Rui Jiang^1,3,*, Kaisheng Lai², Jianping Xu¹, Xiang Feng¹, Shaoye Wang¹, Xiaojian Wang³, Zhe Liu²

Congenital Heart Disease, Vol.17, No.6, pp. 675-686, 2022, DOI:10.32604/chd.2022.021626

Abstract Background: The etiology of pulmonary arterial hypertension associated with congenital heart disease (PAHCHD) is complicated and the phenotype is heterogeneous. Genetic defects of NOTCH3 were associated with cerebral disease and pulmonary hypertension. However, the relationship between NOTCH3 mutations and the clinical phenotype has not been reported in CHD-PAH. Methods: We eventually enrolled 142 PAH-CHD patients from Fuwai Hospital. Whole exome sequencing (WES) was performed to screen the rare deleterious variants of NOTCH3 gene. Results: This PAH-CHD cohort included 43 (30.3%) men and 99 (69.7%) women with the mean age 29.8 ± 10.9 years old. The pathogenic or likely pathogenic mutations… More >

Sihua Wang^1,2, Wenhui Zhang^1,2,*, Gaofei Zheng^1,2, Xujie Li^1,2, Yougeng Zhao^1,2

Energy Engineering, Vol.119, No.6, pp. 2431-2445, 2022, DOI:10.32604/ee.2022.020779

Abstract In order to improve the condition monitoring and fault diagnosis of wind turbines, a stacked noise reduction autoencoding network based on group normalization is proposed in this paper. The network is based on SCADA data of wind turbine operation, firstly, the group normalization (GN) algorithm is added to solve the problems of stack noise reduction autoencoding network training and slow convergence speed, and the RMSProp algorithm is used to update the weight and the bias of the autoenccoder, which further optimizes the problem that the loss function swings too much during the update process. Finally, in the last layer of… More >

Belayneh Yitayew^1,*, Wondwossen Bogale²

Energy Engineering, Vol.119, No.6, pp. 2513-2532, 2022, DOI:10.32604/ee.2022.018961

Abstract Energy is one of the most important factors in socio-economic development. The rapid increase in energy demand and air pollution has increased the number of ways to generate energy in the power sector. Currently, wind energy capacity in Ethiopia is estimated at 10,000 MW. Of these, however, only eight percent of its capacity has been used in recent years. One of the reasons for the low use of wind energy is the lack of accurate wind atlases in the country. Therefore, the purpose of this study is to develop an accurate wind atlas and review the wind resources using Wind… More >

R. Punithavathi¹, A. Delphin Carolina Rani², K. R. Sughashini³, Chinnarao Kurangi⁴, M. Nirmala⁵, Hasmath Farhana Thariq Ahmed⁶, S. P. Balamurugan^7,*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2759-2774, 2023, DOI:10.32604/csse.2023.027647

Abstract Presently, precision agriculture processes like plant disease, crop yield prediction, species recognition, weed detection, and irrigation can be accomplished by the use of computer vision (CV) approaches. Weed plays a vital role in influencing crop productivity. The wastage and pollution of farmland's natural atmosphere instigated by full coverage chemical herbicide spraying are increased. Since the proper identification of weeds from crops helps to reduce the usage of herbicide and improve productivity, this study presents a novel computer vision and deep learning based weed detection and classification (CVDL-WDC) model for precision agriculture. The proposed CVDL-WDC technique intends to properly discriminate the… More >

V. Nirmala^1,*, B. Gomathy²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2585-2601, 2023, DOI:10.32604/csse.2023.027512

Abstract In agricultural engineering, the main challenge is on methodologies used for disease detection. The manual methods depend on the experience of the personal. Due to large variation in environmental condition, disease diagnosis and classification becomes a challenging task. Apart from the disease, the leaves are affected by climate changes which is hard for the image processing method to discriminate the disease from the other background. In Cucurbita gourd family, the disease severity examination of leaf samples through computer vision, and deep learning methodologies have gained popularity in recent years. In this paper, a hybrid method based on Convolutional Neural Network… More >

Yuchen Hao^*, Dawei Su, Zhen Lei

Energy Engineering, Vol.119, No.5, pp. 2081-2104, 2022, DOI:10.32604/ee.2022.021342

Abstract Renewable energy sources (RES) such as wind turbines (WT) and solar cells have attracted the attention of power system operators and users alike, thanks to their lack of environmental pollution, independence of fossil fuels, and meager marginal costs. With the introduction of RES, challenges have faced the unit commitment (UC) problem as a traditional power system optimization problem aiming to minimize total costs by optimally determining units’ inputs and outputs, and specifying the optimal generation of each unit. The output power of RES such as WT and solar cells depends on natural factors such as wind speed and solar irradiation… More >

Saud S. Alotaibi^*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1815-1829, 2023, DOI:10.32604/iasc.2023.029446

Abstract One of the most critical objectives of precision farming is to assess the germination quality of seeds. Modern models contribute to this field primarily through the use of artificial intelligence techniques such as machine learning, which present difficulties in feature extraction and optimization, which are critical factors in predicting accuracy with few false alarms, and another significant difficulty is assessing germination quality. Additionally, the majority of these contributions make use of benchmark classification methods that are either inept or too complex to train with the supplied features. This manuscript addressed these issues by introducing a novel ensemble classification strategy dubbed… More >

Anwer H. Hussein^*, Hussam K. Risan

Structural Durability & Health Monitoring, Vol.16, No.3, pp. 213-233, 2022, DOI:10.32604/sdhm.2022.018293

Abstract Silos are strategical structures used to stockpile various types of granular materials. They are highly vulnerable to earthquake excitation and have been frequently reported to fail at a higher rate than any other industrial structure. The seismic response of silos within the near-fault region will suffer a complex combination of loadings due to the unique characteristics of the near-fault ground motions; which are usually associated with a large amplitude pulse at the beginning of either the velocity or the displacement time histories. This study aims to numerically evaluate the seismic response of reinforced concrete cylindrical silos under near-fault ground motions… More >

Gyung Deok Han¹, Dae Ho Jung², Seong Heo^3,*, Yong Suk Chung^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2583-2590, 2022, DOI:10.32604/phyton.2022.022866

Abstract In the smart farm, we can control every detail for production. Collecting every factor that affects the crop’s final yield is necessary to optimize its efficiency. The SPAD values were observed in the ‘Star’ cultivar blueberry (Vaccinium darrowii) three times a day and at three different plant heights. The pattern of SPAD value change was different by the planting position. Ground planted blueberry (V. darrowii) represented a stable SPAD value during the day and at the different heights. However, the SPAD value was increased by time in pot-planted blueberry (V. darrowii). Also, the SPAD value of pot-planted blueberry was lower… More >

Yehong Dong^1,2, Guangyin Tang³, Yan Jia⁴, Zekun Wang^4,5, Xiaomin Rong⁵, Chang Cai⁵, Qingan Li⁵, Yingjian Yang^4,5,*

Energy Engineering, Vol.119, No.4, pp. 1341-1360, 2022, DOI:10.32604/ee.2022.019150

Abstract In recent years, the construction of offshore wind farms is developing rapidly. As the wake effect of the upstream wind turbines seriously affect the performance of the downstream wind turbines, the wake effect of offshore wind turbines has become one of the research hotspots. First, this article reviews the research methods of wake effects, including CFD numerical simulation method, wind turbine wake model based on roughness and engineering wake models. However, there is no general model that can be used directly. Then it puts forward some factors that affect the wake of offshore wind turbines. The turbulence intensity in offshore… More > Graphic Abstract