[ Objective] The aim of this study was to provide a theoretical basis for breeding selection, matching parents and the identification of traits during early period. [ Method ] With Shanli （ Pyrus ussuriensis Maxim） ...[ Objective] The aim of this study was to provide a theoretical basis for breeding selection, matching parents and the identification of traits during early period. [ Method ] With Shanli （ Pyrus ussuriensis Maxim） , S2 × Shanli （vigorous）, S2 x ShanU （dwarfing）, S2, super-dwarfing germplasm as the matedais, the dwarfing traits of each germplasm were identified by indices including leaf stomata density, branch-cortex ratio, leaf thickness, palisade tissue thickness, paisade-spongy ratio and vessel density. [Result] Among five kinds of pear germplasms, Shanli with strong growth potential had the smallest branch-cortex ratio, leaf thickness, palisade tissue thickness and palisade-spengy ratio, but the largest stomata density and vessel density. On the contrary, super-dwarfing germplasm with weak growth potential had the largest branch-cortex ratio, leaf thickness, palisade tissue thickness and palisade-spongy ratio, but the smallest stomata density and vessel density. There was a difference in stomata density, branch-cortex ratio, leaf thickness, palisade tissue thickness, palisade-spongy ratio and vessel density for every germplasm. [ Conclusion] Stomata density, branch-cortex ratio, leaf thickness, palisade tissue thickness, palisade-spongy ratio and vessel density can be used as indices of identification for pear growth potential in early period.展开更多
Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation pe...Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.展开更多
A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information ...A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.展开更多
As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in effic...As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection(SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.展开更多
In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criti...In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criticalobjectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. Theproposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH)election, pre-selection, and task set selectionmechanisms, where the latter two kinds of selections forma two-layerselection mechanism. The CH election innovatively introduces the movement trend of the target and establishesa scoring mechanism to determine the optimal CH, which can delay the CH rotation and thus reduce energyconsumption. The pre-selection mechanism adaptively filters out suitable nodes as the candidate task set to applyfor tracking tasks, which can reduce the application consumption and the overhead of the following task setselection. Finally, the task node selection is mathematically transformed into an optimization problem and thegenetic algorithm is adopted to form a final task set in the task set selection mechanism. Simulation results showthat HMNCS outperforms other compared mechanisms in the tracking accuracy and the network lifetime.展开更多
基金Supported by National Natural Science Foundation(3056009130960231)~~
文摘[ Objective] The aim of this study was to provide a theoretical basis for breeding selection, matching parents and the identification of traits during early period. [ Method ] With Shanli （ Pyrus ussuriensis Maxim） , S2 × Shanli （vigorous）, S2 x ShanU （dwarfing）, S2, super-dwarfing germplasm as the matedais, the dwarfing traits of each germplasm were identified by indices including leaf stomata density, branch-cortex ratio, leaf thickness, palisade tissue thickness, paisade-spongy ratio and vessel density. [Result] Among five kinds of pear germplasms, Shanli with strong growth potential had the smallest branch-cortex ratio, leaf thickness, palisade tissue thickness and palisade-spengy ratio, but the largest stomata density and vessel density. On the contrary, super-dwarfing germplasm with weak growth potential had the largest branch-cortex ratio, leaf thickness, palisade tissue thickness and palisade-spongy ratio, but the smallest stomata density and vessel density. There was a difference in stomata density, branch-cortex ratio, leaf thickness, palisade tissue thickness, palisade-spongy ratio and vessel density for every germplasm. [ Conclusion] Stomata density, branch-cortex ratio, leaf thickness, palisade tissue thickness, palisade-spongy ratio and vessel density can be used as indices of identification for pear growth potential in early period.
基金This research was supported in part by the National Key Research and Development Program of China under Grant 2022YFB3305303in part by the National Natural Science Foundations of China(NSFC)under Grant 62106055+1 种基金in part by the Guangdong Natural Science Foundation under Grant 2022A1515011825in part by the Guangzhou Science and Technology Planning Project under Grants 2023A04J0388 and 2023A03J0662.
文摘Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.
基金Project(D101106049710005) supported by the Beijing Science Foundation Program,ChinaProject(61104164) supported by the National Natural Science Foundation,China
文摘A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.
基金the Project of National Natural Science Foundation of China (Grant No. 61471395, No. 61301161, and No. 61501510)partly supported by Natural Science Foundation of Jiangsu Province (Grant No. BK20161125 and No. BK20150717)
文摘As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection(SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.
基金the Project Program of Science and Technology on Micro-System Laboratory,No.6142804220101.
文摘In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criticalobjectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. Theproposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH)election, pre-selection, and task set selectionmechanisms, where the latter two kinds of selections forma two-layerselection mechanism. The CH election innovatively introduces the movement trend of the target and establishesa scoring mechanism to determine the optimal CH, which can delay the CH rotation and thus reduce energyconsumption. The pre-selection mechanism adaptively filters out suitable nodes as the candidate task set to applyfor tracking tasks, which can reduce the application consumption and the overhead of the following task setselection. Finally, the task node selection is mathematically transformed into an optimization problem and thegenetic algorithm is adopted to form a final task set in the task set selection mechanism. Simulation results showthat HMNCS outperforms other compared mechanisms in the tracking accuracy and the network lifetime.
