Pub Date : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073403
Wen-Huan Wu, Zhang Qian
As we know, the problem of image matching is difficult and important in the field of computer vision. In this paper we present a novel matching algorithm based on local invariant feature description. Firstly, feature points are detected by difference of Gaussian. Secondly, the Haar-wavelet responses within a feature point neighborhood are projected into four directions, and then a 64-dimensional vector is generated for describing the feature point. Finally, matching pairs are determined by using the nearest neighbor distance ratio. Experimental results show that the proposed algorithm is not only rapid and robust, but the matching rate is higher than PCA-SIFT and SURF algorithms.
{"title":"A novel image matching algorithm using local description","authors":"Wen-Huan Wu, Zhang Qian","doi":"10.1109/ICCWAMTIP.2014.7073403","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073403","url":null,"abstract":"As we know, the problem of image matching is difficult and important in the field of computer vision. In this paper we present a novel matching algorithm based on local invariant feature description. Firstly, feature points are detected by difference of Gaussian. Secondly, the Haar-wavelet responses within a feature point neighborhood are projected into four directions, and then a 64-dimensional vector is generated for describing the feature point. Finally, matching pairs are determined by using the nearest neighbor distance ratio. Experimental results show that the proposed algorithm is not only rapid and robust, but the matching rate is higher than PCA-SIFT and SURF algorithms.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127357435","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073370
Xianggen Liu, Huasong Zhong, Sheng Chang, Y. Meng
This paper proposes a method to search safe landing site using dual-threshold image segmentation algorithm for Chang'e-3 when the digital elevation map is obtained. Aiming at meeting the need of security, the probe ought to choose a flat ground to land at. Thus an improved dual-threshold image segmentation algorithm is proposed to deal with the shadowed and light split regions of obstacles respectively. At the same time, genetic algorithm is used to optimize its parameters, and the image sampling is also used to improve the efficiency of the algorithm. In order to identify candidate safe landing areas, a search method based on the maximum blank squares is applied in the processed image. Experimental results show that the proposed method has a strong ability of recognizing obstacles and searching flat ground, and is conductive to real-time space exploration mission.
{"title":"Searching safe landing site with parameters optimization based on genetic algorithm","authors":"Xianggen Liu, Huasong Zhong, Sheng Chang, Y. Meng","doi":"10.1109/ICCWAMTIP.2014.7073370","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073370","url":null,"abstract":"This paper proposes a method to search safe landing site using dual-threshold image segmentation algorithm for Chang'e-3 when the digital elevation map is obtained. Aiming at meeting the need of security, the probe ought to choose a flat ground to land at. Thus an improved dual-threshold image segmentation algorithm is proposed to deal with the shadowed and light split regions of obstacles respectively. At the same time, genetic algorithm is used to optimize its parameters, and the image sampling is also used to improve the efficiency of the algorithm. In order to identify candidate safe landing areas, a search method based on the maximum blank squares is applied in the processed image. Experimental results show that the proposed method has a strong ability of recognizing obstacles and searching flat ground, and is conductive to real-time space exploration mission.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126864357","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073365
Shu-Huai Ren
In recent years, information is increasing exponentially which makes it more and more difficult for people to find the needed information from the huge database. To fulfill this demanding, a high accurate and fast-time document retrieval algorithm is highly required for current applications. In this paper, based on the document similarity maximum criterion, we propose a new fast-time document retrieval algorithm based on the adaptive discrete stochastic optimization method. The designed adaptive step-size ensures the proposed algorithm converges fast to the relevant documents in the database and retrieve the optimal document. Numerical results demonstrate that the proposed algorithm gets better converge and retrieval performance than conventional methods in the huge database.
{"title":"A new relevant document retrieval algorithm via adaptive discrete stochastic optimization","authors":"Shu-Huai Ren","doi":"10.1109/ICCWAMTIP.2014.7073365","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073365","url":null,"abstract":"In recent years, information is increasing exponentially which makes it more and more difficult for people to find the needed information from the huge database. To fulfill this demanding, a high accurate and fast-time document retrieval algorithm is highly required for current applications. In this paper, based on the document similarity maximum criterion, we propose a new fast-time document retrieval algorithm based on the adaptive discrete stochastic optimization method. The designed adaptive step-size ensures the proposed algorithm converges fast to the relevant documents in the database and retrieve the optimal document. Numerical results demonstrate that the proposed algorithm gets better converge and retrieval performance than conventional methods in the huge database.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115355525","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073443
Xiao-Feng Gu, Jia-Wen Xu, Shi-Jing Huang, Liao-Ming Wang
Most stream classifiers need to detect and react to concept drifts, as traditional machine learning goes to big data machine learning. The most popular ways to adaptive to concept drifts are incrementally learning and classifier dynamic ensemble. Recent years, ensemble classifiers have become an established research line in this field, mainly due to their modularity which offers a natural way of adapting to changes. However, many ensembles which process instances in blocks do not react to sudden changes sufficiently quickly, and which process streams incrementally do not offer accurate reactions to gradual and incremental changes. Fortunately, an Online Accuracy Updated Ensemble (OAUE) algorithm was presented by Brzezinski and Stefanowski. OAUE algorithm has been proven to be an effective ensemble to deal with drifting data stream. But, it has a potentially weakness to adaptive to sudden changes as it uses a fixed window. Therefore, we put forward a Window-Adaptive Online Accuracy Updated Ensemble (WAOAUE) algorithm, which is based on OAUE, and a change detector is added to the ensemble for deciding the window size of each candidate classifier. The proposed algorithm was experimentally compared with four state-of-the-art online ensembles, include OAUE, and provided best practice for big data stream mining.
{"title":"An improving online accuracy updated ensemble method in learning from evolving data streams","authors":"Xiao-Feng Gu, Jia-Wen Xu, Shi-Jing Huang, Liao-Ming Wang","doi":"10.1109/ICCWAMTIP.2014.7073443","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073443","url":null,"abstract":"Most stream classifiers need to detect and react to concept drifts, as traditional machine learning goes to big data machine learning. The most popular ways to adaptive to concept drifts are incrementally learning and classifier dynamic ensemble. Recent years, ensemble classifiers have become an established research line in this field, mainly due to their modularity which offers a natural way of adapting to changes. However, many ensembles which process instances in blocks do not react to sudden changes sufficiently quickly, and which process streams incrementally do not offer accurate reactions to gradual and incremental changes. Fortunately, an Online Accuracy Updated Ensemble (OAUE) algorithm was presented by Brzezinski and Stefanowski. OAUE algorithm has been proven to be an effective ensemble to deal with drifting data stream. But, it has a potentially weakness to adaptive to sudden changes as it uses a fixed window. Therefore, we put forward a Window-Adaptive Online Accuracy Updated Ensemble (WAOAUE) algorithm, which is based on OAUE, and a change detector is added to the ensemble for deciding the window size of each candidate classifier. The proposed algorithm was experimentally compared with four state-of-the-art online ensembles, include OAUE, and provided best practice for big data stream mining.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129522284","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073429
Yilong Wang
In this paper, we consider the quasilinear parabolic-elliptic repulsion chemotaxis system with logistic source under homogeneous Neumann boundary condition in a smooth bounded domain. It is proved that the classical solutions to the corresponding initial boundary value problem are uniformly bounded in time.
{"title":"Boundedness in a quasilinear parabolic-elliptic repulsion chemotaxis system with logistic source","authors":"Yilong Wang","doi":"10.1109/ICCWAMTIP.2014.7073429","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073429","url":null,"abstract":"In this paper, we consider the quasilinear parabolic-elliptic repulsion chemotaxis system with logistic source under homogeneous Neumann boundary condition in a smooth bounded domain. It is proved that the classical solutions to the corresponding initial boundary value problem are uniformly bounded in time.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120961063","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073454
Xiao-Feng Gu, Le Yang, Shaoquan Wu
In contemporary, the value of data has increasingly been seen. We need to deal with different types of data in different ways. For some data types, their value will be reduced with the passage of time. As a result, when we receive the data, we need to deal with it as soon as possible instead of accumulation. For this point, Map-Reduce is not enough. This article will introduce a Real-Time stream computing system which is based on node.js and focus on real-time data processing, abbreviated as VRSS. In order to transmit data stream, we will use the channel mechanism of redis.
{"title":"A real-time stream system based on node.js","authors":"Xiao-Feng Gu, Le Yang, Shaoquan Wu","doi":"10.1109/ICCWAMTIP.2014.7073454","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073454","url":null,"abstract":"In contemporary, the value of data has increasingly been seen. We need to deal with different types of data in different ways. For some data types, their value will be reduced with the passage of time. As a result, when we receive the data, we need to deal with it as soon as possible instead of accumulation. For this point, Map-Reduce is not enough. This article will introduce a Real-Time stream computing system which is based on node.js and focus on real-time data processing, abbreviated as VRSS. In order to transmit data stream, we will use the channel mechanism of redis.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113986916","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073408
Muhammad Hammad Memon, Asif Khan, Jian-ping Li, R. Shaikh, I. Memon, S. Deep
In recently years, in the era of multimedia technologies need for information/data retrieval systems getting more attention. The data might be image, video, audio and/or text files. Digital libraries, surveillance application, web applications and many other applications that handle huge volume of data essentially have data retrieval components. These data always include large-scale of independent information with both textual and visual contents. The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. In this paper, we proposed a method of Geo-location-based image retrieval (GLBIR). The proposed method identifies a geo location in an image using visual attention-based mechanism and represents them using its color layout descriptors and curve let descriptors. These features are extracted from geo location of query image from Flickr. The likeness between the query geo coordinates and image is ranked according to a similarity measure computed from the feature vectors. Our proposed model does not full semantic understanding of image content, uses visual metrics for example proximity, color contrast, size and nearness to image's boundaries to locate viewer's attention. We evaluate our approach on the image dataset from Flickr. We analyzed results analyzed and compared with state of art CBIR Systems and GLBIR Technique.
{"title":"Content based image retrieval based on geo-location driven image tagging on the social web","authors":"Muhammad Hammad Memon, Asif Khan, Jian-ping Li, R. Shaikh, I. Memon, S. Deep","doi":"10.1109/ICCWAMTIP.2014.7073408","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073408","url":null,"abstract":"In recently years, in the era of multimedia technologies need for information/data retrieval systems getting more attention. The data might be image, video, audio and/or text files. Digital libraries, surveillance application, web applications and many other applications that handle huge volume of data essentially have data retrieval components. These data always include large-scale of independent information with both textual and visual contents. The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. In this paper, we proposed a method of Geo-location-based image retrieval (GLBIR). The proposed method identifies a geo location in an image using visual attention-based mechanism and represents them using its color layout descriptors and curve let descriptors. These features are extracted from geo location of query image from Flickr. The likeness between the query geo coordinates and image is ranked according to a similarity measure computed from the feature vectors. Our proposed model does not full semantic understanding of image content, uses visual metrics for example proximity, color contrast, size and nearness to image's boundaries to locate viewer's attention. We evaluate our approach on the image dataset from Flickr. We analyzed results analyzed and compared with state of art CBIR Systems and GLBIR Technique.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131996577","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073432
Yong Luo, Zhiping Shi, Xin Zhou, Qiaoyan Liu, Qicong Yi
In order to solve the problem of spectrum and power allocation for D2D communication in cellular networks when the prior knowledge is not available, a method based on machine learning is proposed in this paper. Q-learning, which is one of the most important algorithms in machine learning, is proposed to solve the radio resource management in underlay mode to find the optimal strategy in time series. In this mode, Q-learning is used to finish the channel assignment and the power allocation at the same time. And the simulation results show that greater system capacity can be achieved through the method proposed in this paper.
{"title":"Dynamic resource allocations based on Q-learning for D2D communication in cellular networks","authors":"Yong Luo, Zhiping Shi, Xin Zhou, Qiaoyan Liu, Qicong Yi","doi":"10.1109/ICCWAMTIP.2014.7073432","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073432","url":null,"abstract":"In order to solve the problem of spectrum and power allocation for D2D communication in cellular networks when the prior knowledge is not available, a method based on machine learning is proposed in this paper. Q-learning, which is one of the most important algorithms in machine learning, is proposed to solve the radio resource management in underlay mode to find the optimal strategy in time series. In this mode, Q-learning is used to finish the channel assignment and the power allocation at the same time. And the simulation results show that greater system capacity can be achieved through the method proposed in this paper.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130796768","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073358
Fei Zhang, Y. Dou, Xin Niu
This paper presents an automatic deblurring approach for motion blur images. The approach explores the prior of the intensity and gradient to estimate the motion blur kernel from single blurred image. In this way, motion blur kernel could be well estimated not only on daytime images, but also on nighttime images. Efficient optimization method was given for the prior-based approach. Besides, a cost-effective method was also proposed to remove the noise of the kernel in the iterative kernel estimation. The proposed kernel enhancement approach could also improve the performance of other blind deblurring algorithm. Experimental results showed that the performance of the proposed algorithm was superior to many state-of-the-art blind deblurring algorithms, especially for nighttime images with saturated regions.
{"title":"A blind motion deblurring for daytime and nighttime images","authors":"Fei Zhang, Y. Dou, Xin Niu","doi":"10.1109/ICCWAMTIP.2014.7073358","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073358","url":null,"abstract":"This paper presents an automatic deblurring approach for motion blur images. The approach explores the prior of the intensity and gradient to estimate the motion blur kernel from single blurred image. In this way, motion blur kernel could be well estimated not only on daytime images, but also on nighttime images. Efficient optimization method was given for the prior-based approach. Besides, a cost-effective method was also proposed to remove the noise of the kernel in the iterative kernel estimation. The proposed kernel enhancement approach could also improve the performance of other blind deblurring algorithm. Experimental results showed that the performance of the proposed algorithm was superior to many state-of-the-art blind deblurring algorithms, especially for nighttime images with saturated regions.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132707391","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 : 2014-12-01DOI: 10.1109/ICCWAMTIP.2014.7073355
Tianshi Jia, Yanan Liu
In order to obtain real-time and accurately magnetic parameters, a micro digital magnetometer based on HMC1001 magnetoresistance sensors was designed. The paper detailedly illustrates the working principle and design scheme of the system. The data acquisition module adopts 24 bit sigma-delta A/D converter AD7732 to sample magnetic signals of three sensors. FPGA is applied as main master controller to perform the data acquisition and transmission. Finally, the sampled data are transmitted to the upper computer through RS485 interface in asynchronous serial mode. According to the analysis of writing and reading time diagrams of AD7732, the paper also introduces the software design of data collection. Through the use of parallel processing capabilities of FPGA, three-channel analog signals are sampled in parallel, which realizes the real time acquisition and transmission of magnetic signals. The test result showed that tricomponent magnetic resistance magnetometer has the good performance in linearity, noise level and long-term stability. Compared with traditional magnetometer, this system has advantages such as high reliability, high precision and low power consumption. It can be applied successfully in the detection of weak geomagnetic field signal.
{"title":"Design and implementation of weak magnetic measurement based on magnetoresistive sensors","authors":"Tianshi Jia, Yanan Liu","doi":"10.1109/ICCWAMTIP.2014.7073355","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2014.7073355","url":null,"abstract":"In order to obtain real-time and accurately magnetic parameters, a micro digital magnetometer based on HMC1001 magnetoresistance sensors was designed. The paper detailedly illustrates the working principle and design scheme of the system. The data acquisition module adopts 24 bit sigma-delta A/D converter AD7732 to sample magnetic signals of three sensors. FPGA is applied as main master controller to perform the data acquisition and transmission. Finally, the sampled data are transmitted to the upper computer through RS485 interface in asynchronous serial mode. According to the analysis of writing and reading time diagrams of AD7732, the paper also introduces the software design of data collection. Through the use of parallel processing capabilities of FPGA, three-channel analog signals are sampled in parallel, which realizes the real time acquisition and transmission of magnetic signals. The test result showed that tricomponent magnetic resistance magnetometer has the good performance in linearity, noise level and long-term stability. Compared with traditional magnetometer, this system has advantages such as high reliability, high precision and low power consumption. It can be applied successfully in the detection of weak geomagnetic field signal.","PeriodicalId":211273,"journal":{"name":"2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124457493","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：