Yue Zhang, R. Tian, Xiaoye Dai, Yuezheng Ma, Hui Li, Lin Shi
ORC (Organic Rankine Cycle) is a promising way to efficiently utilize renewable energy and waste heat. This paper focuses on CHF (Critical Heat Flux) causing sharp increase of wall temperature in vapor generator which should be carefully avoided due to its negative effects of heat transfer deterioration and instability of working fluids, aiming to provide guidance for vapor generator's operation and cycle design of ORC system. Experiments were conducted in a 10.3 mm horizontal smooth tube covering a wide pressure range of 0.61 to 0.97 Pc. The occurrence of CHF at bottom wall is found to be the mechanism leading to sharp increase of wall temperature. Pressure is a significant factor changing the CHF type from dryout type to DNB type, which makes near-critical region with higher pressures more sensitive in triggering of CHF. For near-critical region which has not been well studied in existing literature, experimental results showing CHF values for various conditions are provided showing mass flux is important in enhancing CHF level and compensating for negative impact of increasing pressure, accompanied by a newly proposed correlation for predicting CHF at bottom wall in horizontal tube. The predicting CHF values agree well with experimental results with a mean deviation of 7.3% and prediction accuracy is not sensitive to the change of operating conditions.
{"title":"Experimental Study on Sharp Increase of Wall Temperature in Vapor Generator for Organic Rankine Cycle","authors":"Yue Zhang, R. Tian, Xiaoye Dai, Yuezheng Ma, Hui Li, Lin Shi","doi":"10.1145/3208854.3208884","DOIUrl":"https://doi.org/10.1145/3208854.3208884","url":null,"abstract":"ORC (Organic Rankine Cycle) is a promising way to efficiently utilize renewable energy and waste heat. This paper focuses on CHF (Critical Heat Flux) causing sharp increase of wall temperature in vapor generator which should be carefully avoided due to its negative effects of heat transfer deterioration and instability of working fluids, aiming to provide guidance for vapor generator's operation and cycle design of ORC system. Experiments were conducted in a 10.3 mm horizontal smooth tube covering a wide pressure range of 0.61 to 0.97 Pc. The occurrence of CHF at bottom wall is found to be the mechanism leading to sharp increase of wall temperature. Pressure is a significant factor changing the CHF type from dryout type to DNB type, which makes near-critical region with higher pressures more sensitive in triggering of CHF. For near-critical region which has not been well studied in existing literature, experimental results showing CHF values for various conditions are provided showing mass flux is important in enhancing CHF level and compensating for negative impact of increasing pressure, accompanied by a newly proposed correlation for predicting CHF at bottom wall in horizontal tube. The predicting CHF values agree well with experimental results with a mean deviation of 7.3% and prediction accuracy is not sensitive to the change of operating conditions.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124492099","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}
Peiqi Liu, Kehan Wu, Siyuan Xu, Jintao Wu, Fengxia Liu, D. Hu
The offset angle, which is adjustable, is a key parameter of gas wave refrigerator, affecting refrigeration performance. When the high pressure moist gas injects into the oscillation tube of the refrigerator, the non-equilibrium condensation will occur. Phase transition will impact the wave system in the tube and then change the optimal offset angle of the gas wave refrigerator. In this paper, a 2D model of the non-equilibrium condensation in oscillation tube is established to investigate the condensation influence on the optimal offset angle. The results show that: at constant offset angle, with the increase of rotation speed, refrigeration efficiency raises first and then decreases resulting from wave system difference. It shows optimal offset angle truly exists under every working condition, going for optimal wave system match. Condensation process will cause temperature-jump and condensation compression wave which affects wave system in the tube, so the optimal offset angle changes. Since the final Mach number of shock wave increases linearly with the raise of RH (0~0.8), the optimal offset angle decreases linearly. When RH= 0.8, the optimal offset angle decreases by 7%.
{"title":"Influence of Non-equilibrium Condensation on key Parameter of Gas Wave Refrigerator","authors":"Peiqi Liu, Kehan Wu, Siyuan Xu, Jintao Wu, Fengxia Liu, D. Hu","doi":"10.1145/3208854.3208894","DOIUrl":"https://doi.org/10.1145/3208854.3208894","url":null,"abstract":"The offset angle, which is adjustable, is a key parameter of gas wave refrigerator, affecting refrigeration performance. When the high pressure moist gas injects into the oscillation tube of the refrigerator, the non-equilibrium condensation will occur. Phase transition will impact the wave system in the tube and then change the optimal offset angle of the gas wave refrigerator. In this paper, a 2D model of the non-equilibrium condensation in oscillation tube is established to investigate the condensation influence on the optimal offset angle. The results show that: at constant offset angle, with the increase of rotation speed, refrigeration efficiency raises first and then decreases resulting from wave system difference. It shows optimal offset angle truly exists under every working condition, going for optimal wave system match. Condensation process will cause temperature-jump and condensation compression wave which affects wave system in the tube, so the optimal offset angle changes. Since the final Mach number of shock wave increases linearly with the raise of RH (0~0.8), the optimal offset angle decreases linearly. When RH= 0.8, the optimal offset angle decreases by 7%.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121637175","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 recent years, with the development of remote sensing techniques, image classification based on remote sensing imagery with high spatial resolution has played a significant role. At present, there are mainly two ways to classify the imagery of high resolution: pixel-based method and object-based method. Because of the wide differences of spectral features in pixel-based method, 'salt-and-pepper' effect appears in the classification result, which decreases the accuracy. And the object-based method which is widely used in image classification has a low accuracy of classification about objects with similar spectral features and shape features. Each of the two methods has its advantages and disadvantages. It is generally agreed that object-based classification has an advantage over pixel-based classification. However, the previous study found that the results of object-based classification was deeply influenced by reference sampling method So it is necessary to have a comparison between object and pixel-based method under different reference sampling schemes. In this study, we studied pixel-based method and object-based method, selected samples using 'select samples randomly' method and 'select samples separated by objects' method respectively, and built classification models using SVM and RF classifiers respectively. We compared different classification methods and analyzed the impacts of selection of samples and classifiers on classification results. The research showed that the accuracy of classification depends on the distribution of sample points. When sample points were selected randomly(Rand), object-based method got a higher accuracy; when sample points were selected by reference objects separately(Sep), pixel-based method got a higher accuracy.
{"title":"Comparison of Object- and Pixel-Based High Resolution Image Classification under Different Reference Sampling Schemes","authors":"Dongyi Zhang, Mingli Wang, Y. Ke","doi":"10.1145/3208854.3208899","DOIUrl":"https://doi.org/10.1145/3208854.3208899","url":null,"abstract":"In recent years, with the development of remote sensing techniques, image classification based on remote sensing imagery with high spatial resolution has played a significant role. At present, there are mainly two ways to classify the imagery of high resolution: pixel-based method and object-based method. Because of the wide differences of spectral features in pixel-based method, 'salt-and-pepper' effect appears in the classification result, which decreases the accuracy. And the object-based method which is widely used in image classification has a low accuracy of classification about objects with similar spectral features and shape features. Each of the two methods has its advantages and disadvantages. It is generally agreed that object-based classification has an advantage over pixel-based classification. However, the previous study found that the results of object-based classification was deeply influenced by reference sampling method So it is necessary to have a comparison between object and pixel-based method under different reference sampling schemes. In this study, we studied pixel-based method and object-based method, selected samples using 'select samples randomly' method and 'select samples separated by objects' method respectively, and built classification models using SVM and RF classifiers respectively. We compared different classification methods and analyzed the impacts of selection of samples and classifiers on classification results. The research showed that the accuracy of classification depends on the distribution of sample points. When sample points were selected randomly(Rand), object-based method got a higher accuracy; when sample points were selected by reference objects separately(Sep), pixel-based method got a higher accuracy.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126134019","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 processing mode for the fruit and vegetable wastes lack of scientific and reasonable evaluation system, this paper adopts fuzzy AHP comprehensive evaluation method to establish a scientific and reasonable system, at the same time, the required data is calculated by using Matlab software, inquiry processing mode evaluation model and processing model suitable for fruit and vegetable wastes. The results show that the 1. CR<0.10 evaluation system constructed in this paper, through the consistency test, this paper constructs the evaluation model of fruit and vegetable waste treatment mode of science, reasonable and effective evaluation results; selection order processing mode of 2.4 kinds of vegetable waste is D2>D3>D4>D1, so in the processing mode selection of fruit and vegetable wastes when the priority selection mode of D2 press pretreatment of biogas fermentation and anaerobic (biogas manure resources).
{"title":"Evaluation of the Modes of Fruit and Vegetable Waste Disposal Based on FAHP","authors":"Xinfei Zhang, Chunhong Shi, Jiexin Li","doi":"10.1145/3208854.3208898","DOIUrl":"https://doi.org/10.1145/3208854.3208898","url":null,"abstract":"The processing mode for the fruit and vegetable wastes lack of scientific and reasonable evaluation system, this paper adopts fuzzy AHP comprehensive evaluation method to establish a scientific and reasonable system, at the same time, the required data is calculated by using Matlab software, inquiry processing mode evaluation model and processing model suitable for fruit and vegetable wastes. The results show that the 1. CR<0.10 evaluation system constructed in this paper, through the consistency test, this paper constructs the evaluation model of fruit and vegetable waste treatment mode of science, reasonable and effective evaluation results; selection order processing mode of 2.4 kinds of vegetable waste is D2>D3>D4>D1, so in the processing mode selection of fruit and vegetable wastes when the priority selection mode of D2 press pretreatment of biogas fermentation and anaerobic (biogas manure resources).","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127220344","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}
Qinqin Long, W. Kurth, C. Pradal, Vincent Migault, B. Pallas
Plant scientists use Functional Structural Plant Models (FSPMs) to model plant systems within a limited space-time range. To allow FSPMs to abstract complex plant systems beyond a single model's limitation, an integration that compounds different FSPMs could be a possible solution. However, the integration involves many technical dimensions and a generic software infrastructure for all integration cases is not possible. In this paper, we analyze the requirements of the integration with all the technical dimensions. Instead of an infrastructure, we propose a generic architecture with specific process-related components as a logical level solution by combining an ETL (Extract, Transform and Load) based sub architecture and a C/S (Client/Server) based sub architecture. This allows the integration of different FSP models hosted on the same and different FSP modeling platforms in a flexible way. We demonstrate the usability of the architecture by the implementation of a full infrastructure for the integration of two specific FSPMs, and we illustrate the effectiveness of the infrastructure by several integrative tests.
{"title":"An Architecture for the Integration of Different Functional and Structural Plant Models","authors":"Qinqin Long, W. Kurth, C. Pradal, Vincent Migault, B. Pallas","doi":"10.1145/3208854.3208875","DOIUrl":"https://doi.org/10.1145/3208854.3208875","url":null,"abstract":"Plant scientists use Functional Structural Plant Models (FSPMs) to model plant systems within a limited space-time range. To allow FSPMs to abstract complex plant systems beyond a single model's limitation, an integration that compounds different FSPMs could be a possible solution. However, the integration involves many technical dimensions and a generic software infrastructure for all integration cases is not possible. In this paper, we analyze the requirements of the integration with all the technical dimensions. Instead of an infrastructure, we propose a generic architecture with specific process-related components as a logical level solution by combining an ETL (Extract, Transform and Load) based sub architecture and a C/S (Client/Server) based sub architecture. This allows the integration of different FSP models hosted on the same and different FSP modeling platforms in a flexible way. We demonstrate the usability of the architecture by the implementation of a full infrastructure for the integration of two specific FSPMs, and we illustrate the effectiveness of the infrastructure by several integrative tests.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121573921","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}
Aiming at the problem that the energy consumption of electric vehicle (EV) was quite different under different acceleration curves, using a typical EV as the research object, and the difference of EV energy consumption between acceleration curves with a single acceleration value and multiple acceleration values was studied by mathematical induction. On this basis, this study established acceleration curve optimization model based on acceleration characteristic parameters, and proposed a genetic optimization method for EV acceleration curves to minimize energy consumption per kilometer. The EV acceleration curve was optimized under the constraint of minimizing energy consumption and driving comfort. The optimal acceleration curve with the lowest energy consumption per kilometer was obtained, and its acceleration characteristic parameter was. To validate the reliability of optimization result, the EV test in different acceleration curves was carried out. The results showed that, the optimized acceleration curve with multiple acceleration values was more effective in minimizing EV energy consumption per kilometer than that of a single acceleration value, and for the same duration, the optimized acceleration curve reduced energy consumption per kilometer by up to 2.23%.
{"title":"Research on Acceleration Curve Optimization of Electric Vehicle based on Energy Consumption","authors":"Qin Liu, Lifu Li","doi":"10.1145/3208854.3208890","DOIUrl":"https://doi.org/10.1145/3208854.3208890","url":null,"abstract":"Aiming at the problem that the energy consumption of electric vehicle (EV) was quite different under different acceleration curves, using a typical EV as the research object, and the difference of EV energy consumption between acceleration curves with a single acceleration value and multiple acceleration values was studied by mathematical induction. On this basis, this study established acceleration curve optimization model based on acceleration characteristic parameters, and proposed a genetic optimization method for EV acceleration curves to minimize energy consumption per kilometer. The EV acceleration curve was optimized under the constraint of minimizing energy consumption and driving comfort. The optimal acceleration curve with the lowest energy consumption per kilometer was obtained, and its acceleration characteristic parameter was. To validate the reliability of optimization result, the EV test in different acceleration curves was carried out. The results showed that, the optimized acceleration curve with multiple acceleration values was more effective in minimizing EV energy consumption per kilometer than that of a single acceleration value, and for the same duration, the optimized acceleration curve reduced energy consumption per kilometer by up to 2.23%.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130245341","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}
Yangfan Huang, Qingchen Wu, Guoren Zhu, Yanyun Li, Lin Huang, Xiaosong Zhang, Youping Mao, Ping Gan
The shallow geological exploration is more and more widely applied. Scattered wave is a research method of geological exploration which is more close to the real seismic waves, and NMO is one of the key steps in seismic data processing. But conventional NMO method cannot completely give play to the advantages of the scattered wave. Conventional NMO prone to make seismic waves stretch distortion and destroy the original information of seismic wave data, and then, affects the accuracy of seismic data processing results. So this paper proposes a scattered wave NMO method based on adaptive algorithm. This paper analyzes the propagation characteristics of scattered waves, make full use of the adaptive time delay estimation which does not need the statistical properties of the signal and automatically adjust the system parameters to achieve the optimal characteristics, then obtain time delay information. This method able to take full advantage of the characteristics of scattered wave, effective decrease NMO stretching distortion, improve the resolution ratio of seismic data processing results, and effectively retain amplitude and phase information of seismic wave.
{"title":"Research of Scattered Wave NMO Method Based on Adaptive Algorithm","authors":"Yangfan Huang, Qingchen Wu, Guoren Zhu, Yanyun Li, Lin Huang, Xiaosong Zhang, Youping Mao, Ping Gan","doi":"10.1145/3208854.3208858","DOIUrl":"https://doi.org/10.1145/3208854.3208858","url":null,"abstract":"The shallow geological exploration is more and more widely applied. Scattered wave is a research method of geological exploration which is more close to the real seismic waves, and NMO is one of the key steps in seismic data processing. But conventional NMO method cannot completely give play to the advantages of the scattered wave. Conventional NMO prone to make seismic waves stretch distortion and destroy the original information of seismic wave data, and then, affects the accuracy of seismic data processing results. So this paper proposes a scattered wave NMO method based on adaptive algorithm. This paper analyzes the propagation characteristics of scattered waves, make full use of the adaptive time delay estimation which does not need the statistical properties of the signal and automatically adjust the system parameters to achieve the optimal characteristics, then obtain time delay information. This method able to take full advantage of the characteristics of scattered wave, effective decrease NMO stretching distortion, improve the resolution ratio of seismic data processing results, and effectively retain amplitude and phase information of seismic wave.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133768032","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}
Infrared (IR) and visible (VIS) image fusion techniques can get a new image which can represent the scene exactly, entirely and reliably. Combined the advantages of the two-scale decomposition (TSD) with the characteristic of guided filter, a novel IR and VIS image fusion framework is proposed in this paper. Firstly, both IR and VIS images are decomposed with a two-scale average filter to generate the base layers and detail layers. Second, phase congruency (PC) with guided filtering fusion rule is applied to base layer and the larger Sum Modified Laplacian (SML) with guided filtering fusion rule is applied to detail layer. Finally, the resultant image is reconstructed by adding the base and detail layers. The proposed method not only preserves the details of source IR and VIS images but also suppress the artifacts effectively. Experimental results show that the proposed approach can achieve excellent performance in terms of subjective visual effect and objective assessment for infrared and visible image fusion.
{"title":"Two-scale Image Fusion of Visible and Infrared Images Using Guided Filter","authors":"Xiaobei Wang, Rencan Nie, Xiaopeng Guo","doi":"10.1145/3208854.3208881","DOIUrl":"https://doi.org/10.1145/3208854.3208881","url":null,"abstract":"Infrared (IR) and visible (VIS) image fusion techniques can get a new image which can represent the scene exactly, entirely and reliably. Combined the advantages of the two-scale decomposition (TSD) with the characteristic of guided filter, a novel IR and VIS image fusion framework is proposed in this paper. Firstly, both IR and VIS images are decomposed with a two-scale average filter to generate the base layers and detail layers. Second, phase congruency (PC) with guided filtering fusion rule is applied to base layer and the larger Sum Modified Laplacian (SML) with guided filtering fusion rule is applied to detail layer. Finally, the resultant image is reconstructed by adding the base and detail layers. The proposed method not only preserves the details of source IR and VIS images but also suppress the artifacts effectively. Experimental results show that the proposed approach can achieve excellent performance in terms of subjective visual effect and objective assessment for infrared and visible image fusion.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122342641","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}
We study the problem of multi-focus image fusion. We propose a novel framework via convolutional network modeling, which directly learns a focused score map through source images. Further, the score map will be refined using some simple post-treatment. Finally, a high quality all-in focus image could be generated based on the score map and source images. The benefits of this work are three-fold: first, different from the most previous work which always adopt a manual feature extraction method to accomplish the fusion task, we leverage recent advances in convolutional network, which is a learning representation that can learn useful features automatically for various missions, to model the multi-focus image fusion task. Second, because of the scarcity of the label of nature focus-image, to train the model efficiently, we synthesize sufficient pairs of multi-focus image patches as the training set. Third, the trained model has high capacity that can distinguish which region is focused and which is not in the source images and therefore can produce an accurate score map for the fusion task. Experiments demonstrate that our method not only has a richer detail on the visual quality but also has a superior performance on the objective assessment, compared with those of recent several representative methods.
{"title":"Learning to Fuse Multi-Focus Image via Convolutional Network Modeling","authors":"Xiaopeng Guo, Liye Mei, Rencan Nie","doi":"10.1145/3208854.3208896","DOIUrl":"https://doi.org/10.1145/3208854.3208896","url":null,"abstract":"We study the problem of multi-focus image fusion. We propose a novel framework via convolutional network modeling, which directly learns a focused score map through source images. Further, the score map will be refined using some simple post-treatment. Finally, a high quality all-in focus image could be generated based on the score map and source images. The benefits of this work are three-fold: first, different from the most previous work which always adopt a manual feature extraction method to accomplish the fusion task, we leverage recent advances in convolutional network, which is a learning representation that can learn useful features automatically for various missions, to model the multi-focus image fusion task. Second, because of the scarcity of the label of nature focus-image, to train the model efficiently, we synthesize sufficient pairs of multi-focus image patches as the training set. Third, the trained model has high capacity that can distinguish which region is focused and which is not in the source images and therefore can produce an accurate score map for the fusion task. Experiments demonstrate that our method not only has a richer detail on the visual quality but also has a superior performance on the objective assessment, compared with those of recent several representative methods.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"101-102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121577958","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}
Based on resource constraints and environmental protection requirements, new energy vehicles have become one of the strategic emerging industries. Since 2009, China has introduced a series of policies of new energy vehicle. But when it comes about policy implementation there are many blocking factors. The existence of these obstructive factors has been adversely affected the development of new energy automotive industry, its industrialization and market process slow forward. On the basis of combing the relevant literature, this paper briefly introduces the development process of China's new energy industry policy and analyzes the relevant factors that block its development, including the imperfect development of policy, the blurring of authority, the lack of core technology, the lack of uniform standards, measures are not in place, serious local protectionism, the lack of policy advocacy. The paper put forward the corresponding measures to resolve these problems and hope that can make a contribution to the development of New Energy Vehicle Policy.
{"title":"The Blocking Factors and Solution Countermeasures in Policy Implementation of New Energy Vehicle","authors":"Xu Geng, Huayun Liu","doi":"10.1145/3208854.3208868","DOIUrl":"https://doi.org/10.1145/3208854.3208868","url":null,"abstract":"Based on resource constraints and environmental protection requirements, new energy vehicles have become one of the strategic emerging industries. Since 2009, China has introduced a series of policies of new energy vehicle. But when it comes about policy implementation there are many blocking factors. The existence of these obstructive factors has been adversely affected the development of new energy automotive industry, its industrialization and market process slow forward. On the basis of combing the relevant literature, this paper briefly introduces the development process of China's new energy industry policy and analyzes the relevant factors that block its development, including the imperfect development of policy, the blurring of authority, the lack of core technology, the lack of uniform standards, measures are not in place, serious local protectionism, the lack of policy advocacy. The paper put forward the corresponding measures to resolve these problems and hope that can make a contribution to the development of New Energy Vehicle Policy.","PeriodicalId":365707,"journal":{"name":"IEEA '18","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117071992","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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