Digitization of education is an important component of Digital China Strategy. China is deeply implementing the digitalization of education strategy, promoting educational reform and innovation, and accelerating the c...Digitization of education is an important component of Digital China Strategy. China is deeply implementing the digitalization of education strategy, promoting educational reform and innovation, and accelerating the construction of a learning society and a learning country where everyone can learn, learn everywhere, and learn at all times [1]. As the cradle and gathering place of talent cultivation, universities should be at the forefront of educational informatization construction. As a comprehensive energy university in the northeastern region of Sichuan, the Nanchong Campus of Southwest Petroleum University plays an irreplaceable role in the local economic development. This article summarizes the current situation of educational informatization construction on this campus and proposes suggestions for its improvement path, providing constructive reference opinions for the development of similar universities.展开更多
As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become ...As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.展开更多
Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent...Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.展开更多
The current parameter estimation algorithms of chirp rate have high complexity and long calculation time,meantime they are difficult to achieve high estimation rate. Therefore,in order to overcome these problems,in th...The current parameter estimation algorithms of chirp rate have high complexity and long calculation time,meantime they are difficult to achieve high estimation rate. Therefore,in order to overcome these problems,in this paper,a new parameter estimation algorithm based on Holder coefficient is presented. Firstly,this algorithm calculates the correlation curve of the Holder coefficient value under different chirp rate. Secondly,this algorithm calculates the correlation curve under different SNR. Finally,the fitting curve expression can be got by the correlation curve,and then the estimation value of chirp rate can also be got. The theory analysis and simulation results show that this algorithm is simple and easy to realize,and has much better application value for real-time estimation.展开更多
The optical response of metal nanoparticles can be modified through near-field or far-field interaction,yet the lattice plasmon modes(LPMs)considered can only be excited from the latter.Here instead,we present a theor...The optical response of metal nanoparticles can be modified through near-field or far-field interaction,yet the lattice plasmon modes(LPMs)considered can only be excited from the latter.Here instead,we present a theoretical evaluation for LPM excitation via the near-field coupling process.The sample is an arrayed structure with specific units composed of upper metal disks,a lower metal hole and a sandwiched dielectric post.The excitation process and underlying mechanism of the LPM and the influence of the structure parameters on the optical properties have been investigated in detail by using a finite-difference time-domain(FDTD)numerical method.Our investigation presented here should advance the understanding of near-field interaction of plasmon modes for LPM excitation,and LPMs could find some potential applications,such as in near-field optical microscopes,biosensors,optical filters and plasmonic lasers.展开更多
乳腺癌是目前全球发病率最高的恶性肿瘤之一,其中三阴性乳腺癌(triple-negative breast cancer,TNBC)占浸润性乳腺癌的10%~20%。TNBC是一种高度异质性和侵袭性的恶性肿瘤,与其他乳腺癌亚型相比,TNBC治疗手段相对匮乏,预后较差,临床上亟...乳腺癌是目前全球发病率最高的恶性肿瘤之一,其中三阴性乳腺癌(triple-negative breast cancer,TNBC)占浸润性乳腺癌的10%~20%。TNBC是一种高度异质性和侵袭性的恶性肿瘤,与其他乳腺癌亚型相比,TNBC治疗手段相对匮乏,预后较差,临床上亟待寻找可用于精准治疗及提高预后的新靶点。人滋养层细胞表面抗原2(trophoblast cell surface antigen 2,Trop2)在三阴性乳腺癌及多种恶性肿瘤中高表达,其通过细胞表面受体信号在肿瘤细胞的增殖、黏附、侵袭、转移中发挥重要作用,以其为靶点的抗体偶联药物(antibody-drug conjugate,ADC)在临床上中具有广阔的应用前景。本文对靶向Trop2的ADC治疗TNBC的临床研究进展予以综述,为靶向Trop2的ADC在TNBC治疗中的临床应用和提高患者生存预后方面提供参考。展开更多
Deep Learning(DL)is such a powerful tool that we have seen tremendous success in areas such as Computer Vision,Speech Recognition,and Natural Language Processing.Since Automated Modulation Classification(AMC)is an imp...Deep Learning(DL)is such a powerful tool that we have seen tremendous success in areas such as Computer Vision,Speech Recognition,and Natural Language Processing.Since Automated Modulation Classification(AMC)is an important part in Cognitive Radio Networks,we try to explore its potential in solving signal modulation recognition problem.It cannot be overlooked that DL model is a complex model,thus making them prone to over-fitting.DL model requires many training data to combat with over-fitting,but adding high quality labels to training data manually is not always cheap and accessible,especially in real-time system,which may counter unprecedented data in dataset.Semi-supervised Learning is a way to exploit unlabeled data effectively to reduce over-fitting in DL.In this paper,we extend Generative Adversarial Networks(GANs)to the semi-supervised learning will show it is a method can be used to create a more dataefficient classifier.展开更多
AIM To evaluate the usefulness of different parameters to differentiate Crohn's disease(CD) from primary intestinal lymphoma(PIL).METHODS The medical records of 85 patients with CD and 56 patients with PIL were re...AIM To evaluate the usefulness of different parameters to differentiate Crohn's disease(CD) from primary intestinal lymphoma(PIL).METHODS The medical records of 85 patients with CD and 56 patients with PIL were reviewed retrospectively. Demographic, clinical, laboratory, endoscopic, and computed tomographic enterography(CTE) parameters were collected. The univariate value of each parameter was analyzed. A differentiation model was established by pooling all the valuable parameters. Diagnostic efficacy was analyzed, and a receiver operating characteristic(ROC) curve was plotted.RESULTS The demographic and clinical parameters that showed significant values for differentiating CD from PIL included age of onset, symptom duration, presence of diarrhea, abdominal mass, and perianal lesions(P < 0.05). Elevated lactate dehydrogenase and serum β2-microglobulin levels suggested a PIL diagnosis(P < 0.05). The endoscopic parameters that showed significant values for differentiating CD from PIL included multiple-site lesions, longitudinal ulcer, irregular ulcer,and intraluminal proliferative mass(P < 0.05). The CTE parameters that were useful in the identification of the two conditions included involvement of ≤ 3 segments, circular thickening of the bowel wall, wall thickness > 8 mm, aneurysmal dilation, stricture with proximal dilation, "comb sign", mass showing the "sandwich sign", and intussusceptions(P < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the differentiation model were 91.8%, 96.4%, 93.6%, 97.5%, and 88.5%, respectively. The cutoff value was 0.5. The area under the ROC curve was 0.989.CONCLUSION The differentiation model that integrated the various parameters together may yield a high diagnostic efficacy in the differential diagnosis between CD and PIL.展开更多
The molecular mechanism of DNA damage induced by hydroquinone （HQ） remains unclear. Poly（ADP-ribose） polymerase-1 （PARP-1） usually works as a DNA damage sensor, and hence, it is possible that PARP-1 is involved ...The molecular mechanism of DNA damage induced by hydroquinone （HQ） remains unclear. Poly（ADP-ribose） polymerase-1 （PARP-1） usually works as a DNA damage sensor, and hence, it is possible that PARP-1 is involved in the DNA damage response induced by HQ. In TK6 cells treated with HQ, PARP activity as well as the expression of apoptosis antagonizing transcription factor （AATF）, PARP-1, and phosphorylated H2AX （v-H2AX） were maximum at 0.5 h, 6 h, 3 h, and 3 h, respectively. To explore the detailed mechanisms underlying the prompt DNA repair reaction, the above indicators were investigated in PARP-l-silenced cells. PARP activity and expression of AATF and PARP-1 decreased to 36%, 32%, and 33%, respectively, in the cells; however, y-H2AX expression increased to 265%. Co-immunoprecipitation （co-IP） assays were employed to determine whether PARP-1 and AATF formed protein complexes. The interaction between these proteins together with the results from IP assays and confocal microscopy indicated that poly（ADP-ribosyl）ation {PARylation） regulated AATF expression, in conclusion, PARP-1 was involved in the DNA damage repair induced by HQ via increasing the accumulation of AATF through PARylation.展开更多
In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firs...In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.展开更多
The conventional sparse representation-based image classification usually codes the samples independently,which will ignore the correlation information existed in the data.Hence,if we can explore the correlation infor...The conventional sparse representation-based image classification usually codes the samples independently,which will ignore the correlation information existed in the data.Hence,if we can explore the correlation information hidden in the data,the classification result will be improved significantly.To this end,in this paper,a novel weighted supervised spare coding method is proposed to address the image classification problem.The proposed method firstly explores the structural information sufficiently hidden in the data based on the low rank representation.And then,it introduced the extracted structural information to a novel weighted sparse representation model to code the samples in a supervised way.Experimental results show that the proposed method is superiority to many conventional image classification methods.展开更多
Traditional Sobel algorithm is deeply influenced by Gaussian noise,therefore,before boundary extraction,mean filter should be done. But the filtering process is always over-smooth images'details of certain directi...Traditional Sobel algorithm is deeply influenced by Gaussian noise,therefore,before boundary extraction,mean filter should be done. But the filtering process is always over-smooth images'details of certain directions,so that images'edges will not be extracted correctly. Aiming at this problem,this paper puts forward a detection algorithm based on edge-preserving characteristics,by matching edge mould of different directions to definite edge preserving directions. Instead of the mean filter process,this algorithm improves the performance of traditional algorithms,and provides the simulation results. The experiment results prove that this algorithm preserves more images'edge information when canceling noise.展开更多
Time series of MODIS land surface temperature(Ts) and normalized difference vegetation index(NDVI) products,combined with digital elevation model(DEM) and meteorological data from 2001 to 2012,were used to map the spa...Time series of MODIS land surface temperature(Ts) and normalized difference vegetation index(NDVI) products,combined with digital elevation model(DEM) and meteorological data from 2001 to 2012,were used to map the spatial distribution of monthly mean air temperature over the Northern Tibetan Plateau(NTP). A time series analysis and a regression analysis of monthly mean land surface temperature(Ts) and air temperature(Ta) were conducted using ordinary linear regression(OLR) and geographical weighted regression(GWR). The analyses showed that GWR,which considers MODIS Ts,NDVI and elevation as independent variables,yielded much better results [RAdj2> 0.79; root-mean-square error(RMSE) =0.51℃–1.12℃] associated with estimating Tacompared to those from OLR(RAdj2= 0.40-0.78; RMSE = 1.60℃–4.38℃).In addition,some characteristics of the spatial distribution of monthly Taand the difference between the surface and air temperature(Td) are as follows. According to the analysis of the 0℃ and 10℃ isothermals,Tavalues over the NTP at elevations of 4000–5000 m were greater than 10℃ in the summer(from May to October),and Tavalues at an elevation of3200 m dropped below 0℃ in the winter(from November to April). Taexhibited an increasing trend from northwest to southeast. Except in the southeastern area of the NTP,T d values in other areas were all larger than 0℃ in the winter.展开更多
In this paper,based on the feature of high resolution one-dimensional range profile,two effective motion compensation methods are presented. Firstly,the processing method of stepped-frequency and the response of targe...In this paper,based on the feature of high resolution one-dimensional range profile,two effective motion compensation methods are presented. Firstly,the processing method of stepped-frequency and the response of target moving to range profile are analyzed. Secondly,the function of range profile entropy and range profile contrast are presented for velocity compensation,and then the theory analysis,math model,and solution method are analyzed in detail. Finally,several simulation experiments are designed to prove the accuracy and effectiveness of these two methods. From the final theory analysis and simulation experiments,the conclusion can be drawn that these two methods are effective,which can get much higher velocity estimation accuracy,well real-time and easy to be used in project application. After motion compens-ation,the high resolution one-dimensional range profile will be much better than that used to be,and is used for the detection, recognition and ranging of moving targets.展开更多
文摘Digitization of education is an important component of Digital China Strategy. China is deeply implementing the digitalization of education strategy, promoting educational reform and innovation, and accelerating the construction of a learning society and a learning country where everyone can learn, learn everywhere, and learn at all times [1]. As the cradle and gathering place of talent cultivation, universities should be at the forefront of educational informatization construction. As a comprehensive energy university in the northeastern region of Sichuan, the Nanchong Campus of Southwest Petroleum University plays an irreplaceable role in the local economic development. This article summarizes the current situation of educational informatization construction on this campus and proposes suggestions for its improvement path, providing constructive reference opinions for the development of similar universities.
基金supported by the National Natural Science Foundation of China(61771154)the Fundamental Research Funds for the Central Universities(3072022CF0601)supported by Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology,Harbin Engineering University,Harbin,China.
文摘As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.
基金supported by National Natural Science Foundation of China(62101088,61801076,61971336)Natural Science Foundation of Liaoning Province(2022-MS-157,2023-MS-108)+1 种基金Key Laboratory of Big Data Intelligent Computing Funds for Chongqing University of Posts and Telecommunications(BDIC-2023-A-003)Fundamental Research Funds for the Central Universities(3132022230).
文摘Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.
基金the financial supports from the National Natural Science Foundation of China (No. 52104109)the National Key Research and Development Program of China (No. 2020YFC1909801)。
基金Sponsored by the Nation Nature Science Foundation of China(Grant No.61201237)the Nature Science Foundation of Heilongjiang Province of China(Grant No.QC2012C069)the Fundamental Research Funds for the Central Universities(Grant No.HEUCFZ1129,HEUCF130810,HEUCF130817)
文摘The current parameter estimation algorithms of chirp rate have high complexity and long calculation time,meantime they are difficult to achieve high estimation rate. Therefore,in order to overcome these problems,in this paper,a new parameter estimation algorithm based on Holder coefficient is presented. Firstly,this algorithm calculates the correlation curve of the Holder coefficient value under different chirp rate. Secondly,this algorithm calculates the correlation curve under different SNR. Finally,the fitting curve expression can be got by the correlation curve,and then the estimation value of chirp rate can also be got. The theory analysis and simulation results show that this algorithm is simple and easy to realize,and has much better application value for real-time estimation.
基金Key Laboratory of Energy Conversion and Storage Technologies(Southern University of Science and Technology),Ministry of Education,Shenzhen,China,the National Key Research and Development Program of China(Grant No.2018YFB0406702)Professorship Startup Funding(Grant No.217056)+1 种基金Innovation-Driven Project of Central South University(Grant No.2018CX001)Project of State Key Laboratory of High Performance Complex Manufacturing,Central South University(Grant No.ZZYJKT2018-01).
文摘The optical response of metal nanoparticles can be modified through near-field or far-field interaction,yet the lattice plasmon modes(LPMs)considered can only be excited from the latter.Here instead,we present a theoretical evaluation for LPM excitation via the near-field coupling process.The sample is an arrayed structure with specific units composed of upper metal disks,a lower metal hole and a sandwiched dielectric post.The excitation process and underlying mechanism of the LPM and the influence of the structure parameters on the optical properties have been investigated in detail by using a finite-difference time-domain(FDTD)numerical method.Our investigation presented here should advance the understanding of near-field interaction of plasmon modes for LPM excitation,and LPMs could find some potential applications,such as in near-field optical microscopes,biosensors,optical filters and plasmonic lasers.
基金This work is supported by the National Natural Science Foundation of China(Nos.61771154,61603239,61772454,6171101570).
文摘Deep Learning(DL)is such a powerful tool that we have seen tremendous success in areas such as Computer Vision,Speech Recognition,and Natural Language Processing.Since Automated Modulation Classification(AMC)is an important part in Cognitive Radio Networks,we try to explore its potential in solving signal modulation recognition problem.It cannot be overlooked that DL model is a complex model,thus making them prone to over-fitting.DL model requires many training data to combat with over-fitting,but adding high quality labels to training data manually is not always cheap and accessible,especially in real-time system,which may counter unprecedented data in dataset.Semi-supervised Learning is a way to exploit unlabeled data effectively to reduce over-fitting in DL.In this paper,we extend Generative Adversarial Networks(GANs)to the semi-supervised learning will show it is a method can be used to create a more dataefficient classifier.
文摘AIM To evaluate the usefulness of different parameters to differentiate Crohn's disease(CD) from primary intestinal lymphoma(PIL).METHODS The medical records of 85 patients with CD and 56 patients with PIL were reviewed retrospectively. Demographic, clinical, laboratory, endoscopic, and computed tomographic enterography(CTE) parameters were collected. The univariate value of each parameter was analyzed. A differentiation model was established by pooling all the valuable parameters. Diagnostic efficacy was analyzed, and a receiver operating characteristic(ROC) curve was plotted.RESULTS The demographic and clinical parameters that showed significant values for differentiating CD from PIL included age of onset, symptom duration, presence of diarrhea, abdominal mass, and perianal lesions(P < 0.05). Elevated lactate dehydrogenase and serum β2-microglobulin levels suggested a PIL diagnosis(P < 0.05). The endoscopic parameters that showed significant values for differentiating CD from PIL included multiple-site lesions, longitudinal ulcer, irregular ulcer,and intraluminal proliferative mass(P < 0.05). The CTE parameters that were useful in the identification of the two conditions included involvement of ≤ 3 segments, circular thickening of the bowel wall, wall thickness > 8 mm, aneurysmal dilation, stricture with proximal dilation, "comb sign", mass showing the "sandwich sign", and intussusceptions(P < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the differentiation model were 91.8%, 96.4%, 93.6%, 97.5%, and 88.5%, respectively. The cutoff value was 0.5. The area under the ROC curve was 0.989.CONCLUSION The differentiation model that integrated the various parameters together may yield a high diagnostic efficacy in the differential diagnosis between CD and PIL.
基金supported by grants from the National Natural Science Foundation of China(8120223181273116+2 种基金81430079)the Science and Technology Program of Guangdong Bureau of Science and TechnologyChina(2013B021800069)
文摘The molecular mechanism of DNA damage induced by hydroquinone （HQ） remains unclear. Poly（ADP-ribose） polymerase-1 （PARP-1） usually works as a DNA damage sensor, and hence, it is possible that PARP-1 is involved in the DNA damage response induced by HQ. In TK6 cells treated with HQ, PARP activity as well as the expression of apoptosis antagonizing transcription factor （AATF）, PARP-1, and phosphorylated H2AX （v-H2AX） were maximum at 0.5 h, 6 h, 3 h, and 3 h, respectively. To explore the detailed mechanisms underlying the prompt DNA repair reaction, the above indicators were investigated in PARP-l-silenced cells. PARP activity and expression of AATF and PARP-1 decreased to 36%, 32%, and 33%, respectively, in the cells; however, y-H2AX expression increased to 265%. Co-immunoprecipitation （co-IP） assays were employed to determine whether PARP-1 and AATF formed protein complexes. The interaction between these proteins together with the results from IP assays and confocal microscopy indicated that poly（ADP-ribosyl）ation {PARylation） regulated AATF expression, in conclusion, PARP-1 was involved in the DNA damage repair induced by HQ via increasing the accumulation of AATF through PARylation.
基金Sponsored by the Nation Nature Science Foundation of China(Grant No.61201237,61301095)the Nature Science Foundation of Heilongjiang Province of China(Grant No.QC2012C069)the Fundamental Research Funds for the Central Universities(Grant No.HEUCFZ1129,HEUCF130817,HEUCF130810)
文摘In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.
基金This research is funded by the National Natural Science Foundation of China(61771154).
文摘The conventional sparse representation-based image classification usually codes the samples independently,which will ignore the correlation information existed in the data.Hence,if we can explore the correlation information hidden in the data,the classification result will be improved significantly.To this end,in this paper,a novel weighted supervised spare coding method is proposed to address the image classification problem.The proposed method firstly explores the structural information sufficiently hidden in the data based on the low rank representation.And then,it introduced the extracted structural information to a novel weighted sparse representation model to code the samples in a supervised way.Experimental results show that the proposed method is superiority to many conventional image classification methods.
基金Sponsored by the Nation Nature Science Foundation of China(Grant No.61201237)the Nature Sciece Foundation of Heilongjiang Province of China(Grant No.QC2012C069)the Fundamental Research Funds for the Central Universities(Grant No.HEUCFZ1129,HEUCF130810,HEUCF130817)
文摘Traditional Sobel algorithm is deeply influenced by Gaussian noise,therefore,before boundary extraction,mean filter should be done. But the filtering process is always over-smooth images'details of certain directions,so that images'edges will not be extracted correctly. Aiming at this problem,this paper puts forward a detection algorithm based on edge-preserving characteristics,by matching edge mould of different directions to definite edge preserving directions. Instead of the mean filter process,this algorithm improves the performance of traditional algorithms,and provides the simulation results. The experiment results prove that this algorithm preserves more images'edge information when canceling noise.
基金funded by the Chinese Academy of Science“Hundred Talents”program (Dr.Weiqiang MA)the National Natural Science Foundation of China (Grant Nos.41375009,91337212,41275010 and 41522501 and 41661144043)+3 种基金Study on long term changes of surface heat source in northern Tibetan Plateau and its thermal effect on the plateau monsoon system (Dr.Zeyong HUGrant No.91537101)the China Meteorological Administration Special Fund for Scientific Research in the Public Interest (Grant No.GYHY201406001)the EU-FP7 project “CORECLIMAX” (Grant No.313085)
文摘Time series of MODIS land surface temperature(Ts) and normalized difference vegetation index(NDVI) products,combined with digital elevation model(DEM) and meteorological data from 2001 to 2012,were used to map the spatial distribution of monthly mean air temperature over the Northern Tibetan Plateau(NTP). A time series analysis and a regression analysis of monthly mean land surface temperature(Ts) and air temperature(Ta) were conducted using ordinary linear regression(OLR) and geographical weighted regression(GWR). The analyses showed that GWR,which considers MODIS Ts,NDVI and elevation as independent variables,yielded much better results [RAdj2> 0.79; root-mean-square error(RMSE) =0.51℃–1.12℃] associated with estimating Tacompared to those from OLR(RAdj2= 0.40-0.78; RMSE = 1.60℃–4.38℃).In addition,some characteristics of the spatial distribution of monthly Taand the difference between the surface and air temperature(Td) are as follows. According to the analysis of the 0℃ and 10℃ isothermals,Tavalues over the NTP at elevations of 4000–5000 m were greater than 10℃ in the summer(from May to October),and Tavalues at an elevation of3200 m dropped below 0℃ in the winter(from November to April). Taexhibited an increasing trend from northwest to southeast. Except in the southeastern area of the NTP,T d values in other areas were all larger than 0℃ in the winter.
基金Sponsored by the National Nature Science Foundation of China(Grant No.61201237)the Nature Science Foundation of Heilongjiang Province of China(Grant No.QC2012C069)the Fundamental Research Funds for the Central Universities(Grant No.HEUCFZ1129,HEUCF130810,HEUCF130817)
文摘In this paper,based on the feature of high resolution one-dimensional range profile,two effective motion compensation methods are presented. Firstly,the processing method of stepped-frequency and the response of target moving to range profile are analyzed. Secondly,the function of range profile entropy and range profile contrast are presented for velocity compensation,and then the theory analysis,math model,and solution method are analyzed in detail. Finally,several simulation experiments are designed to prove the accuracy and effectiveness of these two methods. From the final theory analysis and simulation experiments,the conclusion can be drawn that these two methods are effective,which can get much higher velocity estimation accuracy,well real-time and easy to be used in project application. After motion compens-ation,the high resolution one-dimensional range profile will be much better than that used to be,and is used for the detection, recognition and ranging of moving targets.
