Pub Date : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974580
Chen-Hung Yu, Weiping Li
This paper presents a new mechanism for data transmission over mobile networks. The ultimate goal of designing the next generation mobile network is to have a single network that can support all applications with different data attributes. The proposed mechanism in this paper is inspired by the Mechanism Design Theory that is an emerging branch of game theory and has been used successfully in economics. The proposed attribute switching mechanism provides incentives for network applications to label their data attributes honestly and processes the data according to their attributes so that all applications achieve their best possible data transmission results without taking unnecessary network resources. Our simulation results have shown that the proposed approach performs better than other methods.
{"title":"An attribute switching mechanism for mobile networks","authors":"Chen-Hung Yu, Weiping Li","doi":"10.1109/ICNIDC.2016.7974580","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974580","url":null,"abstract":"This paper presents a new mechanism for data transmission over mobile networks. The ultimate goal of designing the next generation mobile network is to have a single network that can support all applications with different data attributes. The proposed mechanism in this paper is inspired by the Mechanism Design Theory that is an emerging branch of game theory and has been used successfully in economics. The proposed attribute switching mechanism provides incentives for network applications to label their data attributes honestly and processes the data according to their attributes so that all applications achieve their best possible data transmission results without taking unnecessary network resources. Our simulation results have shown that the proposed approach performs better than other methods.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124532849","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974588
Jaewook Kwak, Hyung Chan Kim, I. Park, Y. Song
Unlike hard disk drive (HDD)-based storage systems, NAND flash memory-based storage systems require an additional layer called the flash translation layer (FTL) between the file system and storage devices. The FTL helps file systems use NAND flash memory in the same way as HDD by using the address mapping function. However, this function can produce a side effect of delaying the physical erasure point of data when deleting data. In this paper, we analyze the time delay phenomenon of data erasure from the flash storage device that uses the FTL and propose the anti-forensic deletion scheme, which can minimize the delay time. The experimental results confirm that the proposed deletion scheme is effective in reducing the delay time of data erasing.
{"title":"Anti-forensic deletion scheme for flash storage systems","authors":"Jaewook Kwak, Hyung Chan Kim, I. Park, Y. Song","doi":"10.1109/ICNIDC.2016.7974588","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974588","url":null,"abstract":"Unlike hard disk drive (HDD)-based storage systems, NAND flash memory-based storage systems require an additional layer called the flash translation layer (FTL) between the file system and storage devices. The FTL helps file systems use NAND flash memory in the same way as HDD by using the address mapping function. However, this function can produce a side effect of delaying the physical erasure point of data when deleting data. In this paper, we analyze the time delay phenomenon of data erasure from the flash storage device that uses the FTL and propose the anti-forensic deletion scheme, which can minimize the delay time. The experimental results confirm that the proposed deletion scheme is effective in reducing the delay time of data erasing.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127997233","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974540
Yuanying Peng, K. Yu
Nowadays Internet user behavior becomes more and more complicated due to application diversity. It is important to analyze user behavior on specific websites such as e-commerce, education, and healthcare in order for personalized recommendation or targeted advertisement. In this paper, based on the large-scale traffic flow data of real network and crawling data from websites, we focus on the analysis of user browsing behavior on automobile websites. First of all, data pre-processing and statistical analysis based on MapReduce framework are designed and implemented, which is mainly to transform the flow data type to sequential dataset. By improving regular expressions matching method in distributed computing, the running time is reduced from O(N) to O(1). Secondly, we apply the sequential pattern mining algorithm AprioriAll to analyze the sequential dataset. The analysis result reflects the preference of the users when browsing automobile websites to acquire their wanted information.
{"title":"User behavior analysis of automobile websites based on distributed computing and sequential pattern mining","authors":"Yuanying Peng, K. Yu","doi":"10.1109/ICNIDC.2016.7974540","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974540","url":null,"abstract":"Nowadays Internet user behavior becomes more and more complicated due to application diversity. It is important to analyze user behavior on specific websites such as e-commerce, education, and healthcare in order for personalized recommendation or targeted advertisement. In this paper, based on the large-scale traffic flow data of real network and crawling data from websites, we focus on the analysis of user browsing behavior on automobile websites. First of all, data pre-processing and statistical analysis based on MapReduce framework are designed and implemented, which is mainly to transform the flow data type to sequential dataset. By improving regular expressions matching method in distributed computing, the running time is reduced from O(N) to O(1). Secondly, we apply the sequential pattern mining algorithm AprioriAll to analyze the sequential dataset. The analysis result reflects the preference of the users when browsing automobile websites to acquire their wanted information.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122371661","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974564
Yuqian Qiao, K. Niu, Zhiqiang He
Recent researches on graph signal processing (GSP) have been successfully applied on homogeneous networks. However, in real-world network, nodes and relationships of multiple types are usually heterogeneous. In this paper, we discuss signal processing on heterogeneous networks. Heterogeneous networks are modeled as hypergraphs by adjacency tensor. An algorithm called signal processing on tensor (TSP) is proposed to analyze signal propagation in vertex and frequency domain. In vertex domain, TSP propagates signals not only on homogeneous subgraphs but also on hypergraphs including hyperlinks of multi-subgraphs. In frequency domain, tensor Fourier transform is defined based on factor matrices of higher-order singular value decomposition (HOSVD), which is used to describe high and low frequencies of signals on hypergraphs. Finally, we verify algorithm by data classification on network generated randomly. Comparing to classification on homogeneous subgraphs merely, our algorithm achieves higher accuracy.
{"title":"Signal processing on heterogeneous network based on tensor decomposition","authors":"Yuqian Qiao, K. Niu, Zhiqiang He","doi":"10.1109/ICNIDC.2016.7974564","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974564","url":null,"abstract":"Recent researches on graph signal processing (GSP) have been successfully applied on homogeneous networks. However, in real-world network, nodes and relationships of multiple types are usually heterogeneous. In this paper, we discuss signal processing on heterogeneous networks. Heterogeneous networks are modeled as hypergraphs by adjacency tensor. An algorithm called signal processing on tensor (TSP) is proposed to analyze signal propagation in vertex and frequency domain. In vertex domain, TSP propagates signals not only on homogeneous subgraphs but also on hypergraphs including hyperlinks of multi-subgraphs. In frequency domain, tensor Fourier transform is defined based on factor matrices of higher-order singular value decomposition (HOSVD), which is used to describe high and low frequencies of signals on hypergraphs. Finally, we verify algorithm by data classification on network generated randomly. Comparing to classification on homogeneous subgraphs merely, our algorithm achieves higher accuracy.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"100 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131479303","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974581
Junchen Li, Fengmin Li, Jian Kuang, Song Song, Juchen Pan
Recently, those methods of protecting application from crack have a great development. Code obfuscation, dynamic link library, software shelling, those methods all have different levels of innovation and optimization [1]. However, various software crack technology also became increasingly mature. Static code analysis cooperating with dynamic code analysis makes mostly code reinforcement method failed. After analyzing all of those code reinforcement method, author came up with a kind of core code reinforcement method, which is organized with client and server architecture and based on dynamic loading. Different with most methods, this method can ensure even if hacker has obtained the original dex file, the application can still be safe.
{"title":"A core code reinforcement method based on dynamic loading on Android platform","authors":"Junchen Li, Fengmin Li, Jian Kuang, Song Song, Juchen Pan","doi":"10.1109/ICNIDC.2016.7974581","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974581","url":null,"abstract":"Recently, those methods of protecting application from crack have a great development. Code obfuscation, dynamic link library, software shelling, those methods all have different levels of innovation and optimization [1]. However, various software crack technology also became increasingly mature. Static code analysis cooperating with dynamic code analysis makes mostly code reinforcement method failed. After analyzing all of those code reinforcement method, author came up with a kind of core code reinforcement method, which is organized with client and server architecture and based on dynamic loading. Different with most methods, this method can ensure even if hacker has obtained the original dex file, the application can still be safe.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565157","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974556
Yang Liu, Ya Zhang, Hui Wang, Juan Xu, Jiwen Li
Diverse antivirus engines have different naming rules for Android malwares, so that they return detection results of the same application in different expression forms. This paper researches the naming methods of the malwares by the engines, and institutes a standardized naming rule for the malwares which is easy to understand. This paper also designs a method to standardize the Android application's detection results provided by the engines. The method uses the character recognition and the sample matching to realize the unification of the detection results, and obtain the results in standard form which have clear meanings and available for evaluation. The experimental results show that the method can effectively unify various forms of detection results, and provide explicit and rich application identification information.
{"title":"Research on standardization of the Android malware detection results","authors":"Yang Liu, Ya Zhang, Hui Wang, Juan Xu, Jiwen Li","doi":"10.1109/ICNIDC.2016.7974556","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974556","url":null,"abstract":"Diverse antivirus engines have different naming rules for Android malwares, so that they return detection results of the same application in different expression forms. This paper researches the naming methods of the malwares by the engines, and institutes a standardized naming rule for the malwares which is easy to understand. This paper also designs a method to standardize the Android application's detection results provided by the engines. The method uses the character recognition and the sample matching to realize the unification of the detection results, and obtain the results in standard form which have clear meanings and available for evaluation. The experimental results show that the method can effectively unify various forms of detection results, and provide explicit and rich application identification information.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123079342","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974607
Suyou Li, Zhigang Guo, Guochu Shou, Yihong Hu, Hongxing Li
Mobile Edge Computing (MEC) provides mobile and cloud computing capabilities within the access network. Network Functions Virtualization (NFV) leverages standard IT Virtualization technology to decouple the network functions from the underlying physical infrastructure. Basing on the ICT demand, MEC can be consolidated into NFV, as a network element within access network. This paper presents an architecture of NFV-based MEC platform and analyzes its Quality of Service (QoS) compared with the remote servers (Shenzhen and Qingdao). Then, this paper measures the Quality of Experience (QoE) of HTTP videos deployed in the servers. The result shows MEC can offer a service environment with higher bandwidth, which supports 10-fold gains, and ultra-low latency, jitter and packet loss rate. Moreover, along with the higher resolution and bitrates, the range of the video QoE improvement on this platform rises compared with the remote servers. In a word, the NFV-based MEC can achieve better performance than the remote servers.
{"title":"QoE analysis of NFV-based mobile edge computing video application","authors":"Suyou Li, Zhigang Guo, Guochu Shou, Yihong Hu, Hongxing Li","doi":"10.1109/ICNIDC.2016.7974607","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974607","url":null,"abstract":"Mobile Edge Computing (MEC) provides mobile and cloud computing capabilities within the access network. Network Functions Virtualization (NFV) leverages standard IT Virtualization technology to decouple the network functions from the underlying physical infrastructure. Basing on the ICT demand, MEC can be consolidated into NFV, as a network element within access network. This paper presents an architecture of NFV-based MEC platform and analyzes its Quality of Service (QoS) compared with the remote servers (Shenzhen and Qingdao). Then, this paper measures the Quality of Experience (QoE) of HTTP videos deployed in the servers. The result shows MEC can offer a service environment with higher bandwidth, which supports 10-fold gains, and ultra-low latency, jitter and packet loss rate. Moreover, along with the higher resolution and bitrates, the range of the video QoE improvement on this platform rises compared with the remote servers. In a word, the NFV-based MEC can achieve better performance than the remote servers.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124496173","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974583
Yingjie Li, Gang Liu
This paper presents an audio event classification algorithm which automatically classifies an audio event as footstep, glass breaking, gunshot or scream mainly for surveillance applications. First, the Gabor feature of the audio spectrogram is extracted, there are two kinds of Gabor features, namely global Gabor feature and local Gabor feature. Then we use Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA) to compress the feature dimension, finally the K nearest neighbor classifier (KNN) is used to recognize audio events. We carried out extensive experiments on the clean and noisy audio sets. Our results demonstrate that the algorithm is able to guarantee a recall of 96.1% on clean sets and is proved to be more effective than traditional methods.
{"title":"Sound classification based on spectrogram for surveillance applications","authors":"Yingjie Li, Gang Liu","doi":"10.1109/ICNIDC.2016.7974583","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974583","url":null,"abstract":"This paper presents an audio event classification algorithm which automatically classifies an audio event as footstep, glass breaking, gunshot or scream mainly for surveillance applications. First, the Gabor feature of the audio spectrogram is extracted, there are two kinds of Gabor features, namely global Gabor feature and local Gabor feature. Then we use Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA) to compress the feature dimension, finally the K nearest neighbor classifier (KNN) is used to recognize audio events. We carried out extensive experiments on the clean and noisy audio sets. Our results demonstrate that the algorithm is able to guarantee a recall of 96.1% on clean sets and is proved to be more effective than traditional methods.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127658003","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974593
Yang Liu, Chao Dong, Zhiqiang He
In this paper, we introduce a block iterative frequency domain decision feedback equalizer with noise prediction (NP-BI) for single-carrier (SC) multiple input multiple output (MIMO) relay systems. Firstly, we derive the minimum mean-squared error (MMSE) equalizer at the destination node. Then the decision feedback equalizer coefficients can be calculated according to the error covariance matrix of the MMSE equalizer and the equivalent channel frequency-domain (FD) response. Then, we combine the spatial precoding matrix with the decision feedback equalizer at the source node, which performs better than the frequency domain equalization with noise prediction (FDE-NP), especially when the number of antennas is large. In addition, NP-BI has a lower computational complexity than FDE-NP.
{"title":"A low complexity decision feedback equalizer for single-carrier amplify-forward MIMO relay system","authors":"Yang Liu, Chao Dong, Zhiqiang He","doi":"10.1109/ICNIDC.2016.7974593","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974593","url":null,"abstract":"In this paper, we introduce a block iterative frequency domain decision feedback equalizer with noise prediction (NP-BI) for single-carrier (SC) multiple input multiple output (MIMO) relay systems. Firstly, we derive the minimum mean-squared error (MMSE) equalizer at the destination node. Then the decision feedback equalizer coefficients can be calculated according to the error covariance matrix of the MMSE equalizer and the equivalent channel frequency-domain (FD) response. Then, we combine the spatial precoding matrix with the decision feedback equalizer at the source node, which performs better than the frequency domain equalization with noise prediction (FDE-NP), especially when the number of antennas is large. In addition, NP-BI has a lower computational complexity than FDE-NP.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127948207","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 : 2016-09-01DOI: 10.1109/ICNIDC.2016.7974573
Jinnian Zhang, Yan Li, K. Niu
Generalized Frequency Division Multiplexing (GFDM) is a promising solution for the cellular system of the fifth generation (5G) PHY layer because its flexibility can address the different application requirements. However, due to the pulse shaping, there is inherent interference existing in the received signal, which has a negative impact on pilot-based channel estimation. Although the interference on the pilot symbols can be eliminated at the transmitter by using precoding matrices, the accompanied transmitting power penalty increases with the non-orthogonality of subcarriers and subsymbols. In our work, we propose an iterative method for interference cancellation at the receiver, which can efficiently mitigate the effect of neighboring symbols on pilots without transmitting power penalty. In addition, to improve the accuracy of channel estimation, we adopt the compressive sensing (CS) technology. Simulation results show that our proposed channel estimation algorithm is efficient even when the interference is severe, and by using orthogonal match pursuit (OMP) recovery algorithm, the performance of our algorithm can be close to the Cramer-Rao bound (CRB).
{"title":"Iterative channel estimation algorithm based on compressive sensing for GFDM","authors":"Jinnian Zhang, Yan Li, K. Niu","doi":"10.1109/ICNIDC.2016.7974573","DOIUrl":"https://doi.org/10.1109/ICNIDC.2016.7974573","url":null,"abstract":"Generalized Frequency Division Multiplexing (GFDM) is a promising solution for the cellular system of the fifth generation (5G) PHY layer because its flexibility can address the different application requirements. However, due to the pulse shaping, there is inherent interference existing in the received signal, which has a negative impact on pilot-based channel estimation. Although the interference on the pilot symbols can be eliminated at the transmitter by using precoding matrices, the accompanied transmitting power penalty increases with the non-orthogonality of subcarriers and subsymbols. In our work, we propose an iterative method for interference cancellation at the receiver, which can efficiently mitigate the effect of neighboring symbols on pilots without transmitting power penalty. In addition, to improve the accuracy of channel estimation, we adopt the compressive sensing (CS) technology. Simulation results show that our proposed channel estimation algorithm is efficient even when the interference is severe, and by using orthogonal match pursuit (OMP) recovery algorithm, the performance of our algorithm can be close to the Cramer-Rao bound (CRB).","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127967071","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：