Satellite remote sensing data are usually used to analyze the spatial distribution pattern of geological structures and generally serve as a significant means for the identification of alteration zones. Based on the L...Satellite remote sensing data are usually used to analyze the spatial distribution pattern of geological structures and generally serve as a significant means for the identification of alteration zones. Based on the Landsat Enhanced Thematic Mapper （ETM＋） data, which have better spectral resolution （8 bands） and spatial resolution （15 m in PAN band）, the synthesis processing techniques were presented to fulfill alteration information extraction： data preparation, vegetation indices and band ratios, and expert classifier-based classification. These techniques have been implemented in the MapGIS-RSP software （version 1.0）, developed by the Wuhan Zondy Cyber Technology Co., Ltd, China. In the study area application of extracting alteration information in the Zhaoyuan （招远） gold mines, Shandong （山东） Province, China, several hydorthermally altered zones （included two new sites） were found after satellite imagery interpretation coupled with field surveys. It is concluded that these synthesis processing techniques are useful approaches and are applicable to a wide range of gold-mineralized alteration information extraction.展开更多
According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteris...According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.展开更多
The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice,particularly in achieving accurate early diagnosis and risk stratification.While traditional approach...The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice,particularly in achieving accurate early diagnosis and risk stratification.While traditional approaches rely heavily on subjective interpretations and variable expertise,machine learning(ML)has emerged as a transformative tool in healthcare.We conducted a comprehensive review of published literature on ML applications in esophageal diseases,analyzing technical approaches,validation methods,and clinical outcomes.ML demonstrates superior performance:In gastroesophageal reflux disease,ML models achieve 80%-90%accuracy in potential of hydrogen-impedance analysis and endoscopic grading;for Barrett’s esophagus,ML-based approaches show 88%-95% accuracy in invasive diagnostics and 77%-85% accuracy in non-invasive screening.In esophageal cancer,ML improves early detection and survival prediction by 6%-10% compared to traditional methods.Novel applications in achalasia and esophageal varices demonstrate promising results in automated diagnosis and risk stratification,with accuracy rates exceeding 85%.While challenges persist in data standardization,model interpretability,and clinical integration,emerging solutions in federated learning and explainable artificial intelligence offer promising pathways forward.The continued evolution of these technologies,coupled with rigorous validation and thoughtful implementation,may fundamentally transform our approach to esophageal disease management in the era of precision medicine.展开更多
In order to meet the requirements of accurate identification of surface defects on copper strip in industrial production,a detection model of surface defects based on machine vision,CSC-YOLO,is proposed.The model uses...In order to meet the requirements of accurate identification of surface defects on copper strip in industrial production,a detection model of surface defects based on machine vision,CSC-YOLO,is proposed.The model uses YOLOv4-tiny as the benchmark network.First,K-means clustering is introduced into the benchmark network to obtain anchor frames that match the self-built dataset.Second,a cross-region fusion module is introduced in the backbone network to solve the difficult target recognition problem by fusing contextual semantic information.Third,the spatial pyramid pooling-efficient channel attention network(SPP-E)module is introduced in the path aggregation network(PANet)to enhance the extraction of features.Fourth,to prevent the loss of channel information,a lightweight attention mechanism is introduced to improve the performance of the network.Finally,the performance of the model is improved by adding adjustment factors to correct the loss function for the dimensional characteristics of the surface defects.CSC-YOLO was tested on the self-built dataset of surface defects in copper strip,and the experimental results showed that the mAP of the model can reach 93.58%,which is a 3.37% improvement compared with the benchmark network,and FPS,although decreasing compared with the benchmark network,reached 104.CSC-YOLO takes into account the real-time requirements of copper strip production.The comparison experiments with Faster RCNN,SSD300,YOLOv3,YOLOv4,Resnet50-YOLOv4,YOLOv5s,YOLOv7,and other algorithms show that the algorithm obtains a faster computation speed while maintaining a higher detection accuracy.展开更多
Sensitivity encoding(SENSE)is a parallel magnetic resonance imaging(MRI)reconstruction model by utilizing the sensitivity information of receiver coils to achieve image reconstruction.The existing SENSE-based reconstr...Sensitivity encoding(SENSE)is a parallel magnetic resonance imaging(MRI)reconstruction model by utilizing the sensitivity information of receiver coils to achieve image reconstruction.The existing SENSE-based reconstruction algorithms usually used nonadaptive sparsifying transforms,resulting in a limited reconstruction accuracy.Therefore,we proposed a new model for accurate parallel MRI reconstruction by combining the L0 norm regularization term based on the efficient sum of outer products dictionary learning(SOUPDIL)with the SENSE model,called SOUPDIL-SENSE.The SOUPDIL-SENSE model is mainly solved by utilizing the variable splitting and alternating direction method of multipliers techniques.The experimental results on four human datasets show that the proposed algorithm effectively promotes the image sparsity,eliminates the noise and artifacts of the reconstructed images,and improves the reconstruction accuracy.展开更多
Semantic segmentation provides important technical support for Land cover/land use(LCLU)research.By calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global...Semantic segmentation provides important technical support for Land cover/land use(LCLU)research.By calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global information of high-resolution remote sensing images.However,the diversity of detailed and edge features within the same class of ground objects in high-resolution remote sensing images leads to a dispersed embedding distribution.The dispersed feature distribution enlarges feature vector angles and reduces cosine similarity,weakening the attention mechanism’s ability to identify the same class of ground objects.To address this challenge,remote sensing image information granulation transformer for semantic segmentation is proposed.The model employs adaptive granulation to extract common semantic features among objects of the same class,constructing an information granule to replace the detailed feature representation of these objects.Then,the Laplacian operator of the information granule is applied to extract the edge features of the object as represented by the information granule.In the experiments,the proposed model was validated on the Beijing Land-Use(BLU),Gaofen Image Dataset(GID),and Potsdam Dataset(PD).In particular,the model achieves 88.81%for mOA,82.64%for mF1,and 71.50%for mIoU metrics on the GID dataset.Experimental results show that the model effectively handles high-resolution remote sensing images.Our code is available at https://github.com/sjmp525/RSIGT(accessed on 16 April 2025).展开更多
To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a ...To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.展开更多
Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar dynamics.This paper introduces an innovative unsupervised deep learning optical flow model designed to calcu...Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar dynamics.This paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the transverse velocity field,addressing the challenges of missing optical flow labels and the limited accuracy of velocity field measurements in high-resolution solar images.The proposed method converts the transverse velocity field computation problem into an optical flow computation problem,using two forward propagations of features to get rid of the reliance on optical flow labels.Additionally,it reduces the impact of the“Brightness Consistency”constraint on optical flow accuracy by identifying and handling optical flow outliers.We apply this method to compute the transverse velocity fields of high-resolution solar image sequences from the Hαand TiO bands,observed by the New Vacuum Solar Telescope.Comparative experiments with several wellestablished optical flow methods,including those based on supervised deep learning models,show that our approach outperforms the comparison methods according to key evaluation metrics such as Residual Map Mean,Residual Map Variance,Cross Correlation,and Structural Similarity Index Measure.Moreover,since optical flow captures the fundamental motion information in image sequences,the proposed method can be applied to a variety of research areas,including solar image registration,sequence alignment,image super-resolution,magnetic field calibration,and solar activity forecasting.The code is available at https://github.com/jackie-willianm/Transverse-Velocity-Field-Measurement-of-Solar-High-Resolution-Images.展开更多
The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect require...The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect requires the determination of the AC magnetic susceptibilityχ(f)of the TM.A torque method is proposed to measure theχ(f)of kg-level samples at the mHz band with a precision of 1×10^(-7).Combined with our previous work[Phys.Rev.Appl.18044010(2022)],the general frequency-dependent susceptibility of the alloy cube with side length L and electrical conductivityσis determined asχ(f)=χ0+(0.24±0.01)σμ0L^(2)f from 0.1 mHz to 1 Hz.The determination is helpful for the preliminary estimation of the in-band eddy current efect in the TianQin noise budget.The technique can be adopted to accurately measureχ(f)of the actual TM in other precision experiments,where the magnetic noise is a signifcant detection limit.展开更多
The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi...The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.展开更多
The MYB transcription factor is one of the largest gene families in plants,playing an important role in regulating plant growth,development,response to stress,senescence,and especially the anthocyanin biosynthesis.In ...The MYB transcription factor is one of the largest gene families in plants,playing an important role in regulating plant growth,development,response to stress,senescence,and especially the anthocyanin biosynthesis.In this study,A total of 217 MYB genes,including 901R-MYBs,124 R2R3-MYBs,and 3 R1R2R3-MYBs have been identified from the potato genome.The 1R-MYB and R2R3-MYB family members could be divided into 20 and 35 subgroups respectively.Analysis of gene structure and protein motifs revealed that members within the same subgroup presented similar exon/intron and motif organization,further supporting the results of phylogenetic analysis.Potato is an ideal plant to reveal the tissue-specific anthocyanins biosynthesis regulated by MYB,as the anthocyanins could be accumulated in different tissues,showing colorful phenotypes.Five pairs of colored and colorless tissues,stigma,petal,stem,leaf,and tuber flesh,were applied to the transcriptomic analysis.A total of 70 MYB genes were found to be differentially expressed between colored and colorless tissues,and these differentially expressed genes were suspected to regulate the biosynthesis of anthocyanin of different tissues.Co-expression analysis identified numerous potential interactive regulators of anthocyanins biosynthesis,involving 39 MYBs,24 bHLHs,2 WD-repeats,and 29 biosynthesis genes.Genome-wide association study(GWAS)of tuber flesh color revealed amajor signal at the end of Chromosome 10,which was co-localized with reported I gene(StMYB88),controlling tuber peel color.Analyses of DEGs(Differentially Expression Genes)revealed that both StMYB88 and StMYB89 were closely related to regulating anthocyanin biosynthesis of tuber flesh.This work offers a comprehensive overview of the MYB family in potato and will lay a foundation for the functional validation of these genes in the tissue-specific regulation of anthocyanin biosynthesis.展开更多
Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was eff...Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.展开更多
In order to derive the distribution of olivine and pyroxene in Crater Copernicus, we compute two band ratios （950/750 and 2 000/1 500 nm）, percent content of elements （Ai%, Ca%, Mg%, FeO%） and maturity （Is/FeO） ...In order to derive the distribution of olivine and pyroxene in Crater Copernicus, we compute two band ratios （950/750 and 2 000/1 500 nm）, percent content of elements （Ai%, Ca%, Mg%, FeO%） and maturity （Is/FeO） based on Clementine UVVIS and NIR image data. The central peaks of Copernicus, which are known to be olivine-rich or pyroxene-rich, are chosen as ＂ground truth＂ and ROIs used to derive the distribution of olivine and pyroxene with a decision tree and spectral angle mapper （SAM）. Additionally, we compared previous works and the extraction results coming from the decision tree and the SAM method. The extraction of olivine by both decision tree and SAM agrees well with the previous works＇ descriptions, and the result by SAM is more accurate than that by decision tree because spectral features are fully used in SAM. For pyroxene extraction, there is a difference between SAM and the decision tree; one of the reasons is that the decision tree does not fully take advantage of spectral features but is only based on statistics. SAM uses band indices that can be easily extended to other areas on the Moon.展开更多
Central nerve signal evoked by thoughts can be directly used to control a robot or prosthetic devices without the involvement of the peripheral nerve and muscles.This is a new strategy of human-computer interaction.A ...Central nerve signal evoked by thoughts can be directly used to control a robot or prosthetic devices without the involvement of the peripheral nerve and muscles.This is a new strategy of human-computer interaction.A method of electroencephalogram(EEG) phase synchronization combined with band energy was proposed to construct a feature vector for pattern recognition of brain-computer interaction based on EEG induced by motor imagery in this paper,rhythm and beta rhythm were first extracted from EEG by band pass filter and then the frequency band energy was calculated by the sliding time window;the instantaneous phase values were obtained using Hilbert transform and then the phase synchronization feature was calculated by the phase locking value(PLV) and the best time interval for extracting the phase synchronization feature was searched by the distribution of the PLV value in the time domain.Finally,discrimination of motor imagery patterns was performed by the support vector machine(SVM).The results showed that the phase synchronization feature more effective in4s-7s and the correct classification rate was 91.4%.Compared with the results achieved by a single EEG feature related to motor imagery,the correct classification rate was improved by 3.5 and4.3 percentage points by combining phase synchronization with band energy.These indicate that the proposed method is effective and it is expected that the study provides a way to improve the performance of the online real-time brain-computer interaction control system based on EEG related to motor imagery.展开更多
The exothermic efficiency of microwave heating an electrolyte/water solution is remarkably high due to the dielectric heating by orientation polarization of water and resistance heating by the Joule process occurred s...The exothermic efficiency of microwave heating an electrolyte/water solution is remarkably high due to the dielectric heating by orientation polarization of water and resistance heating by the Joule process occurred simultaneously compared with pure water.A three-dimensional finite element numerical model of multi-feed microwave heating industrial liquids continuously flowing in a meter-scale circular tube is presented.The temperature field inside the applicator tube in the cavity is solved by COMSOL Multiphysics and professional programming to describe the momentum,energy and Maxwell's equations.The evaluations of the electromagnetic field,the temperature distribution and the velocity field are simulated for the fluids dynamically heated by singleand multi-feed microwave system,respectively.Both the pilot experimental investigations and numerical results of microwave with single-feed heating for fluids with different effective permittivity and flow rates show that the presented numerical modeling makes it possible to analyze dynamic process of multi-feed microwave heating the industrial liquid.The study aids in enhancing the understanding and optimizing of dynamic process in the use of multi-feed microwave heating industrial continuous flow for a variety of material properties and technical parameters.展开更多
A construction method based on the p-plane to design high-girth quasi-cyclic low-density parity-check （QC-LDPC） codes is proposed. Firstly the good points in every line of the p-plane can be ascertained through filt...A construction method based on the p-plane to design high-girth quasi-cyclic low-density parity-check （QC-LDPC） codes is proposed. Firstly the good points in every line of the p-plane can be ascertained through filtering the bad points, because the designed parity-check matrixes using these points have the short cycles in Tanner graph of codes. Then one of the best points from the residual good points of every line in the p-plane will be found, respectively. The optimal point is also singled out according to the bit error rate （BER） performance of the QC-LDPC codes at last. Explicit necessary and sufficient conditions for the QC-LDPC codes to have no short cycles are presented which are in favor of removing the bad points in the p-plane. Since preventing the short cycles also prevents the small stopping sets, the proposed construction method also leads to QC-LDPC codes with a higher stopping distance.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
A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most...A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most of the existing recommender systems, only the purchase information is utilized data and the navigational and behavioral data are seldom concerned. In this paper, we design a novel recommender system for comprehensive online shopping sites. In the proposed recommender system, the navigational and behavioral data, such as access, click, read, and purchase information of a customer, are utilized to calculate the preference degree to each item; then items with larger preference degrees are recommended to the customer. The proposed method has several innovations and two of them are more remarkable: one is that nonexpendable items are distinguished from expendable ones and handled by a different way; another is that the interest shifting of customers are considered. Lastly, we structure an example to show the operation procedure and the performance of the proposed recommender system. The results show that the proposed recommender method with considering interest shifting is superior to Kim et al(2011) method and the method without considering interest shifting.展开更多
In recent years, China has suffered serious geological disasters, most of slope movements due to complex geology, geomorphology, unusual weather conditions, and large-scale land explorations during high speed economic...In recent years, China has suffered serious geological disasters, most of slope movements due to complex geology, geomorphology, unusual weather conditions, and large-scale land explorations during high speed economic development. According to geological hazard investigations organized by the Ministry of Land and Resources of China, there are 400 towns and more than 10 000 villages under the threatening of those landslide hazards. This paper presents the overview landslide hazard assessment in terms of GIS, which aims to evaluate the overview geohazard potentials, vulnerabilities of lives and land resources, and risks in conterminous China on the scale of 1∶6 000 000. This is the first overview landslide hazard potential map of China.展开更多
The emission sources of umbral flashes （UFs） are believed to be closely related to running umbral and penumbral waves, and are concluded to be associated with umbral dots in the solar photosphere. Accurate identific...The emission sources of umbral flashes （UFs） are believed to be closely related to running umbral and penumbral waves, and are concluded to be associated with umbral dots in the solar photosphere. Accurate identification of emission sources of UFs is crucial for investigating these physical phenomena and their inherent relationships. A relatively novel model of shape perception, namely phase congruency （PC）, uses phase information in the Fourier domain to identify the geometrical shape of the region of interest in different intensity levels, rather than intensity or gradient. Previous studies indicate that the model is suitable for identifying features with low contrast and low luminance. In the present paper, we applied the PC model to identify the emission sources of UFs and to locate their positions. For illustrating the high performance of our proposed method, two time sequences of Ca n H images derived from the Hinode/SOT on 2010 August 10 and 2013 August 20 were used. Furthermore, we also compared these results with the analysis results that are identified by the traditional/classical identification methods, including the gray-scale adjusted technique and the running difference technique. The result of our analysis demonstrates that our proposed method is more accurate and effective than the traditional identification methods when applied to identifying the emission sources of UFs and to locating their positions.展开更多
基金The paper is supported by the Research Foundation for Out-standing Young Teachers, China University of Geosciences (Wuhan) (Nos. CUGQNL0628, CUGQNL0640)the National High-Tech Research and Development Program (863 Program) (No. 2001AA135170)the Postdoctoral Foundation of the Shandong Zhaojin Group Co. (No. 20050262120)
文摘Satellite remote sensing data are usually used to analyze the spatial distribution pattern of geological structures and generally serve as a significant means for the identification of alteration zones. Based on the Landsat Enhanced Thematic Mapper （ETM＋） data, which have better spectral resolution （8 bands） and spatial resolution （15 m in PAN band）, the synthesis processing techniques were presented to fulfill alteration information extraction： data preparation, vegetation indices and band ratios, and expert classifier-based classification. These techniques have been implemented in the MapGIS-RSP software （version 1.0）, developed by the Wuhan Zondy Cyber Technology Co., Ltd, China. In the study area application of extracting alteration information in the Zhaoyuan （招远） gold mines, Shandong （山东） Province, China, several hydorthermally altered zones （included two new sites） were found after satellite imagery interpretation coupled with field surveys. It is concluded that these synthesis processing techniques are useful approaches and are applicable to a wide range of gold-mineralized alteration information extraction.
基金supported by the Undergraduate Education and Teaching Reform Research Project of Yunnan Province(JG2023157)Support Program for Yunnan Talents(CA23138L010A)+2 种基金Yunnan Higher Education Undergraduate Teaching Achievement Project(202246)National First class Undergraduate Course Construction Project of Software Engineering(109620210004)Software Engineering Virtual Teaching and Research Office Construction Project of Kunming University of Science and Technology(109620220031)。
文摘According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.
基金Supported by the Central Funds Guiding the Local Science and Technology Development,No.202207AB110017Key Research and Development Program of Yunnan,No.202302AD080004+1 种基金Yunnan Academician and Expert Workstation,No.202205AF150023the Scientific and Technological Innovation Team in Kunming Medical University,No.CXTD202215.
文摘The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice,particularly in achieving accurate early diagnosis and risk stratification.While traditional approaches rely heavily on subjective interpretations and variable expertise,machine learning(ML)has emerged as a transformative tool in healthcare.We conducted a comprehensive review of published literature on ML applications in esophageal diseases,analyzing technical approaches,validation methods,and clinical outcomes.ML demonstrates superior performance:In gastroesophageal reflux disease,ML models achieve 80%-90%accuracy in potential of hydrogen-impedance analysis and endoscopic grading;for Barrett’s esophagus,ML-based approaches show 88%-95% accuracy in invasive diagnostics and 77%-85% accuracy in non-invasive screening.In esophageal cancer,ML improves early detection and survival prediction by 6%-10% compared to traditional methods.Novel applications in achalasia and esophageal varices demonstrate promising results in automated diagnosis and risk stratification,with accuracy rates exceeding 85%.While challenges persist in data standardization,model interpretability,and clinical integration,emerging solutions in federated learning and explainable artificial intelligence offer promising pathways forward.The continued evolution of these technologies,coupled with rigorous validation and thoughtful implementation,may fundamentally transform our approach to esophageal disease management in the era of precision medicine.
基金the Key Project of Basic Research of Yunnan Province(No.202101AS070016)。
文摘In order to meet the requirements of accurate identification of surface defects on copper strip in industrial production,a detection model of surface defects based on machine vision,CSC-YOLO,is proposed.The model uses YOLOv4-tiny as the benchmark network.First,K-means clustering is introduced into the benchmark network to obtain anchor frames that match the self-built dataset.Second,a cross-region fusion module is introduced in the backbone network to solve the difficult target recognition problem by fusing contextual semantic information.Third,the spatial pyramid pooling-efficient channel attention network(SPP-E)module is introduced in the path aggregation network(PANet)to enhance the extraction of features.Fourth,to prevent the loss of channel information,a lightweight attention mechanism is introduced to improve the performance of the network.Finally,the performance of the model is improved by adding adjustment factors to correct the loss function for the dimensional characteristics of the surface defects.CSC-YOLO was tested on the self-built dataset of surface defects in copper strip,and the experimental results showed that the mAP of the model can reach 93.58%,which is a 3.37% improvement compared with the benchmark network,and FPS,although decreasing compared with the benchmark network,reached 104.CSC-YOLO takes into account the real-time requirements of copper strip production.The comparison experiments with Faster RCNN,SSD300,YOLOv3,YOLOv4,Resnet50-YOLOv4,YOLOv5s,YOLOv7,and other algorithms show that the algorithm obtains a faster computation speed while maintaining a higher detection accuracy.
基金the National Natural Science Foundation of China(No.61861023)the Yunnan Fundamental Research Project(No.202301AT070452)。
文摘Sensitivity encoding(SENSE)is a parallel magnetic resonance imaging(MRI)reconstruction model by utilizing the sensitivity information of receiver coils to achieve image reconstruction.The existing SENSE-based reconstruction algorithms usually used nonadaptive sparsifying transforms,resulting in a limited reconstruction accuracy.Therefore,we proposed a new model for accurate parallel MRI reconstruction by combining the L0 norm regularization term based on the efficient sum of outer products dictionary learning(SOUPDIL)with the SENSE model,called SOUPDIL-SENSE.The SOUPDIL-SENSE model is mainly solved by utilizing the variable splitting and alternating direction method of multipliers techniques.The experimental results on four human datasets show that the proposed algorithm effectively promotes the image sparsity,eliminates the noise and artifacts of the reconstructed images,and improves the reconstruction accuracy.
基金supported by the National Natural Science Foundation of China(62462040)the Yunnan Fundamental Research Projects(202501AT070345)+2 种基金the Major Science and Technology Projects in Yunnan Province(202202AD080013)Sichuan Provincial Key Laboratory of Philosophy and Social Science Key Program on Language Intelligence Special Education(YYZN-2024-1)the Photosynthesis Fund Class A(ghfund202407010460).
文摘Semantic segmentation provides important technical support for Land cover/land use(LCLU)research.By calculating the cosine similarity between feature vectors,transformer-based models can effectively capture the global information of high-resolution remote sensing images.However,the diversity of detailed and edge features within the same class of ground objects in high-resolution remote sensing images leads to a dispersed embedding distribution.The dispersed feature distribution enlarges feature vector angles and reduces cosine similarity,weakening the attention mechanism’s ability to identify the same class of ground objects.To address this challenge,remote sensing image information granulation transformer for semantic segmentation is proposed.The model employs adaptive granulation to extract common semantic features among objects of the same class,constructing an information granule to replace the detailed feature representation of these objects.Then,the Laplacian operator of the information granule is applied to extract the edge features of the object as represented by the information granule.In the experiments,the proposed model was validated on the Beijing Land-Use(BLU),Gaofen Image Dataset(GID),and Potsdam Dataset(PD).In particular,the model achieves 88.81%for mOA,82.64%for mF1,and 71.50%for mIoU metrics on the GID dataset.Experimental results show that the model effectively handles high-resolution remote sensing images.Our code is available at https://github.com/sjmp525/RSIGT(accessed on 16 April 2025).
基金the Foshan Science and Technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.
基金supported by the National Natural Science Foundation of China(NSFC,Grant Nos.12063002 and 12163004).
文摘Measuring the transverse velocity field in high-resolution solar images is essential for understanding solar dynamics.This paper introduces an innovative unsupervised deep learning optical flow model designed to calculate the transverse velocity field,addressing the challenges of missing optical flow labels and the limited accuracy of velocity field measurements in high-resolution solar images.The proposed method converts the transverse velocity field computation problem into an optical flow computation problem,using two forward propagations of features to get rid of the reliance on optical flow labels.Additionally,it reduces the impact of the“Brightness Consistency”constraint on optical flow accuracy by identifying and handling optical flow outliers.We apply this method to compute the transverse velocity fields of high-resolution solar image sequences from the Hαand TiO bands,observed by the New Vacuum Solar Telescope.Comparative experiments with several wellestablished optical flow methods,including those based on supervised deep learning models,show that our approach outperforms the comparison methods according to key evaluation metrics such as Residual Map Mean,Residual Map Variance,Cross Correlation,and Structural Similarity Index Measure.Moreover,since optical flow captures the fundamental motion information in image sequences,the proposed method can be applied to a variety of research areas,including solar image registration,sequence alignment,image super-resolution,magnetic field calibration,and solar activity forecasting.The code is available at https://github.com/jackie-willianm/Transverse-Velocity-Field-Measurement-of-Solar-High-Resolution-Images.
基金supported by the National Key R&D Program of China(Grant No.2020YFC2200500)the Key Laboratory of Tian Qin Project(Sun Yat-sen University),Ministry of Education+1 种基金the National Natural Science Foundation of China(Grant Nos.12075325,12005308,and 11605065)the Doctoral Research Foundation Project of Hubei University of Arts and Science(Grant No.kyqdf2059017)。
文摘The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect requires the determination of the AC magnetic susceptibilityχ(f)of the TM.A torque method is proposed to measure theχ(f)of kg-level samples at the mHz band with a precision of 1×10^(-7).Combined with our previous work[Phys.Rev.Appl.18044010(2022)],the general frequency-dependent susceptibility of the alloy cube with side length L and electrical conductivityσis determined asχ(f)=χ0+(0.24±0.01)σμ0L^(2)f from 0.1 mHz to 1 Hz.The determination is helpful for the preliminary estimation of the in-band eddy current efect in the TianQin noise budget.The technique can be adopted to accurately measureχ(f)of the actual TM in other precision experiments,where the magnetic noise is a signifcant detection limit.
基金Project(51090385) supported by the Major Program of National Natural Science Foundation of ChinaProject(2011IB001) supported by Yunnan Provincial Science and Technology Program,China+1 种基金Project(2012DFA70570) supported by the International Science & Technology Cooperation Program of ChinaProject(2011IA004) supported by the Yunnan Provincial International Cooperative Program,China
文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.
基金the National Natural Science Foundation of China(Grant No.31601756)the National Science Fund of Yunnan for Distinguished Young Scholars(Grant No.202001AV070003)。
文摘The MYB transcription factor is one of the largest gene families in plants,playing an important role in regulating plant growth,development,response to stress,senescence,and especially the anthocyanin biosynthesis.In this study,A total of 217 MYB genes,including 901R-MYBs,124 R2R3-MYBs,and 3 R1R2R3-MYBs have been identified from the potato genome.The 1R-MYB and R2R3-MYB family members could be divided into 20 and 35 subgroups respectively.Analysis of gene structure and protein motifs revealed that members within the same subgroup presented similar exon/intron and motif organization,further supporting the results of phylogenetic analysis.Potato is an ideal plant to reveal the tissue-specific anthocyanins biosynthesis regulated by MYB,as the anthocyanins could be accumulated in different tissues,showing colorful phenotypes.Five pairs of colored and colorless tissues,stigma,petal,stem,leaf,and tuber flesh,were applied to the transcriptomic analysis.A total of 70 MYB genes were found to be differentially expressed between colored and colorless tissues,and these differentially expressed genes were suspected to regulate the biosynthesis of anthocyanin of different tissues.Co-expression analysis identified numerous potential interactive regulators of anthocyanins biosynthesis,involving 39 MYBs,24 bHLHs,2 WD-repeats,and 29 biosynthesis genes.Genome-wide association study(GWAS)of tuber flesh color revealed amajor signal at the end of Chromosome 10,which was co-localized with reported I gene(StMYB88),controlling tuber peel color.Analyses of DEGs(Differentially Expression Genes)revealed that both StMYB88 and StMYB89 were closely related to regulating anthocyanin biosynthesis of tuber flesh.This work offers a comprehensive overview of the MYB family in potato and will lay a foundation for the functional validation of these genes in the tissue-specific regulation of anthocyanin biosynthesis.
基金Under the auspices of Fundamental Research Funds for Central Universities,China University of Geosciences(Wuhan)(No.CUGL150417)National Natural Science Foundation of China(No.41274036,41301026)
文摘Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.
基金supported by the Research Foundation of Science and Technology, China University of Geosciences (Wuhan)the Fundamental Research Funds for the Central Universities (No. 2010119047)
文摘In order to derive the distribution of olivine and pyroxene in Crater Copernicus, we compute two band ratios （950/750 and 2 000/1 500 nm）, percent content of elements （Ai%, Ca%, Mg%, FeO%） and maturity （Is/FeO） based on Clementine UVVIS and NIR image data. The central peaks of Copernicus, which are known to be olivine-rich or pyroxene-rich, are chosen as ＂ground truth＂ and ROIs used to derive the distribution of olivine and pyroxene with a decision tree and spectral angle mapper （SAM）. Additionally, we compared previous works and the extraction results coming from the decision tree and the SAM method. The extraction of olivine by both decision tree and SAM agrees well with the previous works＇ descriptions, and the result by SAM is more accurate than that by decision tree because spectral features are fully used in SAM. For pyroxene extraction, there is a difference between SAM and the decision tree; one of the reasons is that the decision tree does not fully take advantage of spectral features but is only based on statistics. SAM uses band indices that can be easily extended to other areas on the Moon.
基金supported by the National Natural Science Foundation of China(81470084,61463024)the Research Project for Application Foundation of Yunnan Province(2013FB026)+2 种基金the Cultivation Program of Talents of Yunnan Province(KKSY201303048)the Focal Program for Education Department of Yunnan Province(2013Z130)the Brain Information Processing and Brain-computer Interaction Fusion Control of Kunming University Scienceand Technology(Fund of Discipline Direction Team)
文摘Central nerve signal evoked by thoughts can be directly used to control a robot or prosthetic devices without the involvement of the peripheral nerve and muscles.This is a new strategy of human-computer interaction.A method of electroencephalogram(EEG) phase synchronization combined with band energy was proposed to construct a feature vector for pattern recognition of brain-computer interaction based on EEG induced by motor imagery in this paper,rhythm and beta rhythm were first extracted from EEG by band pass filter and then the frequency band energy was calculated by the sliding time window;the instantaneous phase values were obtained using Hilbert transform and then the phase synchronization feature was calculated by the phase locking value(PLV) and the best time interval for extracting the phase synchronization feature was searched by the distribution of the PLV value in the time domain.Finally,discrimination of motor imagery patterns was performed by the support vector machine(SVM).The results showed that the phase synchronization feature more effective in4s-7s and the correct classification rate was 91.4%.Compared with the results achieved by a single EEG feature related to motor imagery,the correct classification rate was improved by 3.5 and4.3 percentage points by combining phase synchronization with band energy.These indicate that the proposed method is effective and it is expected that the study provides a way to improve the performance of the online real-time brain-computer interaction control system based on EEG related to motor imagery.
基金Project(KKSY201503006)supported by Scientific Research Foundation of Kunming University of Science and Technology,ChinaProject(2014FD009)supported by the Applied Basic Research Foundation(Youth Program)of ChinaProject(51090385)supported by the National Natural Science Foundation of China
文摘The exothermic efficiency of microwave heating an electrolyte/water solution is remarkably high due to the dielectric heating by orientation polarization of water and resistance heating by the Joule process occurred simultaneously compared with pure water.A three-dimensional finite element numerical model of multi-feed microwave heating industrial liquids continuously flowing in a meter-scale circular tube is presented.The temperature field inside the applicator tube in the cavity is solved by COMSOL Multiphysics and professional programming to describe the momentum,energy and Maxwell's equations.The evaluations of the electromagnetic field,the temperature distribution and the velocity field are simulated for the fluids dynamically heated by singleand multi-feed microwave system,respectively.Both the pilot experimental investigations and numerical results of microwave with single-feed heating for fluids with different effective permittivity and flow rates show that the presented numerical modeling makes it possible to analyze dynamic process of multi-feed microwave heating the industrial liquid.The study aids in enhancing the understanding and optimizing of dynamic process in the use of multi-feed microwave heating industrial continuous flow for a variety of material properties and technical parameters.
基金supported by the National Natural Science Foundation of China (60572093)Specialized Research Fund for the Doctoral Program of Higher Education (20050004016)
文摘A construction method based on the p-plane to design high-girth quasi-cyclic low-density parity-check （QC-LDPC） codes is proposed. Firstly the good points in every line of the p-plane can be ascertained through filtering the bad points, because the designed parity-check matrixes using these points have the short cycles in Tanner graph of codes. Then one of the best points from the residual good points of every line in the p-plane will be found, respectively. The optimal point is also singled out according to the bit error rate （BER） performance of the QC-LDPC codes at last. Explicit necessary and sufficient conditions for the QC-LDPC codes to have no short cycles are presented which are in favor of removing the bad points in the p-plane. Since preventing the short cycles also prevents the small stopping sets, the proposed construction method also leads to QC-LDPC codes with a higher stopping distance.
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%.
基金supported by theNational High-Tech R&D Program (863 Program) No. 2015AA01A705the National Natural Science Foundation of China under Grant No. 61572072+2 种基金the National Science and Technology Major Project No. 2015ZX03001041Fundamental Research Funds for the Central Universities No. FRF-TP-15-027A3Yunnan Provincial Department of Education Foundation Project (No. 2014Y087)
文摘A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most of the existing recommender systems, only the purchase information is utilized data and the navigational and behavioral data are seldom concerned. In this paper, we design a novel recommender system for comprehensive online shopping sites. In the proposed recommender system, the navigational and behavioral data, such as access, click, read, and purchase information of a customer, are utilized to calculate the preference degree to each item; then items with larger preference degrees are recommended to the customer. The proposed method has several innovations and two of them are more remarkable: one is that nonexpendable items are distinguished from expendable ones and handled by a different way; another is that the interest shifting of customers are considered. Lastly, we structure an example to show the operation procedure and the performance of the proposed recommender system. The results show that the proposed recommender method with considering interest shifting is superior to Kim et al(2011) method and the method without considering interest shifting.
文摘In recent years, China has suffered serious geological disasters, most of slope movements due to complex geology, geomorphology, unusual weather conditions, and large-scale land explorations during high speed economic development. According to geological hazard investigations organized by the Ministry of Land and Resources of China, there are 400 towns and more than 10 000 villages under the threatening of those landslide hazards. This paper presents the overview landslide hazard assessment in terms of GIS, which aims to evaluate the overview geohazard potentials, vulnerabilities of lives and land resources, and risks in conterminous China on the scale of 1∶6 000 000. This is the first overview landslide hazard potential map of China.
基金supported by the National Natural Science Foundation of China (Nos. U1231205,11163004,11263004 and 11303011)the Open Research Program of Key Laboratory of Solar Activity of Chinese Academy of Sciences (No. KLSA201309)supported by the Opening Project of Key Laboratory of Astronomical Optics&Technology,Nanjing Institute of Astronomical Optics & Technology,Chinese Academy of Sciences (No. CAS-KLAOT-KF201306)
文摘The emission sources of umbral flashes （UFs） are believed to be closely related to running umbral and penumbral waves, and are concluded to be associated with umbral dots in the solar photosphere. Accurate identification of emission sources of UFs is crucial for investigating these physical phenomena and their inherent relationships. A relatively novel model of shape perception, namely phase congruency （PC）, uses phase information in the Fourier domain to identify the geometrical shape of the region of interest in different intensity levels, rather than intensity or gradient. Previous studies indicate that the model is suitable for identifying features with low contrast and low luminance. In the present paper, we applied the PC model to identify the emission sources of UFs and to locate their positions. For illustrating the high performance of our proposed method, two time sequences of Ca n H images derived from the Hinode/SOT on 2010 August 10 and 2013 August 20 were used. Furthermore, we also compared these results with the analysis results that are identified by the traditional/classical identification methods, including the gray-scale adjusted technique and the running difference technique. The result of our analysis demonstrates that our proposed method is more accurate and effective than the traditional identification methods when applied to identifying the emission sources of UFs and to locating their positions.
