In order to explore the spatial pattern and characteristics of surface information in Erhai Lake basin in Dali city, by using the Landsat 5 and Landsat 8 remote sensing images of which in 2005, 2008, 2011, 2014 and 2017, the surface information of the bare land, vegetation, water body and impervious surface in Erhai Lake basin were extracted based on the Normalized Difference Soil Index (NDSI), the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI) and the Normalized Difference Impervious Surface Index (NDISI). By analyzing the extracted information, the spatial distribution characteristics of the main surface objects were explored and the impacts of which on the ecological environment were studied. This study indicated that the area of the impervious surface in Erhai Lake basin was increasing year by year, but the water quality there was decreasing in recent years. The comprehensive use of GIS, RS and statistical analysis method is the main innovation of this research, and the results can provide reference information for urban planning management and river basin environmental management in Erhai Lake Basin.
{"title":"Analysis of Surface Information Extraction of Erhai Lake Basin in Dali City Based on Remote Sensing Technology, 2005 - 2017","authors":"Quanli Xu, Chao Guo, Wen Dong","doi":"10.1145/3144789.3144819","DOIUrl":"https://doi.org/10.1145/3144789.3144819","url":null,"abstract":"In order to explore the spatial pattern and characteristics of surface information in Erhai Lake basin in Dali city, by using the Landsat 5 and Landsat 8 remote sensing images of which in 2005, 2008, 2011, 2014 and 2017, the surface information of the bare land, vegetation, water body and impervious surface in Erhai Lake basin were extracted based on the Normalized Difference Soil Index (NDSI), the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI) and the Normalized Difference Impervious Surface Index (NDISI). By analyzing the extracted information, the spatial distribution characteristics of the main surface objects were explored and the impacts of which on the ecological environment were studied. This study indicated that the area of the impervious surface in Erhai Lake basin was increasing year by year, but the water quality there was decreasing in recent years. The comprehensive use of GIS, RS and statistical analysis method is the main innovation of this research, and the results can provide reference information for urban planning management and river basin environmental management in Erhai Lake Basin.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130911983","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}
The total variation (TV) model is a classical and effective model in image denoising, but the weighted total variation (WTV) model has not attracted much attention. In this paper, we propose a new constrained WTV model for image denoising. A fast denoising dual method for the new constrained WTV model is also proposed. To achieve this task, we combines the well known gradient projection (GP) and the fast gradient projection (FGP) methods on the dual approach for the image denoising problem. Experimental results show that the proposed method outperforms currently known GP andFGP methods, and canbe applicable to both the isotropic and anisotropic WTV functions.
{"title":"An Image Denoising Fast Algorithm for Weighted Total Variation","authors":"Fan Liao, Shuai Shao","doi":"10.1145/3144789.3144809","DOIUrl":"https://doi.org/10.1145/3144789.3144809","url":null,"abstract":"The total variation (TV) model is a classical and effective model in image denoising, but the weighted total variation (WTV) model has not attracted much attention. In this paper, we propose a new constrained WTV model for image denoising. A fast denoising dual method for the new constrained WTV model is also proposed. To achieve this task, we combines the well known gradient projection (GP) and the fast gradient projection (FGP) methods on the dual approach for the image denoising problem. Experimental results show that the proposed method outperforms currently known GP andFGP methods, and canbe applicable to both the isotropic and anisotropic WTV functions.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115305535","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}
The purpose of this study is to analyze the general characteristics of the spatial and temporal changes of vegetation coverage of Midu County in 2013, 2014 and 2015. Based on the Landsat 8 satellite remote sensing image data of Midu County in the three different periods, the variation characteristics of the vegetation coverage in Midu County were studied by using normalized difference vegetation index (NDVI) and the dimidiate pixel model. The changes of the vegetation coverage in Midu County between 2013 and 2014 were as follows: the lowest vegetation coverage and the lower vegetation coverage were increased by 0.753% and 8.442%, and the moderate vegetation coverage, the higher vegetation coverage and the highest vegetation coverage were decreased by 0.528%, 8.564% and 0.071%, respectively. Then the changes of the vegetation coverage in Midu County between 2014 and 2015 were: the lowest vegetation coverage, the lower vegetation coverage and the moderate vegetation coverage were decreased by 1.852%, 13.158% and 6.249%, and the higher vegetation coverage and the highest vegetation coverage were increased by 0.900% and 20.358%, respectively. The vegetation coverage rate above moderate level in Midu County was 85.35% in 2013, 76% in 2014 and 91.17% in 2015. It can be seen that the vegetation coverage of the Midu County were all above intermediate or high level during the study period, so the overall vegetation cover was in good condition. The comprehensive use of GIS, RS and statistical analysis method is the main innovation of this research, and the results can provide valuable reference for the local ecological environmental protection and scientific development.
{"title":"Variation Characteristics Analysis of the Vegetation Coverage in Midu County Based on Landsat 8 Remote Sensing Image","authors":"Wen Dong, Zhou yang","doi":"10.1145/3144789.3144806","DOIUrl":"https://doi.org/10.1145/3144789.3144806","url":null,"abstract":"The purpose of this study is to analyze the general characteristics of the spatial and temporal changes of vegetation coverage of Midu County in 2013, 2014 and 2015. Based on the Landsat 8 satellite remote sensing image data of Midu County in the three different periods, the variation characteristics of the vegetation coverage in Midu County were studied by using normalized difference vegetation index (NDVI) and the dimidiate pixel model. The changes of the vegetation coverage in Midu County between 2013 and 2014 were as follows: the lowest vegetation coverage and the lower vegetation coverage were increased by 0.753% and 8.442%, and the moderate vegetation coverage, the higher vegetation coverage and the highest vegetation coverage were decreased by 0.528%, 8.564% and 0.071%, respectively. Then the changes of the vegetation coverage in Midu County between 2014 and 2015 were: the lowest vegetation coverage, the lower vegetation coverage and the moderate vegetation coverage were decreased by 1.852%, 13.158% and 6.249%, and the higher vegetation coverage and the highest vegetation coverage were increased by 0.900% and 20.358%, respectively. The vegetation coverage rate above moderate level in Midu County was 85.35% in 2013, 76% in 2014 and 91.17% in 2015. It can be seen that the vegetation coverage of the Midu County were all above intermediate or high level during the study period, so the overall vegetation cover was in good condition. The comprehensive use of GIS, RS and statistical analysis method is the main innovation of this research, and the results can provide valuable reference for the local ecological environmental protection and scientific development.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"292 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121481285","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}
Mingzhe Tan, Ce Chi, Jiahao Zhang, S. Zhao, Guangli Li, Shuai Lü
In order to reduce the energy waste in the data center, while taking into account the violation rate of user service level and the resource utilization rate, this paper studies how to adopt effective strategy to get the reasonable suboptimal solution by combining above three indexes. This paper designs a nonlinear energy consumption model based on polynomials and exponents to measure the energy consumption of different deployment schemes. It is the basis of the deployment strategy. At the heart of this paper, the probability transfer function and the fitness function are designed to optimize the ant colony algorithm. Finally a multi-objective optimization ant colony algorithm based on threshold-dependent pheromone updating was proposed. The algorithm is a kind of distributed optimization method, which is beneficial to parallel computation and has a positive feedback mechanism. The optimal solution can be efficiently obtained by continuous updating of pheromone. The experimental results show that the ant colony algorithm of multi-objective virtual machine placement can achieve the optimal trade-off between multiple conflicting targets, so that the system's energy consumption is less, the violation rate of user service level and the resource utilization rate is also small.
{"title":"An Energy-aware Virtual Machine Placement Algorithm in Cloud Data Center","authors":"Mingzhe Tan, Ce Chi, Jiahao Zhang, S. Zhao, Guangli Li, Shuai Lü","doi":"10.1145/3144789.3144792","DOIUrl":"https://doi.org/10.1145/3144789.3144792","url":null,"abstract":"In order to reduce the energy waste in the data center, while taking into account the violation rate of user service level and the resource utilization rate, this paper studies how to adopt effective strategy to get the reasonable suboptimal solution by combining above three indexes. This paper designs a nonlinear energy consumption model based on polynomials and exponents to measure the energy consumption of different deployment schemes. It is the basis of the deployment strategy. At the heart of this paper, the probability transfer function and the fitness function are designed to optimize the ant colony algorithm. Finally a multi-objective optimization ant colony algorithm based on threshold-dependent pheromone updating was proposed. The algorithm is a kind of distributed optimization method, which is beneficial to parallel computation and has a positive feedback mechanism. The optimal solution can be efficiently obtained by continuous updating of pheromone. The experimental results show that the ant colony algorithm of multi-objective virtual machine placement can achieve the optimal trade-off between multiple conflicting targets, so that the system's energy consumption is less, the violation rate of user service level and the resource utilization rate is also small.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125896640","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}
Preferred semantics is one of the most important semantics in abstract argumentation. This paper designed a new algorithm, named ACPE, for computing preferred extensions based on SAT approach. Firstly, Algorithm ACPE searches for admissible extensions by converting admissible semantic into CNF formula and invoking SAT solver to solve this formula. After finding a new admissible extension, ACPE will get a complete extension by a strategy of expanding, after which ACPE adds a constraint formulae to the CNF formulae to avoid any subset of this extension to be found in searching for a new admissible extension. ACPE execute the above procedure repeatedly until it cannot find any admissible extensions by calling SAT solver. At last, ACPE found all maximum complete extensions or, that is to say, preferred extensions. Through theoretical analysis, this paper proved the correctness and completeness of ACPE. To analyze the performance of ACPE, we compared it with other three solvers, Cegartix, ArgSemSAT and CoQuiAAS, ranking the top three fast solver of computing enumeration reasoning problems for preferred semantics in international competition ICCMA'15. The result of experiment shows that the efficiency of ACPE is similar with ArgSemSAT and Cegartix but weaker than CoQuiAAS when solving easy problems; when it comes to hard problem, ACPE is generally better than ArgSemSAT and CoQuiAAS, and better than Cegartix for most instances.
{"title":"A New Method for Computing Preferred Extensions","authors":"Xindi Zhang, Xiaojie Xie, Yancen Pan, Dangdang Niu, Shuai Lü","doi":"10.1145/3144789.3144796","DOIUrl":"https://doi.org/10.1145/3144789.3144796","url":null,"abstract":"Preferred semantics is one of the most important semantics in abstract argumentation. This paper designed a new algorithm, named ACPE, for computing preferred extensions based on SAT approach. Firstly, Algorithm ACPE searches for admissible extensions by converting admissible semantic into CNF formula and invoking SAT solver to solve this formula. After finding a new admissible extension, ACPE will get a complete extension by a strategy of expanding, after which ACPE adds a constraint formulae to the CNF formulae to avoid any subset of this extension to be found in searching for a new admissible extension. ACPE execute the above procedure repeatedly until it cannot find any admissible extensions by calling SAT solver. At last, ACPE found all maximum complete extensions or, that is to say, preferred extensions. Through theoretical analysis, this paper proved the correctness and completeness of ACPE. To analyze the performance of ACPE, we compared it with other three solvers, Cegartix, ArgSemSAT and CoQuiAAS, ranking the top three fast solver of computing enumeration reasoning problems for preferred semantics in international competition ICCMA'15. The result of experiment shows that the efficiency of ACPE is similar with ArgSemSAT and Cegartix but weaker than CoQuiAAS when solving easy problems; when it comes to hard problem, ACPE is generally better than ArgSemSAT and CoQuiAAS, and better than Cegartix for most instances.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133217687","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}
The DSSS signals are estimated to be difficult under low SNR conditions. In this paper, an improved DSSS signal pseudo-code period estimation method is proposed. It is based on the in-depth analysis of time domain autocorrelation estimation method. In this method, the DSSS signals are grouped by the averaging method, and then combined with the time domain autocorrelation estimation method. It reduces the influence of noise on the estimated performance and improve the SNR limit. The simulation results show that the effective estimation of the pseudo-code period is realized when the SNR is -15dB. Compared withthe cepstrum, it improves 7dB.
{"title":"Analysis on an Improved Pseudo-Code Periodic Estimation Method for DSSS Signals","authors":"Feng Chuan, Sui Tao, Zhou Fan","doi":"10.1145/3144789.3144800","DOIUrl":"https://doi.org/10.1145/3144789.3144800","url":null,"abstract":"The DSSS signals are estimated to be difficult under low SNR conditions. In this paper, an improved DSSS signal pseudo-code period estimation method is proposed. It is based on the in-depth analysis of time domain autocorrelation estimation method. In this method, the DSSS signals are grouped by the averaging method, and then combined with the time domain autocorrelation estimation method. It reduces the influence of noise on the estimated performance and improve the SNR limit. The simulation results show that the effective estimation of the pseudo-code period is realized when the SNR is -15dB. Compared withthe cepstrum, it improves 7dB.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130240548","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}
Cloud computing resource has the features of dynamic, heterogeneous, distributed and complexity etc. Meanwhile the numbers of resources and tasks to be scheduled in Cloud are usually variable. This makes the Cloud resource scheduling a complex optimization problem. None of existing Cloud systems is both being an automated scheduling and considering the optimal usage of resources. To address above problems, we propose a Cloud computing resource scheduling strategy using improved Semantic Search Engine (ISSE). SSE is a new type of service search engine developed by Semantic Computing laboratory in University of California, Irvine. It provides Cloud users with a friendly problem-driven interface to automatically schedule resources that would be used to build a solution according to users' requirementsin the aid of semantic information from resources and user requirements. Further we adopt improvedgenetic algorithm (IGA) in SSE to optimize the scheduling so as to obtain the optimal usage of resources. In our proposed IGA there should be a code distant between the selected parents to retain the population diversity and obtain the valid solution. The architecture of our proposed ISSE is presented as well as the process and implementation of IGA. The experiment results show our proposed ISSE is feasible and can reduce about 16% average tasks execution time comparing to the traditional Cloud resource scheduling (TCRS).
{"title":"Cloud Computing Resource Scheduling based on Improved Semantic Search Engine","authors":"Jia Chen, Jiali Xu, Bei Hui","doi":"10.1145/3144789.3144805","DOIUrl":"https://doi.org/10.1145/3144789.3144805","url":null,"abstract":"Cloud computing resource has the features of dynamic, heterogeneous, distributed and complexity etc. Meanwhile the numbers of resources and tasks to be scheduled in Cloud are usually variable. This makes the Cloud resource scheduling a complex optimization problem. None of existing Cloud systems is both being an automated scheduling and considering the optimal usage of resources. To address above problems, we propose a Cloud computing resource scheduling strategy using improved Semantic Search Engine (ISSE). SSE is a new type of service search engine developed by Semantic Computing laboratory in University of California, Irvine. It provides Cloud users with a friendly problem-driven interface to automatically schedule resources that would be used to build a solution according to users' requirementsin the aid of semantic information from resources and user requirements. Further we adopt improvedgenetic algorithm (IGA) in SSE to optimize the scheduling so as to obtain the optimal usage of resources. In our proposed IGA there should be a code distant between the selected parents to retain the population diversity and obtain the valid solution. The architecture of our proposed ISSE is presented as well as the process and implementation of IGA. The experiment results show our proposed ISSE is feasible and can reduce about 16% average tasks execution time comparing to the traditional Cloud resource scheduling (TCRS).","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131365763","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}
Along with the development of the industrialization, the pollution becomes more and more serious. Many cities are often shrouded in a pollution haze, which threatens seriously the health of the people. Therefore, it is very necessary to establish a scientific and effective air quality forecast model. In this paper, an AQI level forecasting model using chi-square test and BP neural network is established. The model is based on the monitoring data of air pollution obtained from Shijiazhuang air quality monitoring stations. Firstly the model uses chi-square test method to determine the influence factors. Secondly it uses these influence factors data to train the neural network. Finally, the test of the forecasting model is evaluated. The results show that: The AQI level forecasting model has higher forecasting accuracy, it improves the effectiveness and practicability, and can provide more reliable decision evidence for environmental protection departments.
{"title":"An AQI Level Forecasting Model Using Chi-square Test and BP Neural Network","authors":"Haiyao Wang, Jingyang Wang, Xiaohong Wang","doi":"10.1145/3144789.3144817","DOIUrl":"https://doi.org/10.1145/3144789.3144817","url":null,"abstract":"Along with the development of the industrialization, the pollution becomes more and more serious. Many cities are often shrouded in a pollution haze, which threatens seriously the health of the people. Therefore, it is very necessary to establish a scientific and effective air quality forecast model. In this paper, an AQI level forecasting model using chi-square test and BP neural network is established. The model is based on the monitoring data of air pollution obtained from Shijiazhuang air quality monitoring stations. Firstly the model uses chi-square test method to determine the influence factors. Secondly it uses these influence factors data to train the neural network. Finally, the test of the forecasting model is evaluated. The results show that: The AQI level forecasting model has higher forecasting accuracy, it improves the effectiveness and practicability, and can provide more reliable decision evidence for environmental protection departments.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115348295","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}
Morphological component analysis (MCA) is a signal analysis method based on sparse model, its core idea is to represent different components of the signal based on morphological difference of the signal's components. It can separate overlapping texture and cartoon image layers by use two adapted dictionaries. MCA performs good in image inpainting, especially for the image scratch repairing, small area filling, and remove small object. In this paper, we proposed a color image inpainting algorithm based on MCA, and applied the proposed algorithm to repair the murals digital image in the Shibaoshan grotto of Jianchuan, Yunnan province. The central idea of the algorithm is converting the color image into the Lab color space, and inpainting the texture and piecewise smooth (cartoon) parts respectively. Meanwhile, our method increases the TV penalty term in the sparse representation of the cartoon parts to reduce the effects of the noise. Finally, the method combines three channels to realize the color image restoration. Experimential results show that the method has good performence on scratches and cracks in the inpainting of digital images of mural paintings.
{"title":"Research on Mural Inpainting Method based on MCA Image Decomposition","authors":"Z. Qiang, Libo He, Yaqiong Chen, Dan Xu","doi":"10.1145/3144789.3144816","DOIUrl":"https://doi.org/10.1145/3144789.3144816","url":null,"abstract":"Morphological component analysis (MCA) is a signal analysis method based on sparse model, its core idea is to represent different components of the signal based on morphological difference of the signal's components. It can separate overlapping texture and cartoon image layers by use two adapted dictionaries. MCA performs good in image inpainting, especially for the image scratch repairing, small area filling, and remove small object. In this paper, we proposed a color image inpainting algorithm based on MCA, and applied the proposed algorithm to repair the murals digital image in the Shibaoshan grotto of Jianchuan, Yunnan province. The central idea of the algorithm is converting the color image into the Lab color space, and inpainting the texture and piecewise smooth (cartoon) parts respectively. Meanwhile, our method increases the TV penalty term in the sparse representation of the cartoon parts to reduce the effects of the noise. Finally, the method combines three channels to realize the color image restoration. Experimential results show that the method has good performence on scratches and cracks in the inpainting of digital images of mural paintings.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115967825","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}
In this paper, an improved Q-algorithm based on Dynamic Framed Slotted Aloha (DFSA) used in EPC Class 1 Generation 2 (C1G2) protocol is proposed. In the proposed anti-collision algorithm, the total number of frames and the unnecessary sending of QueryAdjust commands are reduced in the recognition process by calculating the optimal threshold for adjusting Q. Besides, the identification efficiency and speed are improved by utilizing the Binary Selection (BS) with Collision Processing Threshold (CPT) strategy and Prediction Bit (PB), respectively. Simulation results show that the improved Q-algorithm costs less time slots and the system throughput fluctuates around 47% which is at least 20% higher than EPC C1G2.
{"title":"An improved Q-algorithm based on EPC Class 1 Generation 2 protocol","authors":"Lin Peng, Yanhan Zeng, Hanyu Liu, Hongzhou Tan","doi":"10.1145/3144789.3144798","DOIUrl":"https://doi.org/10.1145/3144789.3144798","url":null,"abstract":"In this paper, an improved Q-algorithm based on Dynamic Framed Slotted Aloha (DFSA) used in EPC Class 1 Generation 2 (C1G2) protocol is proposed. In the proposed anti-collision algorithm, the total number of frames and the unnecessary sending of QueryAdjust commands are reduced in the recognition process by calculating the optimal threshold for adjusting Q. Besides, the identification efficiency and speed are improved by utilizing the Binary Selection (BS) with Collision Processing Threshold (CPT) strategy and Prediction Bit (PB), respectively. Simulation results show that the improved Q-algorithm costs less time slots and the system throughput fluctuates around 47% which is at least 20% higher than EPC C1G2.","PeriodicalId":254163,"journal":{"name":"Proceedings of the 2nd International Conference on Intelligent Information Processing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124773395","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}
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