检索结果-南通市图书馆

Multi-DAGs Scheduling Integrating with Security and Availability in Cloud Environment

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2015年第4期24卷 709-716页

作者： LIU Yaqiu SHAO Hongrun jing weipeng QIU Zhaowen The College of Information and Computer Engineering Northeast Forestry University Heilongjiang Province Engineering Technology Research Centre for Forestry Ecological Big Data Storage and High Performance (Cloud) Computing

In view of the issue concerns multiple Directed acyclic graphs(DAGs) scheduling in multi-tenant cloud computing environment, a scheduling strategy that integrate security and availability is proposed to satisfy the tenants’ requirements for resource security and availability, as thus it can not only protect the users’ privacy and data security but also advance the success rate. The proposal assesses resource reputation to ensure jobs can be scheduled onto relatively security nodes; during task scheduling, it classifies the DAGs to achieve fairness; in the process of resources allocation, the objective function would maximize the user’s security satisfaction and minimize the deviation of availability; meanwhile, it takes advantage of "time chips" flexibly to promote resource utilization rate; afterwards, we present a Greedy algorithm integrating with security and availability(GISA) to implement the strategy. The experimental results show the correctness and superior of the novel strategy.

关键词： Multi-DAGs scheduling Security Availability Resource utilization

基于Hadoop及出租车历史轨迹的乘客推荐算法

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

计算机工程与应用 2016年第7期52卷 264-270页

作者：景维鹏胡立坤东北林业大学信息与计算机工程学院哈尔滨150040 黑龙江省林业生态大数据存储与高性能(云)计算工程研究中心哈尔滨150040

针对智慧城市中乘客打车策略的推荐算法效率不高的问题,使用古典概率学统计历史轨迹中该时间该路段有空车的天数占数据集总天数比例,作为乘客等到空车概率;使用最小二乘法拟合时间与到达空车数曲线,预测乘客等到空车时间,以提高推荐效... 详细信息

针对智慧城市中乘客打车策略的推荐算法效率不高的问题,使用古典概率学统计历史轨迹中该时间该路段有空车的天数占数据集总天数比例,作为乘客等到空车概率;使用最小二乘法拟合时间与到达空车数曲线,预测乘客等到空车时间,以提高推荐效率。同时,使用Hadoop作为数据存储和计算平台以提高数据处理能力;提出一种基于地图栅格化的路网存储结构来提高搜索地图速度;改进一种基于计算几何的地图匹配算法提高匹配准确率。实验结果显示,空车概率推荐算法正确率约87%,等待时间推荐算法正确率达88.4%,表明挖掘轨迹数据为乘客提供推荐服务的可行性。

关键词： Hadoop 轨迹数据推荐算法乘客推荐服务

A spatio-temporal multi-scale fusion algorithm for pine wood nematode disease tree detection

在线全文

学校读者我要写书评

暂无评论

Journal of Forestry Research 2024年第6期35卷 267-278页

作者： Chao Li Keyi Li Yu Ji Zekun Xu Juntao Gu weipeng jing College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China Heilongjiang Province Cyberspace Research Center Harbin 150090People’s Republic of China

Pine wood nematode infection is a devastating *** aerial vehicle(UAV)remote sensing enables timely and precise ***,UAV aerial images are challenged by small target size and complex sur-face backgrounds which hinder their effectiveness in *** address these challenges,based on the analysis and optimization of UAV remote sensing images,this study developed a spatio-temporal multi-scale fusion algorithm for disease *** multi-head,self-attention mechanism is incorporated to address the issue of excessive features generated by complex surface backgrounds in UAV *** enables adaptive feature control to suppress redundant information and boost the model’s feature extraction *** SPD-Conv module was introduced to address the problem of loss of small target feature information dur-ing feature extraction,enhancing the preservation of key ***,the gather-and-distribute mechanism was implemented to augment the model’s multi-scale feature fusion capacity,preventing the loss of local details during fusion and enriching small target feature *** study established a dataset of pine wood nematode disease in the Huangshan area using DJI(DJ-Innovations)*** results show that the accuracy of the proposed model with spatio-temporal multi-scale fusion reached 78.5%,6.6%higher than that of the benchmark *** upon the timeliness and flexibility of UAV remote sensing,the pro-posed model effectively addressed the challenges of detect-ing small and medium-size targets in complex backgrounds,thereby enhancing the detection efficiency for pine wood nematode *** facilitates early preemptive preser-vation of diseased trees,augments the overall monitoring proficiency of pine wood nematode diseases,and supplies technical aid for proficient monitoring.

关键词： Pine wood nematode disease UAV remote sensing Object detection Deep learning YOLOv8

A NOVEL PFMAC PROTOCOL FOR WIRELESS SENSOR NETWORK BASED ON PREDICTION AND FEEDBACK METHOD

在线全文

学校读者我要写书评

暂无评论

Journal of Electronics(China) 2011年第4期28卷 488-495页

作者： LiuYaqiu Bian Li jing weipeng Zhang Qianlong Information and Computer Engineering College Northeast Forestry University Harbin 150001 China

In view of the problem that existing Media Access Control(MAC) protocols can not pro-vide real-time monitor on network conditions,this paper puts forward a new MAC protocol- Predict and Feedback MAC(PFMAC) which can predict the channel's congestion level *** dominant idea of the new scheme is to record the channel's busy or idle situation in the backoff stage by sending Sensor Nodes(SNs),and according to the congestion level every SN can change the contention window adaptively when send packets successfully to minimize collisions,saving energy and channel *** result of simulation shows that compared with other MAC protocols,the PFMAC protocol can improve network throughput and reduce energy consumption in high speed network en-vironment.

关键词： Media Access Control(MAC) Backoff algorithm Predict and Feedback MAC(PFMAC) Contention window

在线全文

学校读者我要写书评

暂无评论

文本立场检测综述

计算机研究与发展 2021年第11期58卷 2538-2557页

作者：李洋孙宇晴景维鹏东北林业大学信息与计算机工程学院哈尔滨150040

文本立场检测是文本意见挖掘领域的基础性研究,旨在分析文本中对特定目标所表现的立场倾向.随着互联网的飞速发展,用户对于公共事件、消费产品等的讨论文本呈指数级增长,文本立场检测研究对产品营销、舆情决策等具有重要意义.从目标类... 详细信息

文本立场检测是文本意见挖掘领域的基础性研究,旨在分析文本中对特定目标所表现的立场倾向.随着互联网的飞速发展,用户对于公共事件、消费产品等的讨论文本呈指数级增长,文本立场检测研究对产品营销、舆情决策等具有重要意义.从目标类型、文本粒度以及研究方法3个角度对文本立场检测研究工作展开综述.首先,从目标类型角度,围绕单目标、多目标以及跨目标立场检测3个方面梳理了文本立场检测的不同研究任务;从文本粒度角度,对比了句子级、篇章级以及辩论文本立场检测的不同研究场景和方法;从研究方法角度,介绍了基于传统机器学习、主题模型、深度学习以及“2阶段”的方法,并指出各种方法的可取与不足之处.接着,对文本立场检测评测任务以及公开数据资源进行了归纳.最后,立足当前研究形势,总结了文本立场检测研究的应用领域,展望了未来发展趋势以及面临的挑战.

关键词：文本意见挖掘立场检测目标立场

HCS: Expanding H-Code RAID 6 without Recalculating Parity Blocks in Big Data Circumstance

在线全文

学校读者我要写书评

暂无评论

国际计算机前沿大会会议论文集 2015年第1期 20-22页

作者： Shiying Xia Yu Mao Minsheng Tan weipeng jing University of South China HengyangHunanChina Hengyang Normal University HunanChina College of Information and Computer Engineering Northeast Forestry UniversityHarbinChina

This paper introduces a new RAID 6 expanding method HCS, which is facing the circumstance of big data. HCS expands H-Code manner RAID 6. Two key techniques are used to avoid parity blocks’ *** first one is anti-diagonal data blocks’ selection, and the other one is horizontal data migration. These two techniques ensure the data blocks are retained in the same verification zone, that is horizontal verification zone and anti-diagonal verification zone. Experimental results showed that, compared with SDM, which is also a fast expansion method, HCS can reduce 3.6% expansion time and promote 4.62% performance under four traces.

关键词： Big data H-Code RAID expanding Horizontal coding Anti-diagonal parity Horizontal parity

基于自定义RDD的海量遥感图像并行镶嵌方法

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

地球信息科学学报 2017年第10期19卷 1346-1354页

作者：景维鹏霍帅起东北林业大学信息与计算机工程学院哈尔滨150040

图像镶嵌是遥感图像处理中的重要内容,在跨区域遥感图像分析中发挥重要作用。为了解决传统遥感图像并行算法中存在的计算节点利用率低、频繁数据I/O等问题,本文根据Spark分布式内存计算框架,充分利用Spark利于迭代数据处理的优势,提出... 详细信息

图像镶嵌是遥感图像处理中的重要内容,在跨区域遥感图像分析中发挥重要作用。为了解决传统遥感图像并行算法中存在的计算节点利用率低、频繁数据I/O等问题,本文根据Spark分布式内存计算框架,充分利用Spark利于迭代数据处理的优势,提出了一种基于Spark自定义RDD(弹性分布式数据集)的并行镶嵌方法。该方法首先在集群的多个节点上通过相位相关法执行图像重叠区域估计操作,从而提高了图像重叠区域估计的多节点并行计算;然后,通过重写Spark中RDD的compute和get Partitions方法,自定义针对遥感图像处理的RDD,并将图像镶嵌中的重叠区域估计、图像配准和图像融合3个关键步骤作为自定义RDD的Transformation类型的操作算子;最后,通过隐式转换创建自定义RDD,并调用自定义RDD的操作算子实现图像镶嵌的并行处理。实验结果表明,与传统基于MPI的并行镶嵌算法相比,该方法在保证图像镶嵌效果的基础上,能够有效提高大数据量的图像镶嵌效率。

关键词：遥感图像并行镶嵌 Spark 相位相关法自定义RDD

Modeling and Simulation Comparison of Real-time Monitoring of Particleboard Hot-Pressing Thermal Conductivity

在线全文

学校读者我要写书评

暂无评论

Modeling and Simulation Comparison of Real-time Monitoring o...

2010 3rd International Conference on Computer and Electrical Engineering(ICCEE 2010)

作者： Liu Yaqiu Wei Yingying jing weipeng Wu Qu College of Information and Computer Engineering Northeast Forestry University

In this paper we present a new measure method for real-time monitor of thermal conductivity of the hot-pressing process applied to particleboard. In the particleboard hot-pressing process, the monitoring data of thermal conductivity was modeled and forecasted based on BP neural network and ELM algorithm. The trained network can both accurately harmonize different sets of experimental data and precisely predict the dynamic indexes of thermal conductivity. Simulation results show that ELM prediction method not only overcome the shortcoming of the traditional real-time monitoring mechanism in precision but also avoid the problems of depending on a large number of data with high quality in existing BP network learning.

关键词： Particleboard hot-pressing thermal conductivity BP neural network ELM

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

基于对称性区域过滤的显著性区域检测方法

计算机工程 2019年第5期45卷 216-221页

作者：董本志陈迪景维鹏东北林业大学信息与计算机工程学院哈尔滨150040

为获得精确、完整的目标区域分割图,提出一种基于对称性区域过滤的检测方法来进行图像分割。利用改进的简单线性迭代聚类算法将图像分割成若干超像素,并以超像素为节点建立吸收马尔科夫链。计算转移节点到吸收节点的被吸收时间,将其作... 详细信息

为获得精确、完整的目标区域分割图,提出一种基于对称性区域过滤的检测方法来进行图像分割。利用改进的简单线性迭代聚类算法将图像分割成若干超像素,并以超像素为节点建立吸收马尔科夫链。计算转移节点到吸收节点的被吸收时间,将其作为显著值来获取显著图。根据图像目标区域的对称性特征,对显著图进行对称性检测,获取对称轴,通过两侧像素点到对称轴的距离对图像显著值进行区域过滤,从而获得目标图像分割区域。实验结果表明,该方法提取的图像显著目标区域较阈值分割法、最小生成树法和LRR法提取结果更为完整。

关键词：显著性检测超像素吸收马尔科夫链对称性检测图像分割