Local geometric information and discontinuity features are key aspects of the analysis of the evolution and failure mechanisms of unstable rock blocks in rock tunnels.This study demonstrates the integration of terrest...Local geometric information and discontinuity features are key aspects of the analysis of the evolution and failure mechanisms of unstable rock blocks in rock tunnels.This study demonstrates the integration of terrestrial laser scanning(TLS)with distinct element method for rock mass characterization and stability analysis in tunnels.TLS records detailed geometric information of the surrounding rock mass by scanning and collecting the positions of millions of rock surface points without contact.By conducting a fuzzy K-means method,a discontinuity automatic identification algorithm was developed,and a method for obtaining the geometric parameters of discontinuities was proposed.This method permits the user to visually identify each discontinuity and acquire its spatial distribution features(e.g.occurrences,spac-ings,trace lengths)in great detail.Compared with hand mapping in conventional geotechnical surveys,the geometric information of discontinuities obtained by this approach is more accurate and the iden-tification is more efficient.Then,a discrete fracture network with the same statistical characteristics as the actual discontinuities was generated with the distinct element method,and a representative nu-merical model of the jointed surrounding rock mass was established.By means of numerical simulation,potential unstable rock blocks were assessed,and failure mechanisms were analyzed.This method was applied to detection and assessment of unstable rock blocks in the spillway and sand flushing tunnel of the Hongshiyan hydropower project after a collapse.The results show that the noncontact detection of blocks was more labor-saving with lower safety risks compared with manual surveys,and the stability assessment was more reliable since the numerical model built by this method was more consistent with the distribution characteristics of actual joints.This study can provide a reference for geological survey and unstable rock block hazard mitigation in tunnels subjected to complex geology and active rockfalls.展开更多
In recent years, automatic identification of butterfly species arouses more and more attention in different areas. Because most of their larvae are pests, this research is not only meaningful for the popularization of...In recent years, automatic identification of butterfly species arouses more and more attention in different areas. Because most of their larvae are pests, this research is not only meaningful for the popularization of science but also important to the agricultural production and the environment. Texture as a notable feature is widely used in digital image recognition technology; for describing the texture, an extremely effective method, graylevel co-occurrence matrix(GLCM), has been proposed and used in automatic identification systems. However,according to most of the existing works, GLCM is computed by the whole image, which likely misses some important features in local areas. To solve this problem, this paper presents a new method based on the GLCM features extruded from three image blocks, and a weight-based k-nearest neighbor(KNN) search algorithm used for classifier design. With this method, a butterfly classification system works on ten butterfly species which are hard to identify by shape features. The final identification accuracy is 98%.展开更多
With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway ...With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.展开更多
Type WYZ 97 eighteen information noninsulate frequency shift automatic blocking system is the most advanced railroad signaling system in China nowadays.The article introduced its principles,technical targets,features ...Type WYZ 97 eighteen information noninsulate frequency shift automatic blocking system is the most advanced railroad signaling system in China nowadays.The article introduced its principles,technical targets,features and the applications.展开更多
A 26-year-old male with a history of hypertrophic cardiomyopathy(HCM) and ventricular arrhythmias s/p automatic implantable cardioverter defibrillator(AICD) placement presented for open reduction and internal fixation...A 26-year-old male with a history of hypertrophic cardiomyopathy(HCM) and ventricular arrhythmias s/p automatic implantable cardioverter defibrillator(AICD) placement presented for open reduction and internal fixation of an open third metacarpal fracture and extensor tendon repair. He underwent successful surgery after placement of an ultrasound-guided infraclavicular brachial plexus block with ropivacaine 0.5% as the main anesthetic. This case report discusses the anesthetic management of patients with HCM and AICD, different approaches available for brachial plexus blockade, and potential complications of anesthesia and surgery in this group of patients.展开更多
Brain tumors are neoplastic diseases caused by the proliferation of abnormal cells in brain tissues,and their appearance may lead to a series of complex symptoms.However,current methods struggle to capture deeper brai...Brain tumors are neoplastic diseases caused by the proliferation of abnormal cells in brain tissues,and their appearance may lead to a series of complex symptoms.However,current methods struggle to capture deeper brain tumor image feature information due to the variations in brain tumor morphology,size,and complex background,resulting in low detection accuracy,high rate of misdiagnosis and underdiagnosis,and challenges in meeting clinical needs.Therefore,this paper proposes the CMS-YOLO network model for multi-category brain tumor detection,which is based on the You Only Look Once version 10(YOLOv10s)algorithm.This model innovatively integrates the Convolutional Medical UNet extended block(CMUNeXt Block)to design a brand-new CSP Bottleneck with 2 convolutions(C2f)structure,which significantly enhances the ability to extract features of the lesion area.Meanwhile,to address the challenge of complex backgrounds in brain tumor detection,a Multi-Scale Attention Aggregation(MSAA)module is introduced.The module integrates features of lesions at different scales,enabling the model to effectively capture multi-scale contextual information and enhance detection accuracy in complex scenarios.Finally,during the model training process,the Shape-IoU loss function is employed to replace the Complete-IoU(CIoU)loss function for optimizing bounding box regression.This ensures that the predicted bounding boxes generated by the model closely match the actual tumor contours,thereby further enhancing the detection precision.The experimental results show that the improved method achieves 94.80%precision,93.60%recall,96.20%score,and 79.60%on the MRI for Brain Tumor with Bounding Boxes dataset.Compared to the YOLOv10s model,this represents improvements of 1.0%,1.1%,1.0%,and 1.1%,respectively.The method can achieve automatic detection and localization of three distinct categories of brain tumors—glioma,meningioma,and pituitary tumor,which can accurately detect and identify brain tumors,assist doctors in early diagnosis,and promote the development of early treatment.展开更多
Aiming at the problems of low success rate and high seedling injury rate of automatic vegetable transplanting,this study focused on cabbage substrate block seedlings and developed a progressive push-out automatic seed...Aiming at the problems of low success rate and high seedling injury rate of automatic vegetable transplanting,this study focused on cabbage substrate block seedlings and developed a progressive push-out automatic seedling device controlled by a PLC system.Based on the friction mechanical properties of seedlings-tray during seedling taking,the collision rebound theoretical analysis of substrate block seedling delivery and the finite element simulation analysis of the seedling taking mechanism were carried out to determine the conditions for stable seedling taking and delivery of the device and the working parameters of the key mechanisms.To evaluate individual parameter effects,a test bench was built,and the effective ranges of key factors were subsequently determined.Three key experimental factors,the inclination angle of the limit guide plate,the seedling separation channel width,and the seedling separation cylinder pressure,were investigated using an L9(34)orthogonal array design with blockage rate and breakage rate as evaluation metrics.The range and variance analysis methods were employed to determine the relative significance of each factor’s influence on the performance indicators.The optimal parameters were determined as:the inclination angle of the limiting guide plate was 3.5°,the width of the seedling separation channel was 50 mm,and the pressure of the seedling separation cylinder was 0.6 MPa.Under these conditions,the seedling taking effect was significantly improved:the blockage rate was 2.46%,the breakage rate was 3.18%,and the seedling taking success rate was 94.36%.The optimal parameter combination was verified by the experiment:the average blockage rate was 3.23%,the average breakage rate was 3.68%,and the average success rate was 93.09%.Compared with the orthogonal experiment,the relative success rate error was 1.27%,indicating that the device has high stability.This study will provide a reference for the design of automatic vegetable transplanters.展开更多
This article about possibility of automations of choice of instrumental equipment. In it described problems of choice of equipment, which are decided by means of mathematical model, developed on the base of finite ele...This article about possibility of automations of choice of instrumental equipment. In it described problems of choice of equipment, which are decided by means of mathematical model, developed on the base of finite element method.展开更多
基金support of the National Natural Science Foundation of China(Grant No.42102316)the Open Project of the Technology Innovation Center for Geological Environment Monitoring of Ministry of Natural Resources of China(Grant No.2022KFK1212005).
文摘Local geometric information and discontinuity features are key aspects of the analysis of the evolution and failure mechanisms of unstable rock blocks in rock tunnels.This study demonstrates the integration of terrestrial laser scanning(TLS)with distinct element method for rock mass characterization and stability analysis in tunnels.TLS records detailed geometric information of the surrounding rock mass by scanning and collecting the positions of millions of rock surface points without contact.By conducting a fuzzy K-means method,a discontinuity automatic identification algorithm was developed,and a method for obtaining the geometric parameters of discontinuities was proposed.This method permits the user to visually identify each discontinuity and acquire its spatial distribution features(e.g.occurrences,spac-ings,trace lengths)in great detail.Compared with hand mapping in conventional geotechnical surveys,the geometric information of discontinuities obtained by this approach is more accurate and the iden-tification is more efficient.Then,a discrete fracture network with the same statistical characteristics as the actual discontinuities was generated with the distinct element method,and a representative nu-merical model of the jointed surrounding rock mass was established.By means of numerical simulation,potential unstable rock blocks were assessed,and failure mechanisms were analyzed.This method was applied to detection and assessment of unstable rock blocks in the spillway and sand flushing tunnel of the Hongshiyan hydropower project after a collapse.The results show that the noncontact detection of blocks was more labor-saving with lower safety risks compared with manual surveys,and the stability assessment was more reliable since the numerical model built by this method was more consistent with the distribution characteristics of actual joints.This study can provide a reference for geological survey and unstable rock block hazard mitigation in tunnels subjected to complex geology and active rockfalls.
基金the Yunnan Applied Basic Research Projects(No.2016FD039)the Talent Cultivation Project in Yunnan Province(No.KKSY201503063)
文摘In recent years, automatic identification of butterfly species arouses more and more attention in different areas. Because most of their larvae are pests, this research is not only meaningful for the popularization of science but also important to the agricultural production and the environment. Texture as a notable feature is widely used in digital image recognition technology; for describing the texture, an extremely effective method, graylevel co-occurrence matrix(GLCM), has been proposed and used in automatic identification systems. However,according to most of the existing works, GLCM is computed by the whole image, which likely misses some important features in local areas. To solve this problem, this paper presents a new method based on the GLCM features extruded from three image blocks, and a weight-based k-nearest neighbor(KNN) search algorithm used for classifier design. With this method, a butterfly classification system works on ten butterfly species which are hard to identify by shape features. The final identification accuracy is 98%.
文摘With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.
文摘Type WYZ 97 eighteen information noninsulate frequency shift automatic blocking system is the most advanced railroad signaling system in China nowadays.The article introduced its principles,technical targets,features and the applications.
文摘A 26-year-old male with a history of hypertrophic cardiomyopathy(HCM) and ventricular arrhythmias s/p automatic implantable cardioverter defibrillator(AICD) placement presented for open reduction and internal fixation of an open third metacarpal fracture and extensor tendon repair. He underwent successful surgery after placement of an ultrasound-guided infraclavicular brachial plexus block with ropivacaine 0.5% as the main anesthetic. This case report discusses the anesthetic management of patients with HCM and AICD, different approaches available for brachial plexus blockade, and potential complications of anesthesia and surgery in this group of patients.
基金supported in part by the National Natural Science Foundation of China under Grants 61861007in part by the Guizhou Province Science and Technology Planning Project ZK[2021]303in part by the Guizhou Province Science Technology Support Plan under Grants[2022]264,[2023]096,[2023]412 and[2023]409.
文摘Brain tumors are neoplastic diseases caused by the proliferation of abnormal cells in brain tissues,and their appearance may lead to a series of complex symptoms.However,current methods struggle to capture deeper brain tumor image feature information due to the variations in brain tumor morphology,size,and complex background,resulting in low detection accuracy,high rate of misdiagnosis and underdiagnosis,and challenges in meeting clinical needs.Therefore,this paper proposes the CMS-YOLO network model for multi-category brain tumor detection,which is based on the You Only Look Once version 10(YOLOv10s)algorithm.This model innovatively integrates the Convolutional Medical UNet extended block(CMUNeXt Block)to design a brand-new CSP Bottleneck with 2 convolutions(C2f)structure,which significantly enhances the ability to extract features of the lesion area.Meanwhile,to address the challenge of complex backgrounds in brain tumor detection,a Multi-Scale Attention Aggregation(MSAA)module is introduced.The module integrates features of lesions at different scales,enabling the model to effectively capture multi-scale contextual information and enhance detection accuracy in complex scenarios.Finally,during the model training process,the Shape-IoU loss function is employed to replace the Complete-IoU(CIoU)loss function for optimizing bounding box regression.This ensures that the predicted bounding boxes generated by the model closely match the actual tumor contours,thereby further enhancing the detection precision.The experimental results show that the improved method achieves 94.80%precision,93.60%recall,96.20%score,and 79.60%on the MRI for Brain Tumor with Bounding Boxes dataset.Compared to the YOLOv10s model,this represents improvements of 1.0%,1.1%,1.0%,and 1.1%,respectively.The method can achieve automatic detection and localization of three distinct categories of brain tumors—glioma,meningioma,and pituitary tumor,which can accurately detect and identify brain tumors,assist doctors in early diagnosis,and promote the development of early treatment.
基金supported by the Fundamental Research Fund of the Chinese Academy of Agricultural Sciences at the Institute Level(Grant No.S202409)Jiangsu Modern Agricultural Machinery Equipment and Technology Demonstration and Promotion Project(Grant No.NJ2023-11)+2 种基金National Key R&D Program of China(Grant No.2023YFD2300700)Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in Southeastern China(Co-construction by Ministry and Province)Ministry of Agriculture and Rural Affairs(Grant No.QSKF2023006).
文摘Aiming at the problems of low success rate and high seedling injury rate of automatic vegetable transplanting,this study focused on cabbage substrate block seedlings and developed a progressive push-out automatic seedling device controlled by a PLC system.Based on the friction mechanical properties of seedlings-tray during seedling taking,the collision rebound theoretical analysis of substrate block seedling delivery and the finite element simulation analysis of the seedling taking mechanism were carried out to determine the conditions for stable seedling taking and delivery of the device and the working parameters of the key mechanisms.To evaluate individual parameter effects,a test bench was built,and the effective ranges of key factors were subsequently determined.Three key experimental factors,the inclination angle of the limit guide plate,the seedling separation channel width,and the seedling separation cylinder pressure,were investigated using an L9(34)orthogonal array design with blockage rate and breakage rate as evaluation metrics.The range and variance analysis methods were employed to determine the relative significance of each factor’s influence on the performance indicators.The optimal parameters were determined as:the inclination angle of the limiting guide plate was 3.5°,the width of the seedling separation channel was 50 mm,and the pressure of the seedling separation cylinder was 0.6 MPa.Under these conditions,the seedling taking effect was significantly improved:the blockage rate was 2.46%,the breakage rate was 3.18%,and the seedling taking success rate was 94.36%.The optimal parameter combination was verified by the experiment:the average blockage rate was 3.23%,the average breakage rate was 3.68%,and the average success rate was 93.09%.Compared with the orthogonal experiment,the relative success rate error was 1.27%,indicating that the device has high stability.This study will provide a reference for the design of automatic vegetable transplanters.
文摘This article about possibility of automations of choice of instrumental equipment. In it described problems of choice of equipment, which are decided by means of mathematical model, developed on the base of finite element method.
