The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces ...The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update(BDTMCDIncreUpdate),which combines distributed computing,storage technology,and incremental update techniques to provide an efficient and effective means for clustering analysis.Firstly,the original dataset is divided into multiple subblocks,and distributed computing resources are utilized to process the sub-blocks in parallel,enhancing efficiency.Then,initial clustering is performed on each sub-block using tensor-based multi-clustering techniques to obtain preliminary results.When new data arrives,incremental update technology is employed to update the core tensor and factor matrix,ensuring that the clustering model can adapt to changes in data.Finally,by combining the updated core tensor and factor matrix with historical computational results,refined clustering results are obtained,achieving real-time adaptation to dynamic data.Through experimental simulation on the Aminer dataset,the BDTMCDIncreUpdate method has demonstrated outstanding performance in terms of accuracy(ACC)and normalized mutual information(NMI)metrics,achieving an accuracy rate of 90%and an NMI score of 0.85,which outperforms existing methods such as TClusInitUpdate and TKLClusUpdate in most scenarios.Therefore,the BDTMCDIncreUpdate method offers an innovative solution to the field of big data analysis,integrating distributed computing,incremental updates,and tensor-based multi-clustering techniques.It not only improves the efficiency and scalability in processing large-scale high-dimensional datasets but also has been validated for its effectiveness and accuracy through experiments.This method shows great potential in real-world applications where dynamic data growth is common,and it is of significant importance for advancing the development of data analysis technology.展开更多
In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive netwo...In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive networks) are appealing solutions to the mentioned problem when the statistical information of the underlying process is not available or it varies over time. In this paper, our goal is to develop a new incremental least-mean square(LMS) adaptive network that considers the quality of measurements collected by the nodes. Thus, we use an adaptive combination strategy which assigns each node a step size according to its quality of measurement. The adaptive combination strategy improves the robustness of the proposed algorithm to the spatial variations of signal-to-noise ratio(SNR). The performance of our algorithm is more remarkable in inhomogeneous environments when there are some nodes with low SNRs in the network. The simulation results indicate the efficiency of the proposed algorithm.展开更多
Incremental LOD can be transmitted on the network as a stream, then users on the clients can easily catch the skeleton of terrain without downloading all the data from the server. Detailed information in a local part ...Incremental LOD can be transmitted on the network as a stream, then users on the clients can easily catch the skeleton of terrain without downloading all the data from the server. Detailed information in a local part can be added gradually when users zoom it in without redundant data transmission in this procedure. To do this, an incremental LOD method is put forward according to the regular arrangement of grid. This method applies arbitrary sized grid terrains and is not restricted to square ones with a side measuring 2 k + 1 samples. Maximum height errors are recorded when the LOD is preprocessed and it can be visualized with the geometrical Mipmaps to reduce the screen error.展开更多
In this paper,we derive the Symbol Error Probability(SEP)of cooperative systems with incremental relaying and Distributed Relay Selection(DRS).The relays remain idle when the Signal to Noise Ratio(SNR)between the sour...In this paper,we derive the Symbol Error Probability(SEP)of cooperative systems with incremental relaying and Distributed Relay Selection(DRS).The relays remain idle when the Signal to Noise Ratio(SNR)between the source and destination is larger than T.Otherwise,we activate a relay using DRS.Relay nodes transmit only if their SNR is larger than thresholdβ.If the SNRs of more than two relays is larger thanβ,there is a collision and the destination uses only the received signal from the source.If all relays have SNR less thanβ,no relay is chosen.Thresholdβis optimized to yield the lowest SEP at the destination.Our results are compared to centralized relay selection using opportunistic Amplify and Forward(OAF),Partial and Reactive Relay Selection(PRS and RRS).We compare our results to computer simulations for Rayleigh fading channels.展开更多
Big data are always processed repeatedly with small changes, which is a major form of big data processing. The feature of incremental change of big data shows that incremental computing mode can improve the performanc...Big data are always processed repeatedly with small changes, which is a major form of big data processing. The feature of incremental change of big data shows that incremental computing mode can improve the performance greatly. HDFS is a distributed file system on Hadoop which is the most popular platform for big data analytics. And HDFS adopts fixed-size chunking policy, which is inefficient facing incremental computing. Therefore, in this paper, we proposed iHDFS (incremental HDFS), a distributed file system, which can provide basic guarantee for big data parallel processing. The iHDFS is implemented as an extension to HDFS. In iHDFS, Rabin fingerprint algorithm is applied to achieve content defined chunking. This policy make data chunking has much higher stability, and the intermediate processing results can be reused efficiently, so the performance of incremental data processing can be improved significantly. The effectiveness and efficiency of iHDFS have been demonstrated by the experimental results.展开更多
Although multi-stage incremental sheet forming has always been adopted instead of single-stage forming to form parts with a steep wall angle or to achieve a high forming performance, it is largely dependent on empiric...Although multi-stage incremental sheet forming has always been adopted instead of single-stage forming to form parts with a steep wall angle or to achieve a high forming performance, it is largely dependent on empirical designs. In order to research multi-stage forming further, the effect of forming stages(n) and angle interval between the two adjacent stages(Δα) on thickness distribution was investigated. Firstly, a finite element method(FEM) model of multi-stage incremental forming was established and experimentally verified. Then, based on the proposed simulation model, different strategies were adopted to form a frustum of cone with wall angle of 30° to research the thickness distribution of multi-pass forming. It is proved that the minimum thickness increases largely and the variance of sheet thickness decreases significantly as the value of n grows. Further, with the increase of Δα, the minimum thickness increases initially and then decreases, and the optimal thickness distribution is achieved with Δα of 10°.Additionally, a formula is deduced to estimate the sheet thickness after multi-stage forming and proved to be effective. And the simulation results fit well with the experimental results.展开更多
Severe ground-level ozone(O_(3))pollution over major Chinese cities has become one of the most challenging problems,which have deleterious effects on human health and the sustainability of society.This study explored ...Severe ground-level ozone(O_(3))pollution over major Chinese cities has become one of the most challenging problems,which have deleterious effects on human health and the sustainability of society.This study explored the spatiotemporal distribution characteristics of ground-level O_(3) and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021.Then,a high-performance convolutional neural network(CNN)model was established by expanding the moment and the concentration variations to general factors.Finally,the response mechanism of O_(3) to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables.The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern.When the wind direction(WD)ranges from east to southwest and the wind speed(WS)ranges between 2 and 3 m/sec,higher O_(3) concentration prone to occur.At different temperatures(T),the O_(3) concentration showed a trend of first increasing and subsequently decreasing with increasing NO_(2) concentration,peaks at the NO_(2) concentration around 0.02mg/m^(3).The sensitivity of NO_(2) to O_(3) formation is not easily affected by temperature,barometric pressure and dew point temperature.Additionally,there is a minimum IRNO_(2) at each temperature when the NO_(2) concentration is 0.03 mg/m^(3),and this minimum IRNO_(2) decreases with increasing temperature.The study explores the response mechanism of O_(3) with the change of driving variables,which can provide a scientific foundation and methodological support for the targeted management of O_(3) pollution.展开更多
Distributed Integrated Modular Avionics(DIMA)develops from Integrated Modular Avionics(IMA)and realizes distributed integration of multiple sub-function areas.Timetriggered network provides effective support for time ...Distributed Integrated Modular Avionics(DIMA)develops from Integrated Modular Avionics(IMA)and realizes distributed integration of multiple sub-function areas.Timetriggered network provides effective support for time synchronization and information coordination in DIMA systems.However,inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism.To ensure such time determinism and achieve guaranteed real-time performance,system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain.This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication,and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes.Furthermore,incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost.To control such cost,this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible.Finally,two typical cases,including a simple fully connected DIMA system case and an industrial DIMA system case,are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.展开更多
In this paper,the models of increment distributions of stock price are constructed with two approaches. The first approach is based on limit theorems of random summation. The second approach is based on the statistica...In this paper,the models of increment distributions of stock price are constructed with two approaches. The first approach is based on limit theorems of random summation. The second approach is based on the statistical analysis of the increment distribution of the logarithms of stock prices.展开更多
A simple method is proposed, for incremental static analysis of a set of inter-colliding particles, simulating 2D flow. Within each step of proposed algorithm, the particles perform small displacements, proportional t...A simple method is proposed, for incremental static analysis of a set of inter-colliding particles, simulating 2D flow. Within each step of proposed algorithm, the particles perform small displacements, proportional to the out-of-balance forces, acting on them. Numerical experiments show that if the liquid is confined within boundaries of a set of inter-communicating vessels, then the proposed method converges to a final equilibrium state. This incremental static analysis approximates dynamic behavior with strong damping and can provide information, as a first approximation to 2D movement of a liquid. In the initial arrangement of particles, a rhombic element is proposed, which assures satisfactory incompressibility of the fluid. Based on the proposed algorithm, a simple and short computer program (a “pocket” program) has been developed, with only about 120 Fortran instructions. This program is first applied to an amount of liquid, contained in a single vessel. A coarse and refined discretization is tried. In final equilibrium state of liquid, the distribution on hydro-static pressure on vessel boundaries, obtained by proposed computational model, is found in satisfactory approximation with corresponding theoretical data. Then, an opening is formed, at the bottom of a vertical boundary of initial vessel, and the liquid is allowed to flow gradually to an adjacent vessel. Almost whole amount of liquid is transferred, from first to second vessel, except of few drops-particles, which remain, in equilibrium, at the bottom of initial vessel. In the final equilibrium state of liquid, in the second vessel, the free surface level of the liquid confirms that the proposed rhombing element assures a satisfactory incompressibility of the fluid.展开更多
This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor tec...This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.展开更多
In order to protect the property rights and interests of farmers,promote the revitalization and development of rural areas,and provide a reference basis for the reform of marketing rural collective land for developmen...In order to protect the property rights and interests of farmers,promote the revitalization and development of rural areas,and provide a reference basis for the reform of marketing rural collective land for development purposes,this study explores the reasonable distribution proportion of land increment income from marketing rural collective land for development purposes through analytic hierarchy process and Delphi expert scoring method.The results show that there is a positive correlation between land increment income and land grade,that is,the higher the land grade,the higher the increment income,the larger the proportion of increment income to the transaction price.According to the calculation,when marketing rural collective land for development purposes,the reasonable distribution proportion of the land increment income of the government and the village collective is 28.6%and 71.4%,respectively,and the land increment income actually obtained by farmers has been greatly improved compared with the current situation.In practice,this distribution model has universal applicability and long-term mechanism.The reform of marketing also needs to improve the standard of marketing,explore diversified channels to protect interests,and strengthen the construction of rural collective management system.In short,the distribution of land increment income from marketing rural collective land for development purposes should proceed from the perspective of land property rights and the factors affecting the price of collective land for development purposes,in order to build a reasonable income distribution model.展开更多
A pressing technique has become available that might be useful for compressing granular explosives. If the height diameter ratio of the charge is unfavorable,the high quality charge can not be obtained with the common...A pressing technique has become available that might be useful for compressing granular explosives. If the height diameter ratio of the charge is unfavorable,the high quality charge can not be obtained with the common single action pressing. This paper presents incremental pressing technique, which can obtain the charge with higher overall density and more uniform density.展开更多
基金sponsored by the National Natural Science Foundation of China(Nos.61972208,62102194 and 62102196)National Natural Science Foundation of China(Youth Project)(No.62302237)+3 种基金Six Talent Peaks Project of Jiangsu Province(No.RJFW-111),China Postdoctoral Science Foundation Project(No.2018M640509)Postgraduate Research and Practice Innovation Program of Jiangsu Province(Nos.KYCX22_1019,KYCX23_1087,KYCX22_1027,KYCX23_1087,SJCX24_0339 and SJCX24_0346)Innovative Training Program for College Students of Nanjing University of Posts and Telecommunications(No.XZD2019116)Nanjing University of Posts and Telecommunications College Students Innovation Training Program(Nos.XZD2019116,XYB2019331).
文摘The scale and complexity of big data are growing continuously,posing severe challenges to traditional data processing methods,especially in the field of clustering analysis.To address this issue,this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update(BDTMCDIncreUpdate),which combines distributed computing,storage technology,and incremental update techniques to provide an efficient and effective means for clustering analysis.Firstly,the original dataset is divided into multiple subblocks,and distributed computing resources are utilized to process the sub-blocks in parallel,enhancing efficiency.Then,initial clustering is performed on each sub-block using tensor-based multi-clustering techniques to obtain preliminary results.When new data arrives,incremental update technology is employed to update the core tensor and factor matrix,ensuring that the clustering model can adapt to changes in data.Finally,by combining the updated core tensor and factor matrix with historical computational results,refined clustering results are obtained,achieving real-time adaptation to dynamic data.Through experimental simulation on the Aminer dataset,the BDTMCDIncreUpdate method has demonstrated outstanding performance in terms of accuracy(ACC)and normalized mutual information(NMI)metrics,achieving an accuracy rate of 90%and an NMI score of 0.85,which outperforms existing methods such as TClusInitUpdate and TKLClusUpdate in most scenarios.Therefore,the BDTMCDIncreUpdate method offers an innovative solution to the field of big data analysis,integrating distributed computing,incremental updates,and tensor-based multi-clustering techniques.It not only improves the efficiency and scalability in processing large-scale high-dimensional datasets but also has been validated for its effectiveness and accuracy through experiments.This method shows great potential in real-world applications where dynamic data growth is common,and it is of significant importance for advancing the development of data analysis technology.
文摘In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive networks) are appealing solutions to the mentioned problem when the statistical information of the underlying process is not available or it varies over time. In this paper, our goal is to develop a new incremental least-mean square(LMS) adaptive network that considers the quality of measurements collected by the nodes. Thus, we use an adaptive combination strategy which assigns each node a step size according to its quality of measurement. The adaptive combination strategy improves the robustness of the proposed algorithm to the spatial variations of signal-to-noise ratio(SNR). The performance of our algorithm is more remarkable in inhomogeneous environments when there are some nodes with low SNRs in the network. The simulation results indicate the efficiency of the proposed algorithm.
文摘Incremental LOD can be transmitted on the network as a stream, then users on the clients can easily catch the skeleton of terrain without downloading all the data from the server. Detailed information in a local part can be added gradually when users zoom it in without redundant data transmission in this procedure. To do this, an incremental LOD method is put forward according to the regular arrangement of grid. This method applies arbitrary sized grid terrains and is not restricted to square ones with a side measuring 2 k + 1 samples. Maximum height errors are recorded when the LOD is preprocessed and it can be visualized with the geometrical Mipmaps to reduce the screen error.
文摘In this paper,we derive the Symbol Error Probability(SEP)of cooperative systems with incremental relaying and Distributed Relay Selection(DRS).The relays remain idle when the Signal to Noise Ratio(SNR)between the source and destination is larger than T.Otherwise,we activate a relay using DRS.Relay nodes transmit only if their SNR is larger than thresholdβ.If the SNRs of more than two relays is larger thanβ,there is a collision and the destination uses only the received signal from the source.If all relays have SNR less thanβ,no relay is chosen.Thresholdβis optimized to yield the lowest SEP at the destination.Our results are compared to centralized relay selection using opportunistic Amplify and Forward(OAF),Partial and Reactive Relay Selection(PRS and RRS).We compare our results to computer simulations for Rayleigh fading channels.
文摘Big data are always processed repeatedly with small changes, which is a major form of big data processing. The feature of incremental change of big data shows that incremental computing mode can improve the performance greatly. HDFS is a distributed file system on Hadoop which is the most popular platform for big data analytics. And HDFS adopts fixed-size chunking policy, which is inefficient facing incremental computing. Therefore, in this paper, we proposed iHDFS (incremental HDFS), a distributed file system, which can provide basic guarantee for big data parallel processing. The iHDFS is implemented as an extension to HDFS. In iHDFS, Rabin fingerprint algorithm is applied to achieve content defined chunking. This policy make data chunking has much higher stability, and the intermediate processing results can be reused efficiently, so the performance of incremental data processing can be improved significantly. The effectiveness and efficiency of iHDFS have been demonstrated by the experimental results.
基金Project(51005258) supported by the National Natural Science Foundation of ChinaProject(CDJZR12130065) supported by the Fundamental Research Funds for the Central Universities,China
文摘Although multi-stage incremental sheet forming has always been adopted instead of single-stage forming to form parts with a steep wall angle or to achieve a high forming performance, it is largely dependent on empirical designs. In order to research multi-stage forming further, the effect of forming stages(n) and angle interval between the two adjacent stages(Δα) on thickness distribution was investigated. Firstly, a finite element method(FEM) model of multi-stage incremental forming was established and experimentally verified. Then, based on the proposed simulation model, different strategies were adopted to form a frustum of cone with wall angle of 30° to research the thickness distribution of multi-pass forming. It is proved that the minimum thickness increases largely and the variance of sheet thickness decreases significantly as the value of n grows. Further, with the increase of Δα, the minimum thickness increases initially and then decreases, and the optimal thickness distribution is achieved with Δα of 10°.Additionally, a formula is deduced to estimate the sheet thickness after multi-stage forming and proved to be effective. And the simulation results fit well with the experimental results.
基金supported by the National Key Research and Development Program of China (Nos.2022YFC3702000 and 2022YFC3703500)the Key R&D Project of Zhejiang Province (No.2022C03146).
文摘Severe ground-level ozone(O_(3))pollution over major Chinese cities has become one of the most challenging problems,which have deleterious effects on human health and the sustainability of society.This study explored the spatiotemporal distribution characteristics of ground-level O_(3) and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021.Then,a high-performance convolutional neural network(CNN)model was established by expanding the moment and the concentration variations to general factors.Finally,the response mechanism of O_(3) to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables.The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern.When the wind direction(WD)ranges from east to southwest and the wind speed(WS)ranges between 2 and 3 m/sec,higher O_(3) concentration prone to occur.At different temperatures(T),the O_(3) concentration showed a trend of first increasing and subsequently decreasing with increasing NO_(2) concentration,peaks at the NO_(2) concentration around 0.02mg/m^(3).The sensitivity of NO_(2) to O_(3) formation is not easily affected by temperature,barometric pressure and dew point temperature.Additionally,there is a minimum IRNO_(2) at each temperature when the NO_(2) concentration is 0.03 mg/m^(3),and this minimum IRNO_(2) decreases with increasing temperature.The study explores the response mechanism of O_(3) with the change of driving variables,which can provide a scientific foundation and methodological support for the targeted management of O_(3) pollution.
基金co-supported by the National Natural Science Foundation of China(No.71701020)the Defense Research Field Foundation of China(No.61403120404)the Civil Aircraft Airworthiness and Maintenance Key Laboratory Fund of Civil Aviation University of China(No.2017SW02).
文摘Distributed Integrated Modular Avionics(DIMA)develops from Integrated Modular Avionics(IMA)and realizes distributed integration of multiple sub-function areas.Timetriggered network provides effective support for time synchronization and information coordination in DIMA systems.However,inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism.To ensure such time determinism and achieve guaranteed real-time performance,system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain.This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication,and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes.Furthermore,incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost.To control such cost,this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible.Finally,two typical cases,including a simple fully connected DIMA system case and an industrial DIMA system case,are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.
文摘In this paper,the models of increment distributions of stock price are constructed with two approaches. The first approach is based on limit theorems of random summation. The second approach is based on the statistical analysis of the increment distribution of the logarithms of stock prices.
文摘A simple method is proposed, for incremental static analysis of a set of inter-colliding particles, simulating 2D flow. Within each step of proposed algorithm, the particles perform small displacements, proportional to the out-of-balance forces, acting on them. Numerical experiments show that if the liquid is confined within boundaries of a set of inter-communicating vessels, then the proposed method converges to a final equilibrium state. This incremental static analysis approximates dynamic behavior with strong damping and can provide information, as a first approximation to 2D movement of a liquid. In the initial arrangement of particles, a rhombic element is proposed, which assures satisfactory incompressibility of the fluid. Based on the proposed algorithm, a simple and short computer program (a “pocket” program) has been developed, with only about 120 Fortran instructions. This program is first applied to an amount of liquid, contained in a single vessel. A coarse and refined discretization is tried. In final equilibrium state of liquid, the distribution on hydro-static pressure on vessel boundaries, obtained by proposed computational model, is found in satisfactory approximation with corresponding theoretical data. Then, an opening is formed, at the bottom of a vertical boundary of initial vessel, and the liquid is allowed to flow gradually to an adjacent vessel. Almost whole amount of liquid is transferred, from first to second vessel, except of few drops-particles, which remain, in equilibrium, at the bottom of initial vessel. In the final equilibrium state of liquid, in the second vessel, the free surface level of the liquid confirms that the proposed rhombing element assures a satisfactory incompressibility of the fluid.
文摘This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.
基金Supported by Basic Project of Henan Academy of Sciences for Scientific Research and Development(210601043).
文摘In order to protect the property rights and interests of farmers,promote the revitalization and development of rural areas,and provide a reference basis for the reform of marketing rural collective land for development purposes,this study explores the reasonable distribution proportion of land increment income from marketing rural collective land for development purposes through analytic hierarchy process and Delphi expert scoring method.The results show that there is a positive correlation between land increment income and land grade,that is,the higher the land grade,the higher the increment income,the larger the proportion of increment income to the transaction price.According to the calculation,when marketing rural collective land for development purposes,the reasonable distribution proportion of the land increment income of the government and the village collective is 28.6%and 71.4%,respectively,and the land increment income actually obtained by farmers has been greatly improved compared with the current situation.In practice,this distribution model has universal applicability and long-term mechanism.The reform of marketing also needs to improve the standard of marketing,explore diversified channels to protect interests,and strengthen the construction of rural collective management system.In short,the distribution of land increment income from marketing rural collective land for development purposes should proceed from the perspective of land property rights and the factors affecting the price of collective land for development purposes,in order to build a reasonable income distribution model.
文摘A pressing technique has become available that might be useful for compressing granular explosives. If the height diameter ratio of the charge is unfavorable,the high quality charge can not be obtained with the common single action pressing. This paper presents incremental pressing technique, which can obtain the charge with higher overall density and more uniform density.
