Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retr...Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.展开更多
Two lines of image representation based on multiple features fusion demonstrate excellent performance in image retrieval.However,there are some problems in both of them:1)the methods defining directly texture in color...Two lines of image representation based on multiple features fusion demonstrate excellent performance in image retrieval.However,there are some problems in both of them:1)the methods defining directly texture in color space put more emphasis on color than texture feature;2)the methods extract several features respectively and combine them into a vector,in which bad features may lead to worse performance after combining directly good and bad features.To address the problems above,a novel hybrid framework for color image retrieval through combination of local and global features achieves higher retrieval precision.The bag-of-visual words(BoW)models and color intensity-based local difference patterns(CILDP)are exploited to capture local and global features of an image.The proposed fusion framework combines the ranking results of BoW and CILDP through graph-based density method.The performance of our proposed framework in terms of average precision on Corel-1K database is86.26%,and it improves the average precision by approximately6.68%and12.53%over CILDP and BoW,respectively.Extensive experiments on different databases demonstrate the effectiveness of the proposed framework for image retrieval.展开更多
A retrieval control strategy for failed satellite,which is connected to a servicing spacecraft by a tether,is studied.The Lagrange analytical mechanics based dynamics modeling for the system composed of a servicing sp...A retrieval control strategy for failed satellite,which is connected to a servicing spacecraft by a tether,is studied.The Lagrange analytical mechanics based dynamics modeling for the system composed of a servicing spacecraft,a tether and a failed satellite,is presented under the earth center inertia coordinate system,then model simplification is conducted under the assumption that the failed satellite’s mass is far smaller than the servicing spacecraft’s,meanwhile the tether’s length is far smaller than the size of the servicing spacecraft’s orbit.Analysis shows that the retrieval process is intrinsically unstable as the Coriolis force functions is a negative damping.A retrieval strategy based on only the tether’s tension is designed,resulting in the fastest retrieval speed.In the proposed strategy,firstly,the tether’s swing angle amplitude is adjusted to 45?by deploying/retrieving the tether;then the tether swings freely with fixed length until it reaches negative maximum angle–45?;finally,the tether is retrieved by the pre-assigned exponential law.For simplicity,only the coplanar situation,that the tether swings in the plane of the servicing spacecraft’s orbit,is studied.Numerical simulation verifies the effectiveness of the strategy proposed.展开更多
A novel image retrieval approach based on color features and anisotropic directional information is proposed for content based image retrieval systems （CBIR）. The color feature is described by the color histogram ...A novel image retrieval approach based on color features and anisotropic directional information is proposed for content based image retrieval systems （CBIR）. The color feature is described by the color histogram （CH）, which is translation and rotation invariant. However, the CH does not contain spatial information which is very important for the image retrieval. To overcome this shortcoming, the subband energy of the lifting directionlet transform （L-DT） is proposed to describe the directional information, in which L-DT is characterized by multi-direction and anisotropic basis functions compared with the wavelet transform. A global similarity measure is designed to implement the fusion of both color feature and anisotropic directionality for the retrieval process. The retrieval experiments using a set of COREL images demonstrate that the higher query precision and better visual effect can be achieved.展开更多
A simple fast method is given for sequentially retrieving all the records in a B tree. A file structure for database is proposed. The records in its primary data file are sorted according to the key order. A B tree ...A simple fast method is given for sequentially retrieving all the records in a B tree. A file structure for database is proposed. The records in its primary data file are sorted according to the key order. A B tree is used as its dense index. It is easy to insert, delete or search a record, and it is also convenient to retrieve records in the sequential order of the keys. The merits and efficiencies of these methods or structures are discussed in detail.展开更多
To realize content-hased retrieval of large image databases, it is required to develop an efficient index and retrieval scheme. This paper proposes an index algorithm of clustering called CMA, which supports fast retr...To realize content-hased retrieval of large image databases, it is required to develop an efficient index and retrieval scheme. This paper proposes an index algorithm of clustering called CMA, which supports fast retrieval of large image databases. CMA takes advantages of k-means and self-adaptive algorithms. It is simple and works without any user interactions. There are two main stages in this algorithm. In the first stage, it classifies images in a database into several clusters, and automatically gets the necessary parameters for the next stage-k-means iteration. The CMA algorithm is tested on a large database of more than ten thousand images and compare it with k-means algorithm. Experimental results show that this algorithm is effective in both precision and retrieval time.展开更多
A novel content based image retrieval （CBIR） algorithmusing relevant feedback is presented. The proposed frameworkhas three major contributions： a novel feature descriptor calledcolor spectral histogram （CSH） to ...A novel content based image retrieval （CBIR） algorithmusing relevant feedback is presented. The proposed frameworkhas three major contributions： a novel feature descriptor calledcolor spectral histogram （CSH） to measure the similarity betweenimages; two-dimensional matrix based indexing approach proposedfor short-term learning （STL）; and long-term learning （LTL）.In general, image similarities are measured from feature representationwhich includes color quantization, texture, color, shapeand edges. However, CSH can describe the image feature onlywith the histogram. Typically the image retrieval process starts byfinding the similarity between the query image and the imagesin the database; the major computation involved here is that theselection of top ranking images requires a sorting algorithm to beemployed at least with the lower bound of O（n log n）. A 2D matrixbased indexing of images can enormously reduce the searchtime in STL. The same structure is used for LTL with an aim toreduce the amount of log to be maintained. The performance ofthe proposed framework is analyzed and compared with the existingapproaches, the quantified results indicates that the proposedfeature descriptor is more effectual than the existing feature descriptorsthat were originally developed for CBIR. In terms of STL,the proposed 2D matrix based indexing minimizes the computationeffort for retrieving similar images and for LTL, the proposed algorithmtakes minimum log information than the existing approaches.展开更多
This paper presents a novel efficient semantic image classification algorithm for high-level feature indexing of high-dimension image database. Experiments show that the algorithm performs well. The size of the train ...This paper presents a novel efficient semantic image classification algorithm for high-level feature indexing of high-dimension image database. Experiments show that the algorithm performs well. The size of the train set and the test set is 7 537 and 5 000 respectively. Based on this theory, another ground is built with 12,000 images, which are divided into three classes: city, landscape and person, the total result of the classifications is 88.92%, meanwhile, some preliminary results are presented for image understanding based on semantic image classification and low level features. The groundtruth for the experiments is built with the images from Corel database, photos and some famous face databases.展开更多
The problem considered in this paper is how to detect the degree of similarity in the content of digital images useful in image retrieval,i.e.,to what extent is the content of a query image similar to content of other...The problem considered in this paper is how to detect the degree of similarity in the content of digital images useful in image retrieval,i.e.,to what extent is the content of a query image similar to content of other images.The solution to this problem results from the detection of subsets that are rough sets contained in covers of digital images determined by perceptual tolerance relations(PTRs).Such relations are defined within the context of perceptual representative spaces that hearken back to work by J.H.Poincare on representative spaces as models of physical continua.Classes determined by a PTR provide content useful in content-based image retrieval(CBIR).In addition,tolerance classes provide a means of determining when subsets of image covers are tolerance rough sets(TRSs).It is the nearness of TRSs present in image tolerance spaces that provide a promising approach to CBIR,especially in cases such as satellite images or aircraft identification where there are subtle differences between pairs of digital images,making it difficult to quantify the similarities between such images.The contribution of this article is the introduction of the nearness of tolerance rough sets as an effective means of measuring digital image similarities and,as a significant consequence,successfully carrying out CBIR.展开更多
In order to extract peptides from formalin-fixed tissue and compare the peptide profile differences between control group and disease group,different antigen retrieval(AR) methods were investigated in this paper: orga...In order to extract peptides from formalin-fixed tissue and compare the peptide profile differences between control group and disease group,different antigen retrieval(AR) methods were investigated in this paper: organic solvent,trypsin and magnetic bead.MALDI-TOF MS was used for evaluating the retrieval efficiency.Results showed: trypsin retrieval method was compatible to MS analysis and the higher quality spectra could be acquired,the time of digestion did not affect the peptide profile but the concentration was crucial.We concluded the optimal conditions as follows: digestion with 0.1μg/μL of trypsin at 37℃ for 2h and using the of α-cyano-4-hydroxy cinnamic acid as the MALDI matrix.展开更多
Building a cloud geodatabase for a sponge city is crucial to integrate the geospatial information dispersed in various departments for multi-user high concurrent access and retrieval,high scalability and availability,...Building a cloud geodatabase for a sponge city is crucial to integrate the geospatial information dispersed in various departments for multi-user high concurrent access and retrieval,high scalability and availability,efficient storage and management.In this study,Hadoop distributed computing framework,including Hadoop distributed file system and MapReduce(mapper and reducer),is firstly designed with a parallel computing framework to process massive spatial data.Then,access control with a series of standard application programming interfaces for different functions is designed,including spatial data storage layer,cloud geodatabase access layer,spatial data access layer and spatial data analysis layer.Subsequently,a retrieval model is designed,including direct addressing via file name,three-level concurrent retrieval and block data retrieval strategies.Main functions are realised,including real-time concurrent access,high-performance computing,communication,massive data storage,efficient retrieval and scheduling decisions on the multi-scale,multi-source and massive spatial data.Finally,the performance of Hadoop cloud geodatabases is validated and compared with that of the Oracle database.The cloud geodatabase for the sponge city can avoid redundant configuration of personnel,hardware and software,support the data transfer,model debugging and application development,and provide accurate,real-time,virtual,intelligent,reliable,elastically scalable,dynamic and on-demand cloud services of the basic and thematic geographic information for the construction and management of the sponge city.展开更多
Several users use metasearch engines directly or indirectly to access and gather data from more than one data sources. The effectiveness of a metasearch engine is majorly determined by the quality of the results and i...Several users use metasearch engines directly or indirectly to access and gather data from more than one data sources. The effectiveness of a metasearch engine is majorly determined by the quality of the results and it returns and in response to user queries. The rank aggregation methods which have been proposed until now exploits very limited set of parameters such as total number of used resources and the rankings they achieved from each individual resource. In this work, we use the neural network to merge the score computation module effectively. Initially, we give a query to different search engines and the top n list from each search engine is chosen for further processing our technique. We then merge the top n list based on unique links and we do some parameter calculations such as title based calculation, snippet based calculation, content based calculation, domain calculation, position calculation and co-occurrence calculation. We give the solutions of the calculations with user given ranking of links to the neural network to train the system. The system then rank and merge the links we obtain from different search engines for the query we give. Experimentation results reports a retrieval effectiveness of about 80%, precision of about 79% for user queries and about 72% for benchmark queries. The proposed technique also includes a response time of about 76 ms for 50 links and 144 ms for 100 links.展开更多
This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer....This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer.A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer(SHRB).Simulation results show that SHRB has a better performance,accuracy,and applicability and more powerful eigenvalues than conventional beamformers.A simple mathematical proof is provided.By changing the number of harmonics,as a degree of freedom that is missing in conventional beamformers,SHRB can achieve more optimal outputs without increasing the number of spatial or temporal samples.We will demonstrate that SHRB offers an improvement of 4 dB in signal to noise ratio(SNR) in bit error rate(BER) of 10~(-4) over conventional beamformers.In the case of direction of arrival(DOA) estimation,SHRB can estimate the DOA of the desired signal with an SNR of-25 dB,when conventional methods cannot have acceptable response.展开更多
Dynamic analysis of the tethered satellite system(TSS)can provide a fundamental guideline to the evaluation of performance and robust design of the system examined.Uncertainties inherited with the parameters would ind...Dynamic analysis of the tethered satellite system(TSS)can provide a fundamental guideline to the evaluation of performance and robust design of the system examined.Uncertainties inherited with the parameters would induce unexpected variation of the response and deteriorate the reliability of the system.In this work,the effect of uncertain mass of the satellites on the deployment and retrieval dynamics of the TSS is investigated.First the interval mode is employed to take the variation of mass of satellite into account in the processes of deployment and retrieval.Then,the Chebyshev interval method is used to obtain the lower and upper response bounds of the TSS.To achieve a smooth and reliable implementation of deployment and retrieval,the nonlinear programming based on the Gauss pseudospectral method is adopted to obtain optimal trajectory of tether velocity.Numerical results show that the uncertainties of mass of the satellites have a distinct influence on the response of tether tension in the processes of deployment and retrieval.展开更多
Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, ...Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.展开更多
In this article, a new model of establishing flexible and utility bi-bliographic systems dependent on microcomputer or minicomputer is di-scussed and compared with the models of large systems and PC-basedsystems. A pr...In this article, a new model of establishing flexible and utility bi-bliographic systems dependent on microcomputer or minicomputer is di-scussed and compared with the models of large systems and PC-basedsystems. A practical example based on this model, Union Catalog Systemof Serials in Western Languages, is used to show our solution for thedevelopment and utilization of the systems of this kind.展开更多
基金supported by the National Natural Science Foundation of China(6157138861601398)the National Natural Science Foundation of Hebei Province(F2016203251)
文摘Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.
基金Projects(61370200,61672130,61602082) supported by the National Natural Science Foundation of ChinaProject(1721203049-1) supported by the Science and Technology Research and Development Plan Project of Handan,Hebei Province,China
文摘Two lines of image representation based on multiple features fusion demonstrate excellent performance in image retrieval.However,there are some problems in both of them:1)the methods defining directly texture in color space put more emphasis on color than texture feature;2)the methods extract several features respectively and combine them into a vector,in which bad features may lead to worse performance after combining directly good and bad features.To address the problems above,a novel hybrid framework for color image retrieval through combination of local and global features achieves higher retrieval precision.The bag-of-visual words(BoW)models and color intensity-based local difference patterns(CILDP)are exploited to capture local and global features of an image.The proposed fusion framework combines the ranking results of BoW and CILDP through graph-based density method.The performance of our proposed framework in terms of average precision on Corel-1K database is86.26%,and it improves the average precision by approximately6.68%and12.53%over CILDP and BoW,respectively.Extensive experiments on different databases demonstrate the effectiveness of the proposed framework for image retrieval.
基金supported by the Fundamental Research Funds for the Central Universities(NUAA-NS2016082)
文摘A retrieval control strategy for failed satellite,which is connected to a servicing spacecraft by a tether,is studied.The Lagrange analytical mechanics based dynamics modeling for the system composed of a servicing spacecraft,a tether and a failed satellite,is presented under the earth center inertia coordinate system,then model simplification is conducted under the assumption that the failed satellite’s mass is far smaller than the servicing spacecraft’s,meanwhile the tether’s length is far smaller than the size of the servicing spacecraft’s orbit.Analysis shows that the retrieval process is intrinsically unstable as the Coriolis force functions is a negative damping.A retrieval strategy based on only the tether’s tension is designed,resulting in the fastest retrieval speed.In the proposed strategy,firstly,the tether’s swing angle amplitude is adjusted to 45?by deploying/retrieving the tether;then the tether swings freely with fixed length until it reaches negative maximum angle–45?;finally,the tether is retrieved by the pre-assigned exponential law.For simplicity,only the coplanar situation,that the tether swings in the plane of the servicing spacecraft’s orbit,is studied.Numerical simulation verifies the effectiveness of the strategy proposed.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2007AA12Z1362007AA12Z223)+2 种基金the National Basic Research Program of China (973Program) (2006CB705707)the National Natural Science Foundation of China (60672126, 60607010)the Program for Cheung Kong Scholars and Innovative Research Team in University (IRT0645)
文摘A novel image retrieval approach based on color features and anisotropic directional information is proposed for content based image retrieval systems （CBIR）. The color feature is described by the color histogram （CH）, which is translation and rotation invariant. However, the CH does not contain spatial information which is very important for the image retrieval. To overcome this shortcoming, the subband energy of the lifting directionlet transform （L-DT） is proposed to describe the directional information, in which L-DT is characterized by multi-direction and anisotropic basis functions compared with the wavelet transform. A global similarity measure is designed to implement the fusion of both color feature and anisotropic directionality for the retrieval process. The retrieval experiments using a set of COREL images demonstrate that the higher query precision and better visual effect can be achieved.
文摘A simple fast method is given for sequentially retrieving all the records in a B tree. A file structure for database is proposed. The records in its primary data file are sorted according to the key order. A B tree is used as its dense index. It is easy to insert, delete or search a record, and it is also convenient to retrieve records in the sequential order of the keys. The merits and efficiencies of these methods or structures are discussed in detail.
基金This project was supported by National High Tech Foundation of 863 (2001AA115123)
文摘To realize content-hased retrieval of large image databases, it is required to develop an efficient index and retrieval scheme. This paper proposes an index algorithm of clustering called CMA, which supports fast retrieval of large image databases. CMA takes advantages of k-means and self-adaptive algorithms. It is simple and works without any user interactions. There are two main stages in this algorithm. In the first stage, it classifies images in a database into several clusters, and automatically gets the necessary parameters for the next stage-k-means iteration. The CMA algorithm is tested on a large database of more than ten thousand images and compare it with k-means algorithm. Experimental results show that this algorithm is effective in both precision and retrieval time.
文摘A novel content based image retrieval （CBIR） algorithmusing relevant feedback is presented. The proposed frameworkhas three major contributions： a novel feature descriptor calledcolor spectral histogram （CSH） to measure the similarity betweenimages; two-dimensional matrix based indexing approach proposedfor short-term learning （STL）; and long-term learning （LTL）.In general, image similarities are measured from feature representationwhich includes color quantization, texture, color, shapeand edges. However, CSH can describe the image feature onlywith the histogram. Typically the image retrieval process starts byfinding the similarity between the query image and the imagesin the database; the major computation involved here is that theselection of top ranking images requires a sorting algorithm to beemployed at least with the lower bound of O（n log n）. A 2D matrixbased indexing of images can enormously reduce the searchtime in STL. The same structure is used for LTL with an aim toreduce the amount of log to be maintained. The performance ofthe proposed framework is analyzed and compared with the existingapproaches, the quantified results indicates that the proposedfeature descriptor is more effectual than the existing feature descriptorsthat were originally developed for CBIR. In terms of STL,the proposed 2D matrix based indexing minimizes the computationeffort for retrieving similar images and for LTL, the proposed algorithmtakes minimum log information than the existing approaches.
文摘This paper presents a novel efficient semantic image classification algorithm for high-level feature indexing of high-dimension image database. Experiments show that the algorithm performs well. The size of the train set and the test set is 7 537 and 5 000 respectively. Based on this theory, another ground is built with 12,000 images, which are divided into three classes: city, landscape and person, the total result of the classifications is 88.92%, meanwhile, some preliminary results are presented for image understanding based on semantic image classification and low level features. The groundtruth for the experiments is built with the images from Corel database, photos and some famous face databases.
基金supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) research grants 194376 and 185986Manitoba Centre of Excellence Fund(MCEF) grant and Canadian Network Centre of Excellence(NCE) and Canadian Arthritis Network(CAN) grant SRI-BIO-05.
文摘The problem considered in this paper is how to detect the degree of similarity in the content of digital images useful in image retrieval,i.e.,to what extent is the content of a query image similar to content of other images.The solution to this problem results from the detection of subsets that are rough sets contained in covers of digital images determined by perceptual tolerance relations(PTRs).Such relations are defined within the context of perceptual representative spaces that hearken back to work by J.H.Poincare on representative spaces as models of physical continua.Classes determined by a PTR provide content useful in content-based image retrieval(CBIR).In addition,tolerance classes provide a means of determining when subsets of image covers are tolerance rough sets(TRSs).It is the nearness of TRSs present in image tolerance spaces that provide a promising approach to CBIR,especially in cases such as satellite images or aircraft identification where there are subtle differences between pairs of digital images,making it difficult to quantify the similarities between such images.The contribution of this article is the introduction of the nearness of tolerance rough sets as an effective means of measuring digital image similarities and,as a significant consequence,successfully carrying out CBIR.
文摘In order to extract peptides from formalin-fixed tissue and compare the peptide profile differences between control group and disease group,different antigen retrieval(AR) methods were investigated in this paper: organic solvent,trypsin and magnetic bead.MALDI-TOF MS was used for evaluating the retrieval efficiency.Results showed: trypsin retrieval method was compatible to MS analysis and the higher quality spectra could be acquired,the time of digestion did not affect the peptide profile but the concentration was crucial.We concluded the optimal conditions as follows: digestion with 0.1μg/μL of trypsin at 37℃ for 2h and using the of α-cyano-4-hydroxy cinnamic acid as the MALDI matrix.
基金Project(NZ1628)supported by the Natural Science Foundation of Ningxia,China
文摘Building a cloud geodatabase for a sponge city is crucial to integrate the geospatial information dispersed in various departments for multi-user high concurrent access and retrieval,high scalability and availability,efficient storage and management.In this study,Hadoop distributed computing framework,including Hadoop distributed file system and MapReduce(mapper and reducer),is firstly designed with a parallel computing framework to process massive spatial data.Then,access control with a series of standard application programming interfaces for different functions is designed,including spatial data storage layer,cloud geodatabase access layer,spatial data access layer and spatial data analysis layer.Subsequently,a retrieval model is designed,including direct addressing via file name,three-level concurrent retrieval and block data retrieval strategies.Main functions are realised,including real-time concurrent access,high-performance computing,communication,massive data storage,efficient retrieval and scheduling decisions on the multi-scale,multi-source and massive spatial data.Finally,the performance of Hadoop cloud geodatabases is validated and compared with that of the Oracle database.The cloud geodatabase for the sponge city can avoid redundant configuration of personnel,hardware and software,support the data transfer,model debugging and application development,and provide accurate,real-time,virtual,intelligent,reliable,elastically scalable,dynamic and on-demand cloud services of the basic and thematic geographic information for the construction and management of the sponge city.
文摘Several users use metasearch engines directly or indirectly to access and gather data from more than one data sources. The effectiveness of a metasearch engine is majorly determined by the quality of the results and it returns and in response to user queries. The rank aggregation methods which have been proposed until now exploits very limited set of parameters such as total number of used resources and the rankings they achieved from each individual resource. In this work, we use the neural network to merge the score computation module effectively. Initially, we give a query to different search engines and the top n list from each search engine is chosen for further processing our technique. We then merge the top n list based on unique links and we do some parameter calculations such as title based calculation, snippet based calculation, content based calculation, domain calculation, position calculation and co-occurrence calculation. We give the solutions of the calculations with user given ranking of links to the neural network to train the system. The system then rank and merge the links we obtain from different search engines for the query we give. Experimentation results reports a retrieval effectiveness of about 80%, precision of about 79% for user queries and about 72% for benchmark queries. The proposed technique also includes a response time of about 76 ms for 50 links and 144 ms for 100 links.
文摘This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer.A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer(SHRB).Simulation results show that SHRB has a better performance,accuracy,and applicability and more powerful eigenvalues than conventional beamformers.A simple mathematical proof is provided.By changing the number of harmonics,as a degree of freedom that is missing in conventional beamformers,SHRB can achieve more optimal outputs without increasing the number of spatial or temporal samples.We will demonstrate that SHRB offers an improvement of 4 dB in signal to noise ratio(SNR) in bit error rate(BER) of 10~(-4) over conventional beamformers.In the case of direction of arrival(DOA) estimation,SHRB can estimate the DOA of the desired signal with an SNR of-25 dB,when conventional methods cannot have acceptable response.
基金supported by the National Natural Science Foundation of China(Grant No.U21B2075)。
文摘Dynamic analysis of the tethered satellite system(TSS)can provide a fundamental guideline to the evaluation of performance and robust design of the system examined.Uncertainties inherited with the parameters would induce unexpected variation of the response and deteriorate the reliability of the system.In this work,the effect of uncertain mass of the satellites on the deployment and retrieval dynamics of the TSS is investigated.First the interval mode is employed to take the variation of mass of satellite into account in the processes of deployment and retrieval.Then,the Chebyshev interval method is used to obtain the lower and upper response bounds of the TSS.To achieve a smooth and reliable implementation of deployment and retrieval,the nonlinear programming based on the Gauss pseudospectral method is adopted to obtain optimal trajectory of tether velocity.Numerical results show that the uncertainties of mass of the satellites have a distinct influence on the response of tether tension in the processes of deployment and retrieval.
基金supported by the Sharing and Diffusion of National R&D Outcome funded by the Korea Institute of Science and Technology Information
文摘Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.
文摘In this article, a new model of establishing flexible and utility bi-bliographic systems dependent on microcomputer or minicomputer is di-scussed and compared with the models of large systems and PC-basedsystems. A practical example based on this model, Union Catalog Systemof Serials in Western Languages, is used to show our solution for thedevelopment and utilization of the systems of this kind.
