Pub Date : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7924815
Shuhua Chen, David Zhang, Jian Wu, Bob Zhang
Disease diagnosis via an individual's facial color has been practiced in oriental medicine for thousands of years. This work tackles the issue of quantitative facial color feature extraction for diagnostic purposes. Existing work in this area directly utilizes classic methods found in the standard color analysis area. We believe that these standard chromatic methods are not the most suitable for describing facial colors. Hence, we propose a color extraction method specially designed for facial diagnosis. The main contribution of this work is to define the facial base colors and to present six non-base colors (centroid colors) to represent the facial color space. First, a facial color gamut in the CIEx-y chromatic diagram is formed. Next, an area composed of base colors is defined within the color gamut. Afterwards, some clusters are located outside the base colors area. Finally, six centroids are selected to form a set of components to describe the facial color features. Disease detection is performed to compare the performance of the proposed and existing methods. Overall, the experimental results show that the proposed method outperforms the existing methods, which verifies its validity and effectiveness.
{"title":"Facial color feature extraction for disease diagnosis using non-base colors","authors":"Shuhua Chen, David Zhang, Jian Wu, Bob Zhang","doi":"10.1109/COMPCOMM.2016.7924815","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7924815","url":null,"abstract":"Disease diagnosis via an individual's facial color has been practiced in oriental medicine for thousands of years. This work tackles the issue of quantitative facial color feature extraction for diagnostic purposes. Existing work in this area directly utilizes classic methods found in the standard color analysis area. We believe that these standard chromatic methods are not the most suitable for describing facial colors. Hence, we propose a color extraction method specially designed for facial diagnosis. The main contribution of this work is to define the facial base colors and to present six non-base colors (centroid colors) to represent the facial color space. First, a facial color gamut in the CIEx-y chromatic diagram is formed. Next, an area composed of base colors is defined within the color gamut. Afterwards, some clusters are located outside the base colors area. Finally, six centroids are selected to form a set of components to describe the facial color features. Disease detection is performed to compare the performance of the proposed and existing methods. Overall, the experimental results show that the proposed method outperforms the existing methods, which verifies its validity and effectiveness.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128785447","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 : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7925139
M. Shafiq, Xiangzhan Yu, A. Laghari, Lu Yao, N. K. Karn, Foudil Abdessamia
Network Traffic Classification is a central topic nowadays in the field of computer science. It is a very essential task for internet service providers (ISPs) to know which types of network applications flow in a network. Network Traffic Classification is the first step to analyze and identify different types of applications flowing in a network. Through this technique, internet service providers or network operators can manage the overall performance of a network. There are many methods traditional technique to classify internet traffic like Port Based, Pay Load Based and Machine Learning Based technique. The most common technique used these days is Machine Learning (ML) technique. Which is used by many researchers and got very effective accuracy results. In this paper, we discuss network traffic classification techniques step by step and real time internet data set is develop using network traffic capture tool, after that feature extraction tool is use to extract features from the capture traffic and then four machine learning classifiers Support Vector Machine, C4.5 decision tree, Naïve Bays and Bayes Net classifiers are applied. Experimental analysis shows that C4.5 classifiers gives very good accuracy result as compare to other classifies.
{"title":"Network Traffic Classification techniques and comparative analysis using Machine Learning algorithms","authors":"M. Shafiq, Xiangzhan Yu, A. Laghari, Lu Yao, N. K. Karn, Foudil Abdessamia","doi":"10.1109/COMPCOMM.2016.7925139","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7925139","url":null,"abstract":"Network Traffic Classification is a central topic nowadays in the field of computer science. It is a very essential task for internet service providers (ISPs) to know which types of network applications flow in a network. Network Traffic Classification is the first step to analyze and identify different types of applications flowing in a network. Through this technique, internet service providers or network operators can manage the overall performance of a network. There are many methods traditional technique to classify internet traffic like Port Based, Pay Load Based and Machine Learning Based technique. The most common technique used these days is Machine Learning (ML) technique. Which is used by many researchers and got very effective accuracy results. In this paper, we discuss network traffic classification techniques step by step and real time internet data set is develop using network traffic capture tool, after that feature extraction tool is use to extract features from the capture traffic and then four machine learning classifiers Support Vector Machine, C4.5 decision tree, Naïve Bays and Bayes Net classifiers are applied. Experimental analysis shows that C4.5 classifiers gives very good accuracy result as compare to other classifies.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128568906","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}
Each part of smart grid system is supported by communications network. The amount of smart grid data is developing larger and more complex so that the network faces a lot of challenges to acquire stable and efficient communication in smart grid. The application of cognitive radio can effectively alleviate the shortage of spectrum resources in the smart grid communication network. In this paper, the spectrum allocation scheme of matching algorithm is proposed based on channel idle time and users' priority. Firstly, hidden Markov-model (HMM) is established to predict the idle time of channels in spectrum pool. Baum-Welch, which is the HMM training algorithm of the most commonly used, is formulated to train HMM parameter for each channel to get the most suitable HMM. Secondly, the data of smart grid is divided considering real-time priority, making the higher priority second user (SU) can occupy the channel with longer idle time. Finally, the system total throughput is calculated based on the two factors above. Simulation results show that the total throughput is improved effectively employing the matching algorithm and the stability and the reliability of communication network is obtained. The utilization of spectrum resources is also improved in smart grid.
{"title":"Dynamic spectrum allocation algorithm based on matching scheme for smart grid communication network","authors":"Suhong Yang, Jinkuan Wang, Yinghua Han, Xiuli Jiang","doi":"10.1109/COMPCOMM.2016.7925250","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7925250","url":null,"abstract":"Each part of smart grid system is supported by communications network. The amount of smart grid data is developing larger and more complex so that the network faces a lot of challenges to acquire stable and efficient communication in smart grid. The application of cognitive radio can effectively alleviate the shortage of spectrum resources in the smart grid communication network. In this paper, the spectrum allocation scheme of matching algorithm is proposed based on channel idle time and users' priority. Firstly, hidden Markov-model (HMM) is established to predict the idle time of channels in spectrum pool. Baum-Welch, which is the HMM training algorithm of the most commonly used, is formulated to train HMM parameter for each channel to get the most suitable HMM. Secondly, the data of smart grid is divided considering real-time priority, making the higher priority second user (SU) can occupy the channel with longer idle time. Finally, the system total throughput is calculated based on the two factors above. Simulation results show that the total throughput is improved effectively employing the matching algorithm and the stability and the reliability of communication network is obtained. The utilization of spectrum resources is also improved in smart grid.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130314571","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 : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7925122
Bin Xiao, R. Rahmani, Yuhong Li, D. Gillblad, T. Kanter
The IoT paradigm proposes to connect entities intelligently with massive heterogeneous nature, which forms an ocean of devices and data whose complexity and volume are incremental with time. Different from the general big data or IoT, the data-intensive feature of IoT introduces several specific challenges, such as circumstance dynamicity and uncertainties. Hence, intelligence techniques are needed in solving the problems brought by the data intensity. Until recent, there are many different views to handle IoT data and different intelligence enablers for IoT, with different contributions and different targets. However, there are still some issues have not been considered. This paper will provide a fresh survey study on the data-intensive IoT issue. Besides that, we conclude some shadow issues that have not been emphasized, which are interesting for the future. We propose also an extended big data model for intelligent data-intensive IoT to tackle the challenges.
{"title":"Intelligent data-intensive IoT: A survey","authors":"Bin Xiao, R. Rahmani, Yuhong Li, D. Gillblad, T. Kanter","doi":"10.1109/COMPCOMM.2016.7925122","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7925122","url":null,"abstract":"The IoT paradigm proposes to connect entities intelligently with massive heterogeneous nature, which forms an ocean of devices and data whose complexity and volume are incremental with time. Different from the general big data or IoT, the data-intensive feature of IoT introduces several specific challenges, such as circumstance dynamicity and uncertainties. Hence, intelligence techniques are needed in solving the problems brought by the data intensity. Until recent, there are many different views to handle IoT data and different intelligence enablers for IoT, with different contributions and different targets. However, there are still some issues have not been considered. This paper will provide a fresh survey study on the data-intensive IoT issue. Besides that, we conclude some shadow issues that have not been emphasized, which are interesting for the future. We propose also an extended big data model for intelligent data-intensive IoT to tackle the challenges.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129112540","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 : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7924749
B. Wei, Yuan Zhang
No-reference video quality assessment can provide essential information for video service provides to improve user experiences. In this paper, we propose a no-reference video quality assessment method by utilizing the hybrid parameters extracted from compressed video frame. In particular, the proposed method, namely FRAME-FEBP(FRAME-Feature Extraction in Bit stream & Pixel), models the video quality by using both the high-level syntax elements from bit-stream and the statistics calculated on pixels. The experiments show that the proposed method can provide satisfactory results on video quality assessment.
无参考视频质量评估可以为视频服务提供商提供必要的信息，改善用户体验。本文提出了一种利用压缩视频帧中提取的混合参数进行无参考视频质量评估的方法。特别地，所提出的方法，即FRAME-FEBP(FRAME-Feature Extraction In Bit stream & Pixel)，通过使用来自比特流的高级语法元素和在像素上计算的统计量来建模视频质量。实验结果表明，该方法对视频质量的评估效果令人满意。
{"title":"No-reference video quality assessment with frame-level hybrid parameters for mobile video services","authors":"B. Wei, Yuan Zhang","doi":"10.1109/COMPCOMM.2016.7924749","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7924749","url":null,"abstract":"No-reference video quality assessment can provide essential information for video service provides to improve user experiences. In this paper, we propose a no-reference video quality assessment method by utilizing the hybrid parameters extracted from compressed video frame. In particular, the proposed method, namely FRAME-FEBP(FRAME-Feature Extraction in Bit stream & Pixel), models the video quality by using both the high-level syntax elements from bit-stream and the statistics calculated on pixels. The experiments show that the proposed method can provide satisfactory results on video quality assessment.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129300617","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 : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7924659
Wanthanee Prachuabsupakij, Pafan Doungpaisan
the aim of this paper is to improve the effectiveness and efficiency of rule-based learning for predicting student's graduation to help in enhancing the quality of education system by matching two preprocessing methods, which are SMOTE and Releif algorithms. This paper used the real-world dataset, which contains 544 students data, obtained from the registration information system at King Mongkut's University of Technology North Bangkok, Prachinburi Campus, Thailand. This dataset is processed with four rule-based learners (DT, OneR, PART, and DTNB). The experimental results have shown that DTNB is providing improved precision, recall, f-measure, and g-mean compared to other methods. Therefore, DTNB algorithm is used to the significant improvement of the prediction student's graduation. The model obtained from our method is used to plan a program of study that will provide the opportunity to graduate in four years.
{"title":"Matching preprocessing methods for improving the prediction of student's graduation","authors":"Wanthanee Prachuabsupakij, Pafan Doungpaisan","doi":"10.1109/COMPCOMM.2016.7924659","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7924659","url":null,"abstract":"the aim of this paper is to improve the effectiveness and efficiency of rule-based learning for predicting student's graduation to help in enhancing the quality of education system by matching two preprocessing methods, which are SMOTE and Releif algorithms. This paper used the real-world dataset, which contains 544 students data, obtained from the registration information system at King Mongkut's University of Technology North Bangkok, Prachinburi Campus, Thailand. This dataset is processed with four rule-based learners (DT, OneR, PART, and DTNB). The experimental results have shown that DTNB is providing improved precision, recall, f-measure, and g-mean compared to other methods. Therefore, DTNB algorithm is used to the significant improvement of the prediction student's graduation. The model obtained from our method is used to plan a program of study that will provide the opportunity to graduate in four years.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130567102","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}
To address the problems of “bottleneck” of expert system (ES) in acquiring knowledge as well as “match conflict” and “combinational explosion” in expert system inference, base on fundamental principles of Maintainability appraisal of electronic recycling equipment in a type of missile, the diagnostic method is proposed for locating the fault of module unit or key component in various PCB Maintainability appraisal models by embedding SVM into ES inference engine, by which the design incorporates construction of ES inference engine diagnosing the faults with electronic recycling equipment in a type of missile based on SVM, together with the method for realization of SVM inference engine. The experiments prove that this method effectively improves ES fault diagnosis rate and identification ratio.
{"title":"Design and realization of inference engine of fault diagnosis expert system for electronic recycling equipment of missile based on support vector machine","authors":"Xuedong Xue, Fuli Liu, Dongyan Liu, Hong-li Wang, Shuai Zhang","doi":"10.1109/COMPCOMM.2016.7924914","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7924914","url":null,"abstract":"To address the problems of “bottleneck” of expert system (ES) in acquiring knowledge as well as “match conflict” and “combinational explosion” in expert system inference, base on fundamental principles of Maintainability appraisal of electronic recycling equipment in a type of missile, the diagnostic method is proposed for locating the fault of module unit or key component in various PCB Maintainability appraisal models by embedding SVM into ES inference engine, by which the design incorporates construction of ES inference engine diagnosing the faults with electronic recycling equipment in a type of missile based on SVM, together with the method for realization of SVM inference engine. The experiments prove that this method effectively improves ES fault diagnosis rate and identification ratio.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130612804","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 : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7925158
Lei Weimin, Liang Zhaozheng, Zhang Wei, Zhao Guanghe
Biometric authentication technology can provide high strength protection for identity authentication, and also an important guarantee for QoE and credibility. However, due to technical gaps and vacancies, there doesn't exist a suitable system for network conversational class service yet. In this paper, a kind of biometric authentication system model is proposed based on the above service type. The composition and implementation of the model is described in detail, and the similarities and differences of each unit are compared and analyzed. In addition, in order to realize the mutual transmission of the authentication relation, a kind of biometric certificate used in the system is designed, and the management of certificate validity is studied emphatically to adapt to session service. The model is realized by Doubango project based on IMS, and the SIP signaling system has been extended necessarily. This proposed system can add biometric support to network conversational class service, and provide high-strength authentication assurance for it.
{"title":"A model of biometric authentication system for network conversational class service","authors":"Lei Weimin, Liang Zhaozheng, Zhang Wei, Zhao Guanghe","doi":"10.1109/COMPCOMM.2016.7925158","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7925158","url":null,"abstract":"Biometric authentication technology can provide high strength protection for identity authentication, and also an important guarantee for QoE and credibility. However, due to technical gaps and vacancies, there doesn't exist a suitable system for network conversational class service yet. In this paper, a kind of biometric authentication system model is proposed based on the above service type. The composition and implementation of the model is described in detail, and the similarities and differences of each unit are compared and analyzed. In addition, in order to realize the mutual transmission of the authentication relation, a kind of biometric certificate used in the system is designed, and the management of certificate validity is studied emphatically to adapt to session service. The model is realized by Doubango project based on IMS, and the SIP signaling system has been extended necessarily. This proposed system can add biometric support to network conversational class service, and provide high-strength authentication assurance for it.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114230843","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 : 2016-10-01DOI: 10.1109/COMPCOMM.2016.7924963
Jie Sun, Zhimin Liu
Full duplex communication is a new wireless technology which can at most improve the spectrum efficiency twice. In full duplex system, the UEs receiving data may suffer severe interference from the UEs transmitting signals with same subcarrier. In this paper, a K-means clustering algorithm is stated to lower interference between UEs in different groups and a method of resource allocation is proposed to reduce co-channel interference among neighbor users. Simulation results show that with the proposed algorithm the interference between UEs can be restrained effectively and the spectral efficiency of system has been improved significantly.
{"title":"K-means clustering algorithm for full duplex communication","authors":"Jie Sun, Zhimin Liu","doi":"10.1109/COMPCOMM.2016.7924963","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7924963","url":null,"abstract":"Full duplex communication is a new wireless technology which can at most improve the spectrum efficiency twice. In full duplex system, the UEs receiving data may suffer severe interference from the UEs transmitting signals with same subcarrier. In this paper, a K-means clustering algorithm is stated to lower interference between UEs in different groups and a method of resource allocation is proposed to reduce co-channel interference among neighbor users. Simulation results show that with the proposed algorithm the interference between UEs can be restrained effectively and the spectral efficiency of system has been improved significantly.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116189943","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}
soil erosion is one of the serious natural disasters in China. Soil erosion control is the main content of the comprehensive management of the river basin. Soil erosion in humid region is mainly caused by hydraulic erosion. In this paper, Shangri La County is taken as a study area; the 2014 Shangri La County soil erosion amount is calculated by modified soil loss equation (RUSLE). The classification of soil erosion intensity of Shangri La County is analyzed by various factors affecting soil erosion situation.
{"title":"Evaluation of soil erosion in Shangri-La County based on GIS and RS","authors":"Jia Li, Ping Duan, Jinliang Wang, Fei Cun, Xingqi Sun, Lu Xiu","doi":"10.1109/COMPCOMM.2016.7925022","DOIUrl":"https://doi.org/10.1109/COMPCOMM.2016.7925022","url":null,"abstract":"soil erosion is one of the serious natural disasters in China. Soil erosion control is the main content of the comprehensive management of the river basin. Soil erosion in humid region is mainly caused by hydraulic erosion. In this paper, Shangri La County is taken as a study area; the 2014 Shangri La County soil erosion amount is calculated by modified soil loss equation (RUSLE). The classification of soil erosion intensity of Shangri La County is analyzed by various factors affecting soil erosion situation.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"34 21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116214791","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：