Cun Wei¹, Yunpeng Zhao^2,*, Mingyang Cong¹, Zhigang Zhou^1,*, Jingzan Yan³, Ruixin Wang¹, Zhuoyang Li¹, Jing Liu¹

Energy Engineering, Vol.120, No.6, pp. 1465-1484, 2023, DOI:10.32604/ee.2023.026337

Abstract With increasing renewable energy utilization, the industry needs an accurate tool to select and size renewable energy equipment and evaluate the corresponding renewable energy plans. This study aims to bring new insights into sustainable and energy-efficient urban planning by developing a practical method for optimizing the production of renewable energy and carbon emission in urban areas. First, we provide a detailed formulation to calculate the renewable energy demand based on total energy demand. Second, we construct a dual-objective optimization model that represents the life cycle cost and carbon emission of renewable energy systems, after which we apply the differential evolution… More >

Xiaorui Zhang^1,2,3,*, Chunlin Yuan¹, Wei Sun^3,4, Sunil Kumar Jha⁵

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4273-4291, 2023, DOI:10.32604/cmc.2023.036975

Abstract The image emotion classification task aims to use the model to automatically predict the emotional response of people when they see the image. Studies have shown that certain local regions are more likely to inspire an emotional response than the whole image. However, existing methods perform poorly in predicting the details of emotional regions and are prone to overfitting during training due to the small size of the dataset. Therefore, this study proposes an image emotion classification network based on multilayer attentional interaction and adaptive feature aggregation. To perform more accurate emotional region prediction, this study designs a multilayer attentional… More >

Cong Lin¹, Chenghao Qiu¹, Can Wu¹, Siling Feng^1,*, Mengxing Huang^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4317-4340, 2023, DOI:10.32604/cmc.2023.036249

Abstract The random-value impulse noise (RVIN) detection approach in image denoising, which is dependent on manually defined detection thresholds or local window information, does not have strong generalization performance and cannot successfully cope with damaged pictures with high noise levels. The fusion of the K-means clustering approach in the noise detection stage is reviewed in this research, and the internal relationship between the flat region and the detail area of the damaged picture is thoroughly explored to suggest an unique two-stage method for gray image denoising. Based on the concept of pixel clustering and grouping, all pixels in the damaged picture… More >

Gamil Ahmed¹, Tarek Sheltami^1,*, Ashraf Mahmoud¹, Ansar Yasar²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3239-3263, 2023, DOI:10.32604/cmes.2023.022860

Abstract Unmanned aerial vehicles (UAVs), commonly known as drones, have drawn significant consideration thanks to their agility, mobility, and flexibility features. They play a crucial role in modern reconnaissance, inspection, intelligence, and surveillance missions. Coverage path planning (CPP) which is one of the crucial aspects that determines an intelligent system’s quality seeks an optimal trajectory to fully cover the region of interest (ROI). However, the flight time of the UAV is limited due to a battery limitation and may not cover the whole region, especially in large region. Therefore, energy consumption is one of the most challenging issues that need to… More >

Wei Jiang^1,2,*, Zelin Cao^3,4

Structural Durability & Health Monitoring, Vol.17, No.1, pp. 37-54, 2023, DOI:10.32604/sdhm.2022.013444

Abstract The attenuation relationship of ground motion based on seismology has always been a front subject of engineering earthquake. Among them, the regional finite-fault source model is very important. In view of this point, the general characteristics of regional seism-tectonics, including the dip and depth of the fault plane, are emphasized. According to the statistics of regional seism-tectonics and focal mechanisms in Sichuan, China, and the sensitivity of estimated peak ground acceleration (PGA) attenuation is analyzed, and the dip angle is taken as an average of 70°. Based the statistics of the upper crustal structure and the focal depth of regional… More >

Wen Long^*, Bin Zhu, Huaizheng Li, Yan Zhu, Zhiqiang Chen, Gang Cheng

Energy Engineering, Vol.120, No.5, pp. 1253-1269, 2023, DOI:10.32604/ee.2023.026395

Abstract There is instability in the distributed energy storage cloud group end region on the power grid side. In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components show a continuous and stable charging and discharging state, a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed. Firstly, a voltage stability analysis model based on multi-scale and multi feature convolution neural network is constructed, and the multi-scale and multi feature convolution neural network… More >

Jinrui Tang^*, Ganheng Ge, Jianchao Liu, Honghui Yang

Energy Engineering, Vol.120, No.5, pp. 1107-1132, 2023, DOI:10.32604/ee.2023.025666

Abstract Electric vehicle (EV) charging load is greatly affected by many traffic factors, such as road congestion. Accurate ultra short-term load forecasting (STLF) results for regional EV charging load are important to the scheduling plan of regional charging load, which can be derived to realize the optimal vehicle to grid benefit. In this paper, a regional-level EV ultra STLF method is proposed and discussed. The usage degree of all charging piles is firstly defined by us based on the usage frequency of charging piles, and then constructed by our collected EV charging transaction data in the field. Secondly, these usage degrees… More >

P. Malathi^1,*, G. Charlyn Pushpa Latha²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1741-1758, 2023, DOI:10.32604/csse.2023.035185

Abstract Breast cancer (BCa) is a leading cause of death in the female population across the globe. Approximately 2.3 million new BCa cases are recorded globally in females, overtaking lung cancer as the most prevalent form of cancer to be diagnosed. However, the mortality rates for cervical and BCa are significantly higher in developing nations than in developed countries. Early diagnosis is the only option to minimize the risks of BCa. Deep learning (DL)-based models have performed well in image processing in recent years, particularly convolutional neural network (CNN). Hence, this research proposes a DL-based CNN model to diagnose BCa from… More >

Mrityunjoy Gain¹, Md Arifur Rahman¹, Rameswar Debnath¹, Mrim M. Alnfiai², Abdullah Sheikh³, Mehedi Masud³, Anupam Kumar Bairagi^1,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1059-1077, 2023, DOI:10.32604/csse.2023.034809

Abstract Colorization is the practice of adding appropriate chromatic values to monochrome photographs or videos. A real-valued luminance image can be mapped to a three-dimensional color image. However, it is a severely ill-defined problem and not has a single solution. In this paper, an encoder-decoder Convolutional Neural Network (CNN) model is used for colorizing gray images where the encoder is a Densely Connected Convolutional Network (DenseNet) and the decoder is a conventional CNN. The DenseNet extracts image features from gray images and the conventional CNN outputs a * b * color channels. Due to a large number of desaturated color components compared to saturated… More >

Luli Li^1,2, Nigel G. Halford³, Huihui Wang⁴, Yingjie Zong¹, Zhenzhu Guo¹, Ruiju Lu¹, Chenghong Liu¹, Zhiwei Chen^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1275-1287, 2023, DOI:10.32604/phyton.2023.026946

Abstract Barley (Hordeum vulgare L.) is an important economic crop for food, feed and industrial raw materials. In the present research, 112 barley landraces from the Shanghai region were genotyped using genotyping-by-sequencing (GBS), and the genetic diversity and population structure were analyzed. The results showed that 210,268 Single Nucleotide Polymorphisms (SNPs) were present in total, and the average poly-morphism information content (PIC) was 0.1642. Genetic diversity and population structure analyses suggested that these barley landraces were differentiated and could be divided into three sub-groups, with morphological traits of row-type and adherence of the hulls the main distinguishing factors between groups. Genotypes… More >