The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
Drug resistance remains a major challenge in breast cancer chemotherapy,yet the metabolic alterations underlying this phenomenon are not fully understood.There is much evidence indicating the cellular heterogeneity am...Drug resistance remains a major challenge in breast cancer chemotherapy,yet the metabolic alterations underlying this phenomenon are not fully understood.There is much evidence indicating the cellular heterogeneity among cancer cells,which exhibit varying degrees of metabolic reprogramming and thus may result in differential contributions to drug resistance.A home-built single-cell quantitative mass spectrometry(MS)platform,which integrates micromanipulation and electro-osmotic sampling,was developed to quantitatively profile the tricarboxylic acid(TCA)cycle metabolites at the single-cell level.Using this platform,the metabolic profiles of drug-sensitive MCF-7 breast cancer cells and their drug-resistant derivative MCF-7/ADR cells were compared.This results revealed a selective upregulation of downstream TCA cycle metabolites includingα-ketoglutarate,succinate,fumarate,and malate in drug-resistant cancer cells,while early TCA metabolites remained largely unchanged.Furthermore,notable variations in the abundance of the metabolites were observed in individual cells.The comparative analysis also revealed that not all MCF-7/ADR cells exhibit the same degree of metabolic deviation from the parental line in the metabolites during resistance acquisition.The observed metabolic profiles indicate enhanced glutaminolysis,altered mitochondrial electron transport chain activity,and increased metabolic flexibility in drug-resistant cancer cells that support their survival under chemotherapeutic stress.The findings further suggest the potential for incorporating cellular metabolic heterogeneity into future drug resistance studies.展开更多
In this paper,a feature selection method for determining input parameters in antenna modeling is proposed.In antenna modeling,the input feature of artificial neural network(ANN)is geometric parameters.The selection cr...In this paper,a feature selection method for determining input parameters in antenna modeling is proposed.In antenna modeling,the input feature of artificial neural network(ANN)is geometric parameters.The selection criteria contain correlation and sensitivity between the geometric parameter and the electromagnetic(EM)response.Maximal information coefficient(MIC),an exploratory data mining tool,is introduced to evaluate both linear and nonlinear correlations.The EM response range is utilized to evaluate the sensitivity.The wide response range corresponding to varying values of a parameter implies the parameter is highly sensitive and the narrow response range suggests the parameter is insensitive.Only the parameter which is highly correlative and sensitive is selected as the input of ANN,and the sampling space of the model is highly reduced.The modeling of a wideband and circularly polarized antenna is studied as an example to verify the effectiveness of the proposed method.The number of input parameters decreases from8 to 4.The testing errors of|S_(11)|and axis ratio are reduced by8.74%and 8.95%,respectively,compared with the ANN with no feature selection.展开更多
[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-base...[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.展开更多
Based on schematically formulation of the vibrations induced by moving trains, this paper analyses the waveforms along the Datong-Qinhuangdao railroad in Northern China recorded in the suburban Huairou district of Bei...Based on schematically formulation of the vibrations induced by moving trains, this paper analyses the waveforms along the Datong-Qinhuangdao railroad in Northern China recorded in the suburban Huairou district of Beijing on March 8, 2003. It is illustrated that vibrations induced by train, except traditional recognized noises and interfer- ence effects, could be used as a seismic source to detect crustal structures with its advantage of abundant frequency spectrum, repeatability and no additional harm to the environment. It will bring lights to the traditional exploration seismology with the further studies of signal processing and interpretation methods, and related models and new observing systems.展开更多
English speech is a discourse delivered at an assembly or on formal occasions. As a variety of the English language, English speech has a unique presentation of its own. This paper, as its title indicates, is to analy...English speech is a discourse delivered at an assembly or on formal occasions. As a variety of the English language, English speech has a unique presentation of its own. This paper, as its title indicates, is to analyze and probe the linguistic and rhetorical features of famous English speeches with a view to improving the ability to appreciate English speeches on the part of Chinese learners of English.展开更多
The mechanical properties and deformation features of AZ31-0.84% Sb alloy have been studied by means of the measurement of the properties and morphology observation. Results show that UTS of AZ31-0.84% Sb alloy at roo...The mechanical properties and deformation features of AZ31-0.84% Sb alloy have been studied by means of the measurement of the properties and morphology observation. Results show that UTS of AZ31-0.84% Sb alloy at room temperature is 297MPa, a higher value of UTS is still maintained up to 189MPa as temperature elevated to 200℃. One of the main reasons for enhancing UTS of the alloy is attributed to the high volume fraction of the precipitates dispersed in the matrix, including Mg3Sb2 phase, which effectively hindered the movement of dislocations during the elevated temperature deformation. The deformation mechanisms of AZ31-0.84% Sb alloy are the twins and dislocations activated on basal and non-basal planes. a+c dislocations may be activated on the basal and non-basal planes in twins regions, and some of the thinner twins may shear through the dense dislocations within the thicker twins.展开更多
A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected...A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected as the features. The four features are combined together as a parameter to detect the edges of color images. Experimental results show that the method can inhibit noisy edges and facilitate the detection for weak edges. It has a better performance than conventional methods in noisy environments.展开更多
Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit feature...Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency. A fault diagnosis illustration validated this method.展开更多
While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection ...While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network(TDBU-FPN),which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes(PASCAL VOC)dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps.展开更多
This paper is going to focus on the lexis characteristics of the advertisement English in stylistics. The lexis characteristics of advertisement include using the new form of the spelling of a word to attract the cons...This paper is going to focus on the lexis characteristics of the advertisement English in stylistics. The lexis characteristics of advertisement include using the new form of the spelling of a word to attract the consumers’ attention; using the borrowed words to enhance the transmission effect of the advertisements; Frequent use of some verbs, adjectives to express the information and enhance the effect of language expression; Using the compounds in flexibility. Meanwhile, we could find out that some specific terms are used and the word used in advertisements show the gender.展开更多
A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated ...A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated from the local motions of selected feature points. Considering the local moving objects or the inevitable mismatch, the matching validation, based on the stable relative distance between the points set is proposed, thus maintaining high accuracy and robustness. Next, the global motion parameters are accumulated for correction by Kalman filteration. The experimental result illustrates that the proposed system is effective to stabilize translational, rotational, and zooming jitter and robust to local motions.展开更多
Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchang...Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format （EXIF） information of image for images authen- tication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.展开更多
Amugang Group is distributed mainly over Amugang, Jiangai Mountain, Mayigangri,Gemuri and Qiagela,etc. lt includes Gemuri Formation and Qiagela Formation. They had even been thought of the crystalline basement of Qian...Amugang Group is distributed mainly over Amugang, Jiangai Mountain, Mayigangri,Gemuri and Qiagela,etc. lt includes Gemuri Formation and Qiagela Formation. They had even been thought of the crystalline basement of Qiangtang terrain. However, Gemuri Formation and Qiagela Formation are not alike in the protolithes, metamorphism and deformation, rock association,etc.In fact, they are different in mechanism.Gemuri Formation is composed of high\|Pressure, low\|temperature glaucophane greenschist\|faci metamorphic rocks. The petrolithes of the blueschists are glaciomarine conglomerates and basalts from the Southern Qiagtang area. The typical mineralogy include: glaucophane+ epidote + calcite +stilpnomelane and stilpnomelane+chlorite+sericite+ quartz+ glaucophane. P.T conditions for the metamorphism of blueschist are estimated to be 0 6～0 7GPa and 320～400℃.The 40 Ar/ 39 Ar dating of the crossite has yielded good plateau age of (222 5±3 7)Ma,which represents the formation of Gemuri Formation.Qiagela Formation comprises schist series, marbles, Gneisses and plagioamphiboles. The protolithes of them are a suit of argillaceous sandstones, arkoses, carbonates and mafic volcanic rocks. The Sm\|Nd isochron age of the metamorphic mafic volcanic rocks is (268 0±5 6)Ma, which shows that The age of the protolithes is early Dias. The typical mineralogy include: Muscovite+biotite+plagioclase+quartz; garnet+kyanite+ staurolite+ biotite+ muscovite+plagioclase+quartz; amphibole+ plagioclase±garnet+ quartz. They are meos\|pressure,meso\|temperature low amphibole\|faci metamorphic rocks. Qiagela Formation is coexistent with the late Triassic and the early Jurassic volcano\|magmatic arc in space and overlapped by the triassic limestones of Xiaocaka Formation. So,it is suggested that the formation of Qiagela Formation be between the late Dias and the late Triassic period. Its genesis is relative to the thermal current provided by magmatic activity.展开更多
Feature extraction of range images provided by ranging sensor is a key issue of pattern recognition. To automatically extract the environmental feature sensed by a 2D ranging sensor laser scanner, an improved method b...Feature extraction of range images provided by ranging sensor is a key issue of pattern recognition. To automatically extract the environmental feature sensed by a 2D ranging sensor laser scanner, an improved method based on genetic clustering VGA-clustering is presented. By integrating the spatial neighbouring information of range data into fuzzy clustering algorithm, a weighted fuzzy clustering algorithm （WFCA） instead of standard clustering algorithm is introduced to realize feature extraction of laser scanner. Aimed at the unknown clustering number in advance, several validation index functions are used to estimate the validity of different clustering algorithms and one validation index is selected as the fitness function of genetic algorithm so as to determine the accurate clustering number automatically. At the same time, an improved genetic algorithm IVGA on the basis of VGA is proposed to solve the local optimum of clustering algorithm, which is implemented by increasing the population diversity and improving the genetic operators of elitist rule to enhance the local search capacity and to quicken the convergence speed. By the comparison with other algorithms, the effectiveness of the algorithm introduced is demonstrated.展开更多
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金supported by National Natural Science Foundation of China(22374080,22174068,21722504)Primary Research&Development Plan of Jiangsu Province(BK20221303,BE2022796)+1 种基金Open Foundation of State Key Laboratory of Reproductive Medicine(SKLRM-2022BP1,JX116GSP20240507)Science and Technology Development Fund of NJMU(NJMUQY2022003)。
文摘Drug resistance remains a major challenge in breast cancer chemotherapy,yet the metabolic alterations underlying this phenomenon are not fully understood.There is much evidence indicating the cellular heterogeneity among cancer cells,which exhibit varying degrees of metabolic reprogramming and thus may result in differential contributions to drug resistance.A home-built single-cell quantitative mass spectrometry(MS)platform,which integrates micromanipulation and electro-osmotic sampling,was developed to quantitatively profile the tricarboxylic acid(TCA)cycle metabolites at the single-cell level.Using this platform,the metabolic profiles of drug-sensitive MCF-7 breast cancer cells and their drug-resistant derivative MCF-7/ADR cells were compared.This results revealed a selective upregulation of downstream TCA cycle metabolites includingα-ketoglutarate,succinate,fumarate,and malate in drug-resistant cancer cells,while early TCA metabolites remained largely unchanged.Furthermore,notable variations in the abundance of the metabolites were observed in individual cells.The comparative analysis also revealed that not all MCF-7/ADR cells exhibit the same degree of metabolic deviation from the parental line in the metabolites during resistance acquisition.The observed metabolic profiles indicate enhanced glutaminolysis,altered mitochondrial electron transport chain activity,and increased metabolic flexibility in drug-resistant cancer cells that support their survival under chemotherapeutic stress.The findings further suggest the potential for incorporating cellular metabolic heterogeneity into future drug resistance studies.
基金National Natural Science Foundation of China(62161048)Sichuan Science and Technology Program(2022NSFSC0547,2022ZYD0109)。
文摘In this paper,a feature selection method for determining input parameters in antenna modeling is proposed.In antenna modeling,the input feature of artificial neural network(ANN)is geometric parameters.The selection criteria contain correlation and sensitivity between the geometric parameter and the electromagnetic(EM)response.Maximal information coefficient(MIC),an exploratory data mining tool,is introduced to evaluate both linear and nonlinear correlations.The EM response range is utilized to evaluate the sensitivity.The wide response range corresponding to varying values of a parameter implies the parameter is highly sensitive and the narrow response range suggests the parameter is insensitive.Only the parameter which is highly correlative and sensitive is selected as the input of ANN,and the sampling space of the model is highly reduced.The modeling of a wideband and circularly polarized antenna is studied as an example to verify the effectiveness of the proposed method.The number of input parameters decreases from8 to 4.The testing errors of|S_(11)|and axis ratio are reduced by8.74%and 8.95%,respectively,compared with the ANN with no feature selection.
文摘[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.
基金National Natural Science Foundations of China (No. 40234038 and 40174014).
文摘Based on schematically formulation of the vibrations induced by moving trains, this paper analyses the waveforms along the Datong-Qinhuangdao railroad in Northern China recorded in the suburban Huairou district of Beijing on March 8, 2003. It is illustrated that vibrations induced by train, except traditional recognized noises and interfer- ence effects, could be used as a seismic source to detect crustal structures with its advantage of abundant frequency spectrum, repeatability and no additional harm to the environment. It will bring lights to the traditional exploration seismology with the further studies of signal processing and interpretation methods, and related models and new observing systems.
文摘English speech is a discourse delivered at an assembly or on formal occasions. As a variety of the English language, English speech has a unique presentation of its own. This paper, as its title indicates, is to analyze and probe the linguistic and rhetorical features of famous English speeches with a view to improving the ability to appreciate English speeches on the part of Chinese learners of English.
文摘The mechanical properties and deformation features of AZ31-0.84% Sb alloy have been studied by means of the measurement of the properties and morphology observation. Results show that UTS of AZ31-0.84% Sb alloy at room temperature is 297MPa, a higher value of UTS is still maintained up to 189MPa as temperature elevated to 200℃. One of the main reasons for enhancing UTS of the alloy is attributed to the high volume fraction of the precipitates dispersed in the matrix, including Mg3Sb2 phase, which effectively hindered the movement of dislocations during the elevated temperature deformation. The deformation mechanisms of AZ31-0.84% Sb alloy are the twins and dislocations activated on basal and non-basal planes. a+c dislocations may be activated on the basal and non-basal planes in twins regions, and some of the thinner twins may shear through the dense dislocations within the thicker twins.
基金supported partly by the National Basic Research Program of China (2005CB724303)the National Natural Science Foundation of China (60671062) Shanghai Leading Academic Discipline Project (B112).
文摘A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected as the features. The four features are combined together as a parameter to detect the edges of color images. Experimental results show that the method can inhibit noisy edges and facilitate the detection for weak edges. It has a better performance than conventional methods in noisy environments.
基金the National Natural Science Fundation of China (60372001 90407007)the Ph. D. Programs Foundation of Ministry of Education of China (20030614006).
文摘Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency. A fault diagnosis illustration validated this method.
基金supported by the Program of Introducing Talents of Discipline to Universities(111 Plan)of China(B14010)the National Natural Science Foundation of China(31727901)
文摘While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network(TDBU-FPN),which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes(PASCAL VOC)dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps.
文摘This paper is going to focus on the lexis characteristics of the advertisement English in stylistics. The lexis characteristics of advertisement include using the new form of the spelling of a word to attract the consumers’ attention; using the borrowed words to enhance the transmission effect of the advertisements; Frequent use of some verbs, adjectives to express the information and enhance the effect of language expression; Using the compounds in flexibility. Meanwhile, we could find out that some specific terms are used and the word used in advertisements show the gender.
基金the National Natural Science Foundation (60572152) of China and Science Foundation ofShaanxi Province (2005F26)
文摘A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated from the local motions of selected feature points. Considering the local moving objects or the inevitable mismatch, the matching validation, based on the stable relative distance between the points set is proposed, thus maintaining high accuracy and robustness. Next, the global motion parameters are accumulated for correction by Kalman filteration. The experimental result illustrates that the proposed system is effective to stabilize translational, rotational, and zooming jitter and robust to local motions.
基金supported by the National Natural Science Foundation of China under Grant Nos.61370195and 11101048Beijing Natural Science Foundation under Grant No.4132060the National Cryptography Development Foundation of China under Grant No.MMJJ201201002
文摘Recently, the digital image blind forensics technology has received an increasing attention in academic community. This paper aims at developing a new identification approach based on the statistical noise and exchangeable image file format （EXIF） information of image for images authen- tication. In particular, the authors can identify whether the current image has been modified or not by utilizing the relevance between noise and EXIF parameters and comparing the real values with the estimated values of the EXIF parameters. Experimental results validate the proposed method. That is, the detecting system can identify the doctored image effectively.
文摘Amugang Group is distributed mainly over Amugang, Jiangai Mountain, Mayigangri,Gemuri and Qiagela,etc. lt includes Gemuri Formation and Qiagela Formation. They had even been thought of the crystalline basement of Qiangtang terrain. However, Gemuri Formation and Qiagela Formation are not alike in the protolithes, metamorphism and deformation, rock association,etc.In fact, they are different in mechanism.Gemuri Formation is composed of high\|Pressure, low\|temperature glaucophane greenschist\|faci metamorphic rocks. The petrolithes of the blueschists are glaciomarine conglomerates and basalts from the Southern Qiagtang area. The typical mineralogy include: glaucophane+ epidote + calcite +stilpnomelane and stilpnomelane+chlorite+sericite+ quartz+ glaucophane. P.T conditions for the metamorphism of blueschist are estimated to be 0 6～0 7GPa and 320～400℃.The 40 Ar/ 39 Ar dating of the crossite has yielded good plateau age of (222 5±3 7)Ma,which represents the formation of Gemuri Formation.Qiagela Formation comprises schist series, marbles, Gneisses and plagioamphiboles. The protolithes of them are a suit of argillaceous sandstones, arkoses, carbonates and mafic volcanic rocks. The Sm\|Nd isochron age of the metamorphic mafic volcanic rocks is (268 0±5 6)Ma, which shows that The age of the protolithes is early Dias. The typical mineralogy include: Muscovite+biotite+plagioclase+quartz; garnet+kyanite+ staurolite+ biotite+ muscovite+plagioclase+quartz; amphibole+ plagioclase±garnet+ quartz. They are meos\|pressure,meso\|temperature low amphibole\|faci metamorphic rocks. Qiagela Formation is coexistent with the late Triassic and the early Jurassic volcano\|magmatic arc in space and overlapped by the triassic limestones of Xiaocaka Formation. So,it is suggested that the formation of Qiagela Formation be between the late Dias and the late Triassic period. Its genesis is relative to the thermal current provided by magmatic activity.
基金the National Natural Science Foundation of China (60234030)the Natural Science Foundationof He’nan Educational Committee of China (2007520019, 2008B520015)Doctoral Foundation of Henan Polytechnic Universityof China (B050901, B2008-61)
文摘Feature extraction of range images provided by ranging sensor is a key issue of pattern recognition. To automatically extract the environmental feature sensed by a 2D ranging sensor laser scanner, an improved method based on genetic clustering VGA-clustering is presented. By integrating the spatial neighbouring information of range data into fuzzy clustering algorithm, a weighted fuzzy clustering algorithm （WFCA） instead of standard clustering algorithm is introduced to realize feature extraction of laser scanner. Aimed at the unknown clustering number in advance, several validation index functions are used to estimate the validity of different clustering algorithms and one validation index is selected as the fitness function of genetic algorithm so as to determine the accurate clustering number automatically. At the same time, an improved genetic algorithm IVGA on the basis of VGA is proposed to solve the local optimum of clustering algorithm, which is implemented by increasing the population diversity and improving the genetic operators of elitist rule to enhance the local search capacity and to quicken the convergence speed. By the comparison with other algorithms, the effectiveness of the algorithm introduced is demonstrated.
