Zeyi Wang¹, Mingxi Jiao¹, Daliang Wang¹, Minxu Liu¹, Minglei Jiang², He Wang³, Shiqiang Li^3,*

Energy Engineering, Vol.121, No.8, pp. 2275-2291, 2024, DOI:10.32604/ee.2024.028223

Abstract This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight method. Three different electrical quantities are selected as observations in the compressed sensing algorithm. The entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance levels. Subsequently, by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,… More >

Zerui Xiao, Wei Liu, Zhiwei Ye^*, Jiatang Yuan, Shishi Liu

Computer Systems Science and Engineering, Vol.48, No.4, pp. 1009-1029, 2024, DOI:10.32604/csse.2023.040475

Abstract Nowadays, construction site safety accidents are frequent, and wearing safety helmets is essential to prevent head injuries caused by object collisions and falls. However, existing helmet detection algorithms have several drawbacks, including a complex structure with many parameters, high calculation volume, and poor detection of small helmets, making deployment on embedded or mobile devices difficult. To address these challenges, this paper proposes a YOLOv5-based multi-head detection safety helmet detection algorithm that is faster and more robust for detecting helmets on construction sites. By replacing the traditional DarkNet backbone network of YOLOv5s with a new backbone… More >

Lirong Yin¹, Lei Wang¹, Siyu Lu^2,*, Ruiyang Wang², Haitao Ren², Ahmed AlSanad³, Salman A. AlQahtani³, Zhengtong Yin⁴, Xiaolu Li⁵, Wenfeng Zheng^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2315-2347, 2024, DOI:10.32604/cmes.2024.050853

Abstract At present, super-resolution algorithms are employed to tackle the challenge of low image resolution, but it is difficult to extract differentiated feature details based on various inputs, resulting in poor generalization ability. Given this situation, this study first analyzes the features of some feature extraction modules of the current super-resolution algorithm and then proposes an adaptive feature fusion block (AFB) for feature extraction. This module mainly comprises dynamic convolution, attention mechanism, and pixel-based gating mechanism. Combined with dynamic convolution with scale information, the network can extract more differentiated feature information. The introduction of a channel More >

Md. Atiqur Rahman¹, Mustavi Ibne Masum¹, Khan Md Hasib², M. F. Mridha^3,*, Sultan Alfarhood⁴, Mejdl Safran^4,*, Dunren Che⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2425-2448, 2024, DOI:10.32604/cmes.2024.050760

Abstract Brain tumors pose a significant threat to human lives and have gained increasing attention as the tenth leading cause of global mortality. This study addresses the pressing issue of brain tumor classification using Magnetic resonance imaging (MRI). It focuses on distinguishing between Low-Grade Gliomas (LGG) and High-Grade Gliomas (HGG). LGGs are benign and typically manageable with surgical resection, while HGGs are malignant and more aggressive. The research introduces an innovative custom convolutional neural network (CNN) model, Glioma-CNN. GliomaCNN stands out as a lightweight CNN model compared to its predecessors. The research utilized the BraTS 2020 More >

Yun-Jung Choi¹, Heewon Song^2,*

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 475-480, 2024, DOI:10.32604/ijmhp.2024.050824

Abstract During the rapid spread of COVID-19, first responders are at risk of being exposed to COVID-19 due to their role in providing first aid and responding to an unspecified number of people. This uncertainty can have adverse mental health effects, such as increased anxiety and fear. This study aimed to investigate the degree of association between fear of COVID-19, obsession with COVID-19, and post-traumatic stress disorder (PTSD) in emergency rescue firefighters. The participants were 150 emergency rescue firefighters working in Region S, Korea. They filled out self-report questionnaires: The data obtained through the Fear of… More >

Rui Zhang^1,2, Tonghai Liu^1,2,*, Wenzheng Liu^1,2, Chaungchuang Yuan^1,2, Xiaoyue Seng^1,2, Tiantian Guo^1,2, Xue Wang^1,2

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1275-1296, 2024, DOI:10.32604/phyton.2024.052397

Abstract Rice diseases can adversely affect both the yield and quality of rice crops, leading to the increased use of pesticides and environmental pollution. Accurate detection of rice diseases in natural environments is crucial for both operational efficiency and quality assurance. Deep learning-based disease identification technologies have shown promise in automatically discerning disease types. However, effectively extracting early disease features in natural environments remains a challenging problem. To address this issue, this study proposes the YOLO-CRD method. This research selected images of common rice diseases, primarily bakanae disease, bacterial brown spot, leaf rice fever, and dry… More >

Binyang Zhao¹, Fengchan Wu², Guojun Cai³, Peiyu Xi², Yulin Guo², Anding Li^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1345-1363, 2024, DOI:10.32604/phyton.2024.050950

Abstract In order to explore the response mechanism of Passiflora edulis Sims to drought stress, the changes in morphological and physiological traits of Passiflora edulis Sims under different drought conditions were studied. A total of 7 germplasm resources of Passiflora edulis Sims were selected and tested under drought stress by the pot culture method under 4 treatment levels: 75%–80% (Control, CK) of maximum field water capacity, 55%–60% (Light Drought, LD) of maximum field water capacity, i.e., mild drought, 40%–45% (Moderate Drought, MD) of maximum field water capacity, i.e., moderate drought and 30%–35% (Severe Drought, SD) of maximum field water… More >

Abdul Momin¹, Amana Khatoon^1,*, Wajahat Khan¹, Dilsat Bozdoğan Konuşkan², Muhammad Mudasar Aslam³, Muhammad Jamil⁴, Shafiq Ur Rehman⁵, Baber Ali⁶, Alevcan Kaplan⁷, Sana Wahab⁸, Muhammad Nauman Khan^9,*, Sezai Ercisli^10,11, Mohammad Khalid Al-Sadoon¹²

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1117-1128, 2024, DOI:10.32604/phyton.2024.048994

Abstract Sprouts are ready-to-eat and are recognized worldwide as functional components of the human diet. Recent advances in innovative agricultural techniques could enable an increase in the production of healthy food. The use of light-emitting diode (LED) in indoor agricultural production could alter the biological feedback loop, increasing the functional benefits of plant foods such as wheat and lentil sprouts and promoting the bioavailability of nutrients. The effects of white (W), red (R), and blue (B) light were investigated on the growth parameters and nutritional value of wheat and lentil sprouts. In the laboratory, seeds were… More >

Hui Tian¹, Dandan Zhao¹, Yannan Wu^2,3,*, Xingyu Yi¹, Jun Ma¹, Xiang Zhou⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1265-1277, 2024, DOI:10.32604/fdmp.2023.044833

Abstract The low porosity and low permeability of tight oil reservoirs call for improvements in the current technologies for oil recovery. Traditional chemical solutions with large molecular size cannot effectively flow through the nano-pores of the reservoir. In this study, the feasibility of Nanofluids has been investigated using a high pressure high temperature core-holder and nuclear magnetic resonance (NMR). The results of the experiments indicate that the specified Nanofluids can enhance the tight oil recovery significantly. The water and oil relative permeability curve shifts to the high water saturation side after Nanofluid flooding, thereby demonstrating an More > Graphic Abstract

Yan Liu¹, Tianli Sun², Bencheng Wang^1,*, Yan Feng²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1165-1180, 2024, DOI:10.32604/fdmp.2023.041852

Abstract A numerical model of hydraulic fracture propagation is introduced for a representative reservoir (Yuanba continental tight sandstone gas reservoir in Northeast Sichuan). Different parameters are considered, i.e., the interlayer stress difference, the fracturing discharge rate and the fracturing fluid viscosity. The results show that these factors affect the gas and water production by influencing the fracture size. The interlayer stress difference can effectively control the fracture height. The greater the stress difference, the smaller the dimensionless reconstruction volume of the reservoir, while the flowback rate and gas production are lower. A large displacement fracturing construction More >