This paper analyses the research status of sensor networks and several improved LEACH protocols. It is known that there are some shortcomings in current low-energy clustering protocols: the problem of uneven network cluster and unequal energy consumption of each node in the cluster group leads to excessive energy consumption of some nodes, the whole network life cycle is also greatly shortened. This paper proposes a multi-feature fusion energy-saving routing algorithm based on hybrid ant colony algorithm to optimise and upgrade LEACH energy-saving routing model for the internet of things on the basis of LEACH (NPCHS-Leach) to improve the problems of short lifetime and low energy utilisation caused by existing clustering routing protocols, it improves and pro-longs the network life cycle. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments.

In order to improve the computing efficiency of user important data security and virtual machine disk integrity verification in cloud computing model, a secure dynamic update storage strategy based on electronic stream cipher in cloud computing is proposed. Firstly, the cloud service provider introduces the concept of virtualization to maintain the virtualization server, storage, and so on to realize the real-time security migration of the virtual machine. At the same time, a model based on the secure electronic stream cipher is introduced. The encryption/decryption uses the ChaCha20 method to maintain the appropriate security for the user sensitive data in the cloud data, to realize data virtualization and dynamic updating in virtual machine disk. Secondly, a new dynamic version of the Merkle B+Hash tree (DMBHT) is proposed. This method does not require random Oracle signature scheme, while uses q-strong Diffie-Hellman (q-SDH) secure short signature, and uses effective bit rate as pseudo delete code (Tornado-z code) on the leaf level of DBHT, which can effectively keep the integrity and authenticity between the virtual machine disk. Finally, simulation results show that the proposed algorithm can achieve fast update and secure modification, and the effectiveness of the proposed algorithm is verified.

为提高项目调度优化过程的合理性,引入一种新的项目调度优化应对冲突的方法,一旦冲突发生在调度方案中,不是重新定义项目的开始时间,而是对冲突的时间调度表进行状态的迁移,得到另一个可行的调度时间表,实现了算法计算效率的提升。然后,将主动和被动项目调度问题作为单一的综合问题来制定,并利用Markov决策过程对上述项目调度优化问题进行建模,有针对性地设计了一种基于随机图的动态规划求解方法。实验结果显示了所提方法在收敛精度和计算效率上的有效性,并通过甘特图方式对调度方案的合理性进行了论证。

针对现有标注算法精度不高的问题,提出一种基于上下文相关模型的图像语义标注方法.首先,根据语义概念在训练数据集中的共现频率,对每个概念构造马尔科夫随机场图结构;其次,从已标注图像的文本信息出发构建一个非对等模态的概率潜语义分析(PLSA)模型,计算图像和语义概念的联合概率,并将其作为马尔科夫随机场(MRF)中点的观察值.与此同时,基于PLSA设计马尔科夫随机场模型的点势函数和边势函数;最后,通过正则化最大伪似然估计学习MRF的模型参数,利用迭代条件模式进行模型推理,从而获得未知图像的精确化语义标注结果.实验表明,所提出方法的性能明显优于若干经典的自动图像标注方法,而且具有更好的检索性能.

Objective—To find a method of the item bank construction that is more suitable for the actual situation of the colleges and universities through theoretical study and practical verification.Methods—By comparing and analyzing of traditional theory of item bank construction,the construction standards,methods and design ideas of improved item bank were proposed and verified by the actual system.Results—The summary of college item bank construction and the research into algorithm of generating test paper were completed.Conclusion—The uniform standards,construction steps and the technology of generating test paper of an item bank system that are more suitable for universities and colleges were proposed.

Sequential pattern mining is an important data mining problem that can extract frequent subsequences from sequences. However, the times between successive items in a sequence is typically used as user-specified constraints to pre-process the input data or to prune the pattern search space. In either cases, the times cannot be used to identify item intervals of sequential patterns. In this paper, we introduce a form of multi-granularity sequence patterns, which is a sequential pattern where each transition time is annotated with multi-granularity boundary interval and average time derived from the source data rather than the user-predetermined time interval or only a typical time. Then we present a novel algorithm, MG-PrefixSpan, of multiple granularity sequential patterns based on PrefixSpan[, which discovers all such patterns. Empirical evaluation shows that MG-PrefixSpan scales up linearly as the size of database, and has a good scalability with respect to the length of sequence and the size of transaction.

This paper presents a new algorithm for multicast routing optimization on multiple constrained QoS,which is based on the combination of genetic algorithm and ant colony algorithm.The algorithm adopts genetic algorithm to produce the original results,transforms them into the initial pheromones value needed by ant colony algorithm,then uses ant colony algorithm to get the best results.Simulation results show that this algorithm is effective,and it is better than the algorithm in the sixth references.

A novel sharp features extraction method is proposed in this paper. First, we calculate the displacement between the point and its local weighted average position and we label the point with salient this value as the candidate sharp feature points and we estimate the normal direction of those candidate sharp feature points by means of local PCA methods. Then we refine the normal estimated by inferring the orientation of the points near the candidate sharp feature region and bilateral filtering in the normal field of point clouds. At last we project the displacement between point and its local weighted average position along the direction of normal. We use value of this projection as the criteria of whether a point can be labeled as sharp feature. The extracted discrete sharp feature points are represented in the form of piece-wised B-Spline lines. Experiment on both real scanner point clouds and synthesized point clouds show that our method of sharp features extraction are simple to be implemented and efficient for both space and time overhead as well as it robust to the noise, outlier and un even sample witch are inherent in the point clouds.

Sequential pattern mining is an important data mining problem that can extract frequent subsequences from sequences.Although the conventional sequential patterns can only reveal what items are frequent occurring and in what order,they can not reveal how long time the items will occur after the preceding items.In this paper,a new form of multi-granularity sequence patterns are introduced,which is a sequential pattern where each transition time is annotated with multi-granularity boundary interval and average time derived from the source data.Then a model for mining multi-granularity sequence patterns is created and a novel algorithm,called MG-PrefixSpan,of multi-granularity sequential patterns is presented.Empirical evaluation shows that MG-PrefixSpan is efficient.

提出一种将分布式数据库数据映射为符合用户要求的XML文档的描述语言--_R2XL,在此基础上给出基于XML的分布式数据库集成系统,实现分布式数据库的透明访问和联合查询.对该系统中的查询处理、分布式数据库中的数据分片方法及相应的集成策略等关键问题进行了探讨.

.NET Remoting for distributed object provides a basic structure.It uses both flexible and can expand the pipeline to the remote process..NET's fully object semantics.In this paper,securities of real-time analysis system as an example,the use of.NET Remoting technology implementation securities investors stock varieties of online real-time analysis functions,not only through the concept of assembly solved the Windows operating system environment has always existed "DLL hell" problem,improve the entire analysis of system flexibility and scalability,but also through more stringent security design,for further study of China's securities market participants dealer strategy,price formation process to create a good application platform.

In this paper, a novel fuzzy particle swarm optimization (NFPSO), in which inertia weight as well as the learning coefficient can be adaptively adjusted according to the control information translated from the fuzzy logic controller (FLC) during the search process, is presented by introducing a two-input and two-output FLC into the canonical particle swarm optimization (CPSO). The effectiveness of NFPSO proposed in this paper is demonstrated by applying it to three benchmark functions obtained from the literature. The simulation results show that NFPSO outperforms CPSO and other fuzzy PSO versions.

Designing a kind of system that making use of new generation of monolithic and whole calibration,high integration,small volume digital temperature and humidity sensors SHT71 by the MCU control to achieve the collected data of temperature and humidity and display it,then through the wireless sending and receiving to transmit the collected data and remote control the temperature and humidity-conditioning equipment,and coupled with portable and PC operation.This system have the features of small in size,the widespread applicability and user-friendly.

The issue of question comprehension in Chinese question answering system (QAS) is discussed in this paper. The authors study word segmentation,question categorization,Keywords extraction and extension,sentence pattern analysis and shallow semantic parsing. The rules combined the question words with question focus based on heuristic to classify questions are introduced. As a result,a question pattern analysis method named question sentence standard formats and a semantic analysis method based on semantic role labeling are proposed. On the basis of the theory study above,a Chinese QAS prototype based on simple facts was developed using language Visual C++ 6.0. The experiment results show that the methods proposed in this paper improve the performance of Chinese QAS effectively.

Nowadays,alot of important data of application systems are stored in databases.In order to avoid losing or destroying the data,it is significant to strengthen the functions of database's backup and restore.Under VS.NET_2003 and SQL Server 2000 condition,the article implements kinds of database backup and restore manners with C# and SQL-DMO,the ordinary users can operate conveniently the database in browser side.Therefore,it assures the security of database.Finally,the article presents and analyzes some main source codes of the instance.

立体化教学资源建设是实现高校信息化教学的先导。阐述了立体化教学资源的概念、组成、作用,构建了立体化教学资源的建设,并对高校立体化教学资源建设进行了思考。

基于传统的互动式教学方式及多媒体教学方式,构建新的互动式多媒体课堂教学模式,以改变传统教学方式及学习方式,并对该教学模式的特征、教学方法、教学过程的组织形式和教学效果的评价标准等问题进行了系统阐述。

从理论上研究了决策表中决策值细化程度与信息粒度、近似分类的精度及近似分类质量之间的关系,结果表明,决策属性的属性值划分得越细,则该属性的信息粒度、近似分类精度和近似分类质量的值就越小.仿真实验同时证明,在基于决策属性划分之下,对任意一个条件属性集经决策细化后的决策表所对应的信息粒度、近似分类精度和近似分类质量的值,都不大于决策细化前决策表所对应的信息粒度、近似分类精度和近似分类质量的值,这个结果对研究决策表属性约简和决策规则的有效性等问题都有指导作用.