As part of the global effort to plant billion trees,an afforestation project is launched in Pakistan in Khyber Pakhtunkhwa(KP)province to conserve existing forests and to increase area under forest cover.The present s...As part of the global effort to plant billion trees,an afforestation project is launched in Pakistan in Khyber Pakhtunkhwa(KP)province to conserve existing forests and to increase area under forest cover.The present study is designed to build a Systems'model by incorporating major activities of the Billion Tree Tsunami Afforestation Project(BTTAP)with special focus on afforestation activities to estimate the growth in forest area of KP.Availability of complete dataset was a challenge.To fix the model,the raw data taken from the project office has been utilized.Planning Commission Form 1-Phase I&II helped us with additional information.We relied on the data available for one and half period of the project as rest of the data is subject to the completion of the project.Our results show that the project target to enhance area under forest differs from the target to afforest area under the project.The system dynamics'model projection shows that the forest area of KP would be 23.59 million hectares at the end of the BTTA project,thus having an increase of 3.29%instead of 2%that has been initially proposed.However,the results show that the progress to meet the target in some afforestation classes is slow as compared to other categories.Farm forestry,plantation on communal lands and owners'plantation need special focus of the authority.Deforestation would affect 0.02 million hectares area of the project.The model under study may be used as a reference model that can be replicated to other areas where billion tree campaigns are going on.展开更多
In a previous paper by the author joint with Baogang XU published in Discrete Math in 2018, we show that every non-planar toroidal graph can be edge partitioned into a planar graph and an outerplanar graph. This edge ...In a previous paper by the author joint with Baogang XU published in Discrete Math in 2018, we show that every non-planar toroidal graph can be edge partitioned into a planar graph and an outerplanar graph. This edge partition then implies some results in thickness and outerthickness of toroidal graphs. In particular, if each planar graph has outerthickness at most 2(conjectured by Chartrand, Geller and Hedetniemi in 1971 and the confirmation of the conjecture was announced by Gon?calves in 2005), then the outerthickness of toroidal graphs is at most 3 which is the best possible due to K7.In this paper we continue to study the edge partition for projective planar graphs and Klein bottle embeddable graphs. We show that(1) every non-planar but projective planar graph can be edge partitioned into a planar graph and a union of caterpillar trees;and(2) every non-planar Klein bottle embeddable graph can be edge partitioned into a planar graph and a subgraph of two vertex amalgamation of a caterpillar tree with a cycle with pendant edges. As consequences,the thinkness of projective planar graphs and Klein bottle embeddabe graphs are at most 2,which are the best possible, and the outerthickness of these graphs are at most 3.展开更多
Frequent Pattern mining plays an essential role in data mining. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especia...Frequent Pattern mining plays an essential role in data mining. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns.In this study, we introduce a novel frequent pattern growth (FP-growth)method, which is efficient and scalable for mining both long and short frequent patterns without candidate generation. And build a new project frequent pattern growth (PFP-tree)algorithm on this study, which not only heirs all the advantages in the FP-growth method, but also avoids it's bottleneck in database size dependence. So increase algorithm's scalability efficiently.展开更多
文摘As part of the global effort to plant billion trees,an afforestation project is launched in Pakistan in Khyber Pakhtunkhwa(KP)province to conserve existing forests and to increase area under forest cover.The present study is designed to build a Systems'model by incorporating major activities of the Billion Tree Tsunami Afforestation Project(BTTAP)with special focus on afforestation activities to estimate the growth in forest area of KP.Availability of complete dataset was a challenge.To fix the model,the raw data taken from the project office has been utilized.Planning Commission Form 1-Phase I&II helped us with additional information.We relied on the data available for one and half period of the project as rest of the data is subject to the completion of the project.Our results show that the project target to enhance area under forest differs from the target to afforest area under the project.The system dynamics'model projection shows that the forest area of KP would be 23.59 million hectares at the end of the BTTA project,thus having an increase of 3.29%instead of 2%that has been initially proposed.However,the results show that the progress to meet the target in some afforestation classes is slow as compared to other categories.Farm forestry,plantation on communal lands and owners'plantation need special focus of the authority.Deforestation would affect 0.02 million hectares area of the project.The model under study may be used as a reference model that can be replicated to other areas where billion tree campaigns are going on.
文摘In a previous paper by the author joint with Baogang XU published in Discrete Math in 2018, we show that every non-planar toroidal graph can be edge partitioned into a planar graph and an outerplanar graph. This edge partition then implies some results in thickness and outerthickness of toroidal graphs. In particular, if each planar graph has outerthickness at most 2(conjectured by Chartrand, Geller and Hedetniemi in 1971 and the confirmation of the conjecture was announced by Gon?calves in 2005), then the outerthickness of toroidal graphs is at most 3 which is the best possible due to K7.In this paper we continue to study the edge partition for projective planar graphs and Klein bottle embeddable graphs. We show that(1) every non-planar but projective planar graph can be edge partitioned into a planar graph and a union of caterpillar trees;and(2) every non-planar Klein bottle embeddable graph can be edge partitioned into a planar graph and a subgraph of two vertex amalgamation of a caterpillar tree with a cycle with pendant edges. As consequences,the thinkness of projective planar graphs and Klein bottle embeddabe graphs are at most 2,which are the best possible, and the outerthickness of these graphs are at most 3.
文摘Frequent Pattern mining plays an essential role in data mining. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns.In this study, we introduce a novel frequent pattern growth (FP-growth)method, which is efficient and scalable for mining both long and short frequent patterns without candidate generation. And build a new project frequent pattern growth (PFP-tree)algorithm on this study, which not only heirs all the advantages in the FP-growth method, but also avoids it's bottleneck in database size dependence. So increase algorithm's scalability efficiently.
