Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4518110
M. Rübsamen, A. Gershman
Two computationally efficient high-resolution methods are proposed for direction-of-arrival (DOA) estimation in arbitrary nonuniform sensor arrays. Our first algorithm is based on the fact that the spectral MUSIC function is periodic in angle. Expanding this function using Fourier series, we reformulate the DOA estimation problem as an equivalent polynomial rooting problem. Our second approach applies the inverse Fourier transform to the so-obtained root-MUSIC polynomial to compute the null-spectrum without any polynomial rooting, using a simple line search. The proposed techniques are shown to offer substantially improved performance-to- complexity tradeoffs as compared to the existing root-MUSIC-type methods applicable to non-uniform arrays.
{"title":"Root-music based direction-of-arrival estimation methods for arbitrary non-uniform arrays","authors":"M. Rübsamen, A. Gershman","doi":"10.1109/ICASSP.2008.4518110","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4518110","url":null,"abstract":"Two computationally efficient high-resolution methods are proposed for direction-of-arrival (DOA) estimation in arbitrary nonuniform sensor arrays. Our first algorithm is based on the fact that the spectral MUSIC function is periodic in angle. Expanding this function using Fourier series, we reformulate the DOA estimation problem as an equivalent polynomial rooting problem. Our second approach applies the inverse Fourier transform to the so-obtained root-MUSIC polynomial to compute the null-spectrum without any polynomial rooting, using a simple line search. The proposed techniques are shown to offer substantially improved performance-to- complexity tradeoffs as compared to the existing root-MUSIC-type methods applicable to non-uniform arrays.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130391951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4517820
Ke-Ying Liao, J. Yang, Ming-Ting Sun
In this paper, a modified bit-rate estimation method is proposed to reduce the computation for 4x4 intra mode decision of H.264/AVC video encoder. The number of coded bits is modeled by a linear combination of existing coding parameters, which are highly related to the entropy coding of H.264/AVC. Furthermore, to improve the accuracy of the estimation, the proposed scheme is made adaptive to the information obtained from previously coded blocks. Comparing to the original rate distortion optimized (RDO) encoding process, which needs to calculate the actual encoded bits of H.264/AVC for each coding mode, the proposed adaptive rate estimation can save about 28% and 21% of the total encoding time for QCIF and VGA sequences, respectively. For the coding performance, the proposed method achieves nearly no loss in visual quality with only slight bit-rate increases.
{"title":"Adaptive rate estimation for H.264/AVC intra mode decision","authors":"Ke-Ying Liao, J. Yang, Ming-Ting Sun","doi":"10.1109/ICASSP.2008.4517820","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4517820","url":null,"abstract":"In this paper, a modified bit-rate estimation method is proposed to reduce the computation for 4x4 intra mode decision of H.264/AVC video encoder. The number of coded bits is modeled by a linear combination of existing coding parameters, which are highly related to the entropy coding of H.264/AVC. Furthermore, to improve the accuracy of the estimation, the proposed scheme is made adaptive to the information obtained from previously coded blocks. Comparing to the original rate distortion optimized (RDO) encoding process, which needs to calculate the actual encoded bits of H.264/AVC for each coding mode, the proposed adaptive rate estimation can save about 28% and 21% of the total encoding time for QCIF and VGA sequences, respectively. For the coding performance, the proposed method achieves nearly no loss in visual quality with only slight bit-rate increases.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130494497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4518087
T. Nwe, Haizhou Li
Timbre is the quality of sound which allows the ear to distinguish between musical sounds. In this paper, we study timbre effects in identification of singing voice segments in popular songs. Firstly, we identify between singing voice and instrumental segments in a song. Then, singing voice segments are further categorized according to their singer identity. Timbre-motivated effects are formulated by fusion of systems that use the features from vibrato, harmonic information and other features extracted using Mel and Log frequency scale filter banks. Statistical methods to select singing voice segments with high confidence measure are proposed for better performance in singer identification process. The experiments conducted on a database of 214 popular songs show that the proposed approach is effective.
{"title":"On fusion of timbre-motivated features for singing voice detection and singer identification","authors":"T. Nwe, Haizhou Li","doi":"10.1109/ICASSP.2008.4518087","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4518087","url":null,"abstract":"Timbre is the quality of sound which allows the ear to distinguish between musical sounds. In this paper, we study timbre effects in identification of singing voice segments in popular songs. Firstly, we identify between singing voice and instrumental segments in a song. Then, singing voice segments are further categorized according to their singer identity. Timbre-motivated effects are formulated by fusion of systems that use the features from vibrato, harmonic information and other features extracted using Mel and Log frequency scale filter banks. Statistical methods to select singing voice segments with high confidence measure are proposed for better performance in singer identification process. The experiments conducted on a database of 214 popular songs show that the proposed approach is effective.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130558062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4518262
M. Joham, H. Brunner, R. Hunger, D. Schmidt, W. Utschick
Non-linear precoding for point-to-point (P2P) multiple-input multiple-output (MIMO) systems is considered. First, the minimum mean square error (MMSE) optimal vector precoding (VP) is presented for different receiver structures, viz., weighted identity matrix, diagonal matrix, weighted unitary matrix, and matrix without particular structure. Whereas the former two structures can also be applied to the vector broadcast channel, the latter two are only realizable for cooperative receivers. Second, VP is derived that minimizes the MSE but is restricted to maximize the mutual information of the MIMO channel. Third, the corresponding Tomlinson-Harashima precoding (THP) is found by applying the nearest-plane approximation to the computation of the perturbation signal. The resulting maximum mutual information THP clearly outperforms the state-of-the-art P2P-MIMO THP based on the generalized triangular decomposition (GTD) with respect to MSE and BER.
{"title":"Point-to-point MIMO MMSE vector precoding and thp achieving capacity","authors":"M. Joham, H. Brunner, R. Hunger, D. Schmidt, W. Utschick","doi":"10.1109/ICASSP.2008.4518262","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4518262","url":null,"abstract":"Non-linear precoding for point-to-point (P2P) multiple-input multiple-output (MIMO) systems is considered. First, the minimum mean square error (MMSE) optimal vector precoding (VP) is presented for different receiver structures, viz., weighted identity matrix, diagonal matrix, weighted unitary matrix, and matrix without particular structure. Whereas the former two structures can also be applied to the vector broadcast channel, the latter two are only realizable for cooperative receivers. Second, VP is derived that minimizes the MSE but is restricted to maximize the mutual information of the MIMO channel. Third, the corresponding Tomlinson-Harashima precoding (THP) is found by applying the nearest-plane approximation to the computation of the perturbation signal. The resulting maximum mutual information THP clearly outperforms the state-of-the-art P2P-MIMO THP based on the generalized triangular decomposition (GTD) with respect to MSE and BER.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126696126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4517906
M. Greco, F. Gini, A. Farina, L. Timmoneri
In this paper we compare two radar target direction-of-arrival (DOA) estimation algorithms, the classical moving window (MW) and the asymptotic maximum likelihood (AML) estimators. The first technique for azimuth DOA estimation exploits multiple detections in the same time-on-target and the second one exploits the fact that the radar antenna mechanical scanning impresses an amplitude modulation on the signals backscattered by the target. Performances of the estimators are numerically investigated through Monte Carlo simulation in terms of root-mean-square-error (RMSE), probability of detection for a fixed probability of false alarm, and probability of "splitting". The obtained results show that the asymptotic maximum likelihood estimator generally outperforms the classical moving window estimator.
{"title":"Radar target doa estimation: Moving window VS AML estimator","authors":"M. Greco, F. Gini, A. Farina, L. Timmoneri","doi":"10.1109/ICASSP.2008.4517906","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4517906","url":null,"abstract":"In this paper we compare two radar target direction-of-arrival (DOA) estimation algorithms, the classical moving window (MW) and the asymptotic maximum likelihood (AML) estimators. The first technique for azimuth DOA estimation exploits multiple detections in the same time-on-target and the second one exploits the fact that the radar antenna mechanical scanning impresses an amplitude modulation on the signals backscattered by the target. Performances of the estimators are numerically investigated through Monte Carlo simulation in terms of root-mean-square-error (RMSE), probability of detection for a fixed probability of false alarm, and probability of \"splitting\". The obtained results show that the asymptotic maximum likelihood estimator generally outperforms the classical moving window estimator.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126785909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4518078
Ting-Yu Huang, Guo-An Jian, J. Chu, Ching-Lung Su, Jiun-In Guo
In this paper, we propose a joint algorithm/code-level optimization scheme to make it feasible to perform real-time H.264/AVC video decoding software on ARM-based platform for mobile multimedia applications. In the algorithm-level optimization, we propose various techniques like fast interpolation scheme, zero-skipping technique for texture decoding, fast boundary strength decision for in-loop filtering, and pattern matching algorithm for CAVLD. In the code-level optimization, we propose the design techniques on minimizing memory access and branch times. The experimental result shows that we have reduced the complexity of H.264 video decoder up to 93% as compared to the reference software JM9.7. The optimized H.264 video decoder can achieve the QCIF@30Hz video decoding on an ARM9 processor when operating at 120MHz clock.
{"title":"Joint algorithm/code-level optimization of H.264 video decoder for mobile multimedia applications","authors":"Ting-Yu Huang, Guo-An Jian, J. Chu, Ching-Lung Su, Jiun-In Guo","doi":"10.1109/ICASSP.2008.4518078","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4518078","url":null,"abstract":"In this paper, we propose a joint algorithm/code-level optimization scheme to make it feasible to perform real-time H.264/AVC video decoding software on ARM-based platform for mobile multimedia applications. In the algorithm-level optimization, we propose various techniques like fast interpolation scheme, zero-skipping technique for texture decoding, fast boundary strength decision for in-loop filtering, and pattern matching algorithm for CAVLD. In the code-level optimization, we propose the design techniques on minimizing memory access and branch times. The experimental result shows that we have reduced the complexity of H.264 video decoder up to 93% as compared to the reference software JM9.7. The optimized H.264 video decoder can achieve the QCIF@30Hz video decoding on an ARM9 processor when operating at 120MHz clock.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129238779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4517676
H. Vikalo, F. Parvaresh, Sidhant Misra, B. Hassibi
DNA microarrays comprising tens of thousands of probe spots are currently being employed to test multitude of targets in a single experiment. Typically, each microarray spot contains a large number of copies of a single probe designed to capture a single target, and hence collects only a single data point. This is a wasteful use of the sensing resources in comparative DNA microarray experiments, where a test sample is measured relative to a reference sample. Since only a small fraction of the total number of genes represented by the two samples is differentially expressed, a vast number of probe spots will not provide any useful information. To this end we consider an alternative design, the so-called compressed microarrays, wherein each spot is a composite of several different probes and the total number of spots is potentially much smaller than the number of targets being tested. Fewer spots directly translates to significantly lower costs due to cheaper array manufacturing, simpler image acquisition and processing, and smaller amount of genomic material needed for experiments. To recover signals from compressed microarray measurements, we leverage ideas from compressive sampling. Moreover, we propose an algorithm which has far less computational complexity than the widely-used linear-programming-based methods, and can also recover signals with less sparsity.
{"title":"Sparse measurements, compressed sampling, and DNA microarrays","authors":"H. Vikalo, F. Parvaresh, Sidhant Misra, B. Hassibi","doi":"10.1109/ICASSP.2008.4517676","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4517676","url":null,"abstract":"DNA microarrays comprising tens of thousands of probe spots are currently being employed to test multitude of targets in a single experiment. Typically, each microarray spot contains a large number of copies of a single probe designed to capture a single target, and hence collects only a single data point. This is a wasteful use of the sensing resources in comparative DNA microarray experiments, where a test sample is measured relative to a reference sample. Since only a small fraction of the total number of genes represented by the two samples is differentially expressed, a vast number of probe spots will not provide any useful information. To this end we consider an alternative design, the so-called compressed microarrays, wherein each spot is a composite of several different probes and the total number of spots is potentially much smaller than the number of targets being tested. Fewer spots directly translates to significantly lower costs due to cheaper array manufacturing, simpler image acquisition and processing, and smaller amount of genomic material needed for experiments. To recover signals from compressed microarray measurements, we leverage ideas from compressive sampling. Moreover, we propose an algorithm which has far less computational complexity than the widely-used linear-programming-based methods, and can also recover signals with less sparsity.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129238901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4518097
S. Barbarossa, T. Battisti, A. Swami
In most sensor network applications, the vector containing the observations gathered by the sensors lies in a space of dimension equal to the number of nodes, typically because of observation noise, even though the useful signal belongs to a subspace of much smaller dimension. This motivates smoothing or rank reduction. We formulate a convex optimization problem, where we incorporate a fidelity constraint that prevents the final smoothed estimate from diverging too far from the observations. This leads to a distributed algorithm in which nodes exchange updates only with neighboring nodes. We show that the widely studied consensus algorithm is indeed only a very specific case of our more general formulation. Finally, we study the convergence rate and propose some approaches to maximize it.
{"title":"Globally optimal decentralized spatial smoothing for wireless sensor networks with local interactions","authors":"S. Barbarossa, T. Battisti, A. Swami","doi":"10.1109/ICASSP.2008.4518097","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4518097","url":null,"abstract":"In most sensor network applications, the vector containing the observations gathered by the sensors lies in a space of dimension equal to the number of nodes, typically because of observation noise, even though the useful signal belongs to a subspace of much smaller dimension. This motivates smoothing or rank reduction. We formulate a convex optimization problem, where we incorporate a fidelity constraint that prevents the final smoothed estimate from diverging too far from the observations. This leads to a distributed algorithm in which nodes exchange updates only with neighboring nodes. We show that the widely studied consensus algorithm is indeed only a very specific case of our more general formulation. Finally, we study the convergence rate and propose some approaches to maximize it.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130613406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4517850
Kuang-Hung Liu, D. Munson
Synthetic aperture radar (SAR) imaging suffers from image focus degradation in the presence of phase errors in the received signals due to unknown platform or target motion. We study automatic focusing (autofocus) under a multistatic passive scenario, where the illumination is provided by a set of stationary UHF transmitters and the goal is to image a moving aircraft. We employ heuristic iterative estimation algorithms that maximize a sharpness metric of the image. A similar method has been studied for the case of mono-static radar, where only one antenna is used for both transmitting and receiving. We present simulation results to help assess the effectiveness of the proposed autofocus approach.
{"title":"Autofocus in multistatic passive SAR imaging","authors":"Kuang-Hung Liu, D. Munson","doi":"10.1109/ICASSP.2008.4517850","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4517850","url":null,"abstract":"Synthetic aperture radar (SAR) imaging suffers from image focus degradation in the presence of phase errors in the received signals due to unknown platform or target motion. We study automatic focusing (autofocus) under a multistatic passive scenario, where the illumination is provided by a set of stationary UHF transmitters and the goal is to image a moving aircraft. We employ heuristic iterative estimation algorithms that maximize a sharpness metric of the image. A similar method has been studied for the case of mono-static radar, where only one antenna is used for both transmitting and receiving. We present simulation results to help assess the effectiveness of the proposed autofocus approach.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123464049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-12DOI: 10.1109/ICASSP.2008.4517851
Dun-Yu Hsiao, H. Liao
In this paper, we propose an effective scheme to enhance the visual details at the minimal cost of user adjustments. The uprising importance of automatic tone reproduction comes from the increasing population of digital archive programs, which contains a large number of images/videos either old irreproducible, or poorly captured. We attempt to solve above issues by a new local normalization step and an adaptive contrast assessment process. With those two processes, our method can effectively enhance poor quality regions and simultaneously preserving good quality ones with default parameter settings. The experimental results demonstrate that our method is superior to many existing algorithms when applied to aid digital archiving issues.
{"title":"Smart tone reproduction","authors":"Dun-Yu Hsiao, H. Liao","doi":"10.1109/ICASSP.2008.4517851","DOIUrl":"https://doi.org/10.1109/ICASSP.2008.4517851","url":null,"abstract":"In this paper, we propose an effective scheme to enhance the visual details at the minimal cost of user adjustments. The uprising importance of automatic tone reproduction comes from the increasing population of digital archive programs, which contains a large number of images/videos either old irreproducible, or poorly captured. We attempt to solve above issues by a new local normalization step and an adaptive contrast assessment process. With those two processes, our method can effectively enhance poor quality regions and simultaneously preserving good quality ones with default parameter settings. The experimental results demonstrate that our method is superior to many existing algorithms when applied to aid digital archiving issues.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123650482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：