云计算下的多源信息资源云体系及云服务模型研究

针对传统信息服务模式存在信息资源规模单一、虚拟化程度低、自适应程度较差及知识泛化等问题,同时考虑到目前云服务体系中忽略多源信息资源这一重要因素,提出了云计算环境下的多源信息资源云体系及服务模型。首先构建了基于云计算的多源信息资源云体系,对信息资源搜索、查询及匹配等技术进行阐述,进而提出了新的云服务模型——基于云计算的多源信息资源即服务(multi-source information resource as a service,MIRaaS),在此基础上搭建了该模型在商务领域下的应用平台。分析表明,该模型能对多源信息资源进行重构、分析、整合及匹配,并充分考虑用户体验,很好地扩展了云服务的研究范围及应用领域。

云计算下多源信息资源云服务模型可信保障机制的研究

针对云计算环境下多源信息资源云服务模型在复杂异构的云网络下存在安全、容错、监管等可信性问题,以及现存保障机制缺乏普适性和独立性,提出一种能从制度上保证服务监管的第三方可信保障机制。分析比对多种信息资源服务模式,将可信性机理、信誉评估、云端访问加密等技术融合,引入第三方信任平台,设计第三方监管角色,搭建独立于服务过程之外的第三方可信保障机制,并设立访问控制模型保障其自身可信性。通过构建商务领域下的应用示例平台,表明该保障机制能充分考虑云计算环境下多源信息资源服务体系中的共性问题,能面向不同应用领域,适用于各种不同类型信息服务应用,具有一定的普适性。

云计算环境下多源信息资源全同态加密仿真

针对云计算环境下多源信息资源的加密,传统的加密方法采用异或算法完成密钥对称解密,增加数据安全性,存在公钥尺度过大和密文长度较长的缺点,导致加密运行效率低和存储空间大的问题。提出一种具有较短公钥的云计算环境下多源信息资源全同态加密方法。添加一组同余数对感知资源同态加密,在加性融合后的密文数据中提取真实资源,采用中国剩余定理验证资源完整性。将新安全参数融合于完整性验证参数经线性转换,减少公钥元素数量,实现公钥尺寸的改进。实验结果表明,所提方法具有较高的运行效率和较小的密钥及密文长度,能够满足实际云环境下的应用需求。

基于语义关联的多源医学信息资源发现服务系统研究

[目的/意义]将不同系统、不同类型的医学信息资源统一关联起来,挖掘和发现其中的医学信息和知识,为临床医生的临床决策和科学研究提供信息服务。[研究设计/方法]在分析医学信息资源发现服务存在问题的基础上,针对临床医生的信息需求和医学信息资源的特点,构建了包含资源层、资源融合层、资源服务层和医学语义与医学知识库的基于语义关联的多源医学信息资源发现服务系统模型;就中文医学语义映射、语义存储结构、语义采集和基于语义关联的资源发现等系统关键技术进行了研究和设计;从语义解释空间和知识关联进行了实例分析。[结论/发现]该资源发现服务系统模型从语义层次实现了语义关联发现。[创新/价值]将医学语义引入医学信息资源服务系统中,为人口健康信息平台的医疗健康大数据深度挖掘和广泛应用等提供一定借鉴。

云计算中多源信息资源平台兼容性路由算法

提出一种基于动态特征K-Means聚类的云计算中多源信息资源平台兼容性路由算法,构建了云计算环境下的多源信息资源通信模型,进行多源信息资源云分析及模型构建,基于动态特征K-Means聚类进行多源信息资源的平台的兼容性特征值挖掘与匹配。仿真结果表明,采用该算法进行云计算环境下的多源信息资源平台兼容路由设计,能提高了云计算平台资源使用效率,降低了CPU负载,节省了计算开销和通信开销,在云平台资源调度等领域就有较高的应用价值。

多源地理信息资源统一描述信息提取方法探究

当前网络上虽然有很多可用的地理信息资源,但由于多源数据格式不统一等问题,难以很好地进行资源共享。鉴于此,本文先提出一种地理信息资源的统一描述框架,该框架分资源对象层、特征层、关联关系层三个层次,并从基本特征、时空特征、深度特征三个侧面开展描述。随后基于该框架,利用原有描述信息转化和半自动或自动提取两种方式进行信息的提取。并对矢量、遥感影像、图像、音频、视频、文本等常见类型的地理信息资源,分别探讨了适合该类型资源的统一描述信息提取方法,包括深度学习、自然语言处理等热门技术,为多源地理信息资源共享提供了新思路。

教育信息化背景下电路理论课程混合式教学研究

随着时代的发展,教育信息化是高校教育的趋势,结合新时代人才培养的要求,该文提出一种信息化背景下混合式教学的架构,并构建以慕课和SPOC为基础的多源教学资源,通过雨课堂进行实施。结果表明,该方法既可提升学生成绩,同时也可解决大班上课难以管理的问题。

Study on Present Status of Plant Germplasm Resources Conservation and Countermeasures

Plant germplasm resources is the material foundation and key point for agricultural production, crop breeding and bioengineering. China is one of the centers for the origin of the cultivated plants worldwide, as well as one of the countries with most abundant plant resources and the highest biodiversity. Strengthening research in the conservation and utilization of plant germplasm resources is of significant value and importance. In this study, the present status of conservation, utilization, and existing problems of plant germplasm resources in China and around the world were reviewed; further, through analyzing measures taken by global countries for plant germplasm resources protection, countermeasures for plant germplasm resources conservation in China were also presented from three aspects, namely, collection and conservation, information network construction and national legislation and policies.

Simultaneously Designing and Targeting for Networks with Multiple Resources of Different Qualities

This paper presents a new design procedure for the networks with multiple resources, such as hydrogen and water, of different qualities. The minimum consumption targets of the resources and pinch-causing sources can be identified as well during design. The objective of this work is to reduce the consumption of the resources with higher quality due to their higher cost. A few examples are investigated to show the proposed method. For a net-work of single resource with single contaminant, there is often only one pinch point for the resource. On the other hand, for a network of multiple resources with single contaminant, there might be a few different pinch points. Each resource might have its own pinch point, if its amount is sufficient. The contaminant concentration of the pinch-causing source for a resource with lower concentration will be below that of the higher-concentration resource(s).

Basin structure and multiresource potential based on high-precision airborne gravity and magnetic data

In this paper,we use high-precision airborne gravity and magnetic data to study the geophysical characteristics of the western slope of the Songliao Basin and its adjacent areas and evaluate the resource potential.We performed an in-depth analysis of three aspects of the basin characteristics:the characteristics of residual strata,the development characteristics of faults,and the distribution characteristics of magmatic rocks.Next,we analyzed the forming background of organic(oil and gas)resources and inorganic(uranium ore and hot dry rock)resources.The results showed that the new Upper Paleozoic strata have significant differences in different regions of the study area(with a thickness of 0–8000 m),mainly distributed in the eastern and northern regions but absent in the middle eastern and western regions.Furthermore,the thickness and depth of the Mesozoic layer varied between the eastern and western regions;it was thicker and deeper in the middle eastern region but thinner and shallower in the western region,and it is absent in most western regions.The main faults in the region are in the north–northeast(NNE)direction.Faults in the NE–NNE and NW directions jointly controlled the morphology of the secondary structural units.Magmatic rocks are relatively developed in the middle and eastern parts of the region.Most magmatic rocks are distributed along the faults and their sides,clearly reflecting the control of the faults on magmatic activities.The western slope of the Songliao basin and its surroundings have a favorable geological setting for the accumulation(mineralization)of oil,gas,shale oil,hot dry rock,and uranium ore.It is conducive to oil and gas exploration of deep new strata and collaborative exploration of multiple resources.

Multi-objective optimization of process based on resource capability

To improve the practicability, suitability and accuracy of the trade-off among time, cost and quality of a process, a method based on resource capability is introduced. Through analyzing the relationship between an activity and its’ supporting resource, the model trades off the time, cost and quality by changing intensity of labor or changing the types of supporting resource or units of labor of resource in a certain time respectively according to the different types of its’ supporting resources. Through contrasting this method with the model of unit time cost corresponding to different quality levels and inter-related linear programming model of time, cost and quality for process optimizing, it is shown that this model does not only cover the above two models but also can describe some conditions the above two models can not express. The method supports to select different function to optimize a process according to different types of its supporting resource.

产业信息云服务模型研究

文章介绍了一种产业信息服务云服务模型,以及通过该模式建立的信息服务平台的总体结构,并对信息服务领域云服务模式进行了探讨。

Efficient Task Scheduling for Many Task Computing with Resource Attribute Selection

Many Task Computing(MTC)is a new class of computing paradigm in which the aggregate number of tasks,quantity of computing,and volumes of data may be extremely large.With the advent of Cloud computing and big data era,scheduling and executing large-scale computing tasks efficiently and allocating resources to tasks reasonably are becoming a quite challenging problem.To improve both task execution and resource utilization efficiency,we present a task scheduling algorithm with resource attribute selection,which can select the optimal node to execute a task according to its resource requirements and the fitness between the resource node and the task.Experiment results show that there is significant improvement in execution throughput and resource utilization compared with the other three algorithms and four scheduling frameworks.In the scheduling algorithm comparison,the throughput is 77%higher than Min-Min algorithm and the resource utilization can reach 91%.In the scheduling framework comparison,the throughput(with work-stealing)is at least 30%higher than the other frameworks and the resource utilization reaches 94%.The scheduling algorithm can make a good model for practical MTC applications.

Resource Intensity Aware Job Scheduling in A Distributed Cloud

A Dominant Resource Fairness （DRF） based scheme for job scheduling in distributed cloud computing systems which was modeled as multi-job scheduling and multi-resource allocation coupling problem is proposed, where the resource pool is constructed from a large number of distributed heterogeneous servers, representing different points in the configuration space of resources such as processing, memory, storage and bandwidth. By introducing dominant resource share of jobs and virtual machines, the multi-job scheduling and multi-resource allocation joint mechanism significantly improves the cloud system＇s resource utilization, yet with a substantial reduction of job completion times. We show through experiments and case studies the superior performance of the algorithms in practice.

Design and Implementation of the Platform for Multimedia Resource Sharing based on Cloud Technology

This paper first reviews the current state of multimedia teaching resource sharing in China as well as the problems encountered. It then proceeds to the focus that a good way out for the dilemma is to design a platform of multimedia teaching resource sharing based on cloud service concept.