieved in road surface extraction based on high-resolution remote sensing image processing. Most current methods rely on fully supervised learning, which necessitates enormous human effort to label the image. Within this field, other research endeavors utilize weakly supervised methods. These approaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such as scribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised and edge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equipped with a distinct decoder module dedicated to road extraction tasks. One… More >

Hongle Li¹, SeongKi Kim^2,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 473-492, 2024, DOI:10.32604/cmc.2024.048402

Abstract Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetables and determines the stop and the start according to the demands. This study explores the optimization of dynamic vehicle scheduling and real-time route planning in urban public transportation systems, with a focus on bus services. It addresses the limitations of current shared mobility routing algorithms, which are primarily designed for simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. The research introduces an route planning algorithm designed to dynamically accommodate passenger travel needs and enable real-time route modifications.… More >

Fatma Nese Efil¹, Sania Qureshi^1,2,3, Nezihal Gokbulut^1,4, Kamyar Hosseini^1,3, Evren Hincal^1,4,*, Amanullah Soomro²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 485-512, 2024, DOI:10.32604/cmes.2024.047907

Abstract The global population has been and will continue to be severely impacted by the COVID-19 epidemic. The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer, heart disease, and diabetes. Here, using ordinary differential equations (ODEs), two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease. After that, we highlight the stability assessments that can be applied to these models. Sensitivity analysis is used to examine how changes in certain factors impact different aspects… More >

Bo Liu^1,2, Li Feng^1,*, Yufeng Chen³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 845-862, 2024, DOI:10.32604/cmes.2024.047695

Abstract This paper focuses on the effective utilization of data augmentation techniques for 3D lidar point clouds to enhance the performance of neural network models. These point clouds, which represent spatial information through a collection of 3D coordinates, have found wide-ranging applications. Data augmentation has emerged as a potent solution to the challenges posed by limited labeled data and the need to enhance model generalization capabilities. Much of the existing research is devoted to crafting novel data augmentation methods specifically for 3D lidar point clouds. However, there has been a lack of focus on making the most of the numerous existing… More >

AYÇA BAL ÖZTÜRK^1,2,*, ZEHRA ÖZBA޳, BENGİ ÖZKAHRAMAN⁴, SERKAN EMİK⁵

Journal of Polymer Materials, Vol.36, No.2, pp. 161-173, 2019, DOI:10.32381/JPM.2019.36.02.5

Abstract A functionalized hydrogel composed of 2-(hydroxyethyl) methacrylate (HEMA) and acrylamide (AAm) was synthesized by amination and saponification reactions, respectively, and its functionality was examined for the elimination of copper(II) ions. The maximum adsorption capacity for copper(II) ions was 0.617 mmol g^-1 before saponification, whereas it was 1.2225 mmol g^-1 after saponification. The adsorption data was analyzed with pseudo-first-order (r² =0.8867), intra-particle diffusion (r² =0.9453), Elovich (r²=0.9489) and pseudo-secondorder(r² =0.9999) kinetic models. Based on the adsorption equilibrium experimental data Freundlich(r² =0.9964), Langmuir(r²=0.998) and Dubinin–Radushkevich (D-R) (r² =0.9960) adsorption isotherms provided good fits for all of experimental results. Finally, the datas of… More >

RABIRANJAN MURMU^a,b, DEBASHIS ROY^a, HAREKRUSHNA SUTAR^b

Journal of Polymer Materials, Vol.40, No.3-4, pp. 125-139, 2023, DOI:10.32381/JPM.2023.40.3-4.1

Abstract A one dimensional isothermal model is proposed by modelling the kinetics of methanol transport at anode flow channel (AFC), membrane and cathode catalyst layer of direct methanol fuel cell (DMFC). Analytical model is proposed to predict methanol cross-over rate through the electrolyte membrane and cell performance. The model presented in this paper considered methanol diffusion and electrochemical oxidation at the anode and cathode channels. The analytical solution of the proposed model was simulated in a MATLAB environment to obtain the polarization curve and leakage current. The effect of methanol concentration on cell voltage and leakage current is studied. The methanol… More >