数字老年体育服务:体系构建、实践困境与发展对策

为推进我国数字老年体育服务的发展,通过文献资料、逻辑分析对数字老年体育服务进行研究。研究认为:数字老年体育服务体系基本框架包括目标层面、内容层面、技术层面、保障与支撑层面。数字老年体育服务实践困境主要包括生态建设滞后,发展不够均衡;复合型人才缺乏,技术创新不足;多元主体联动不够,信息孤岛问题凸显;“数字难民”问题严重,老年人参与不足;理念变革滞后,制度建设不够完善。要实现数字老年体育服务快速发展,一要构建完善生态系统,推进数字老年体育服务均衡发展;二要加快人才培养,强化技术创新;三要优化合作结构,破解信息孤岛难题;四要提高老年人数字技术应用能力,强化老年人参与;五要加快理念变革,完善相关制度。

猪瘟病毒基因表达水平与同义密码子使用频率的关系

用信息类聚方法研究了猪瘟病毒基因表达水平与同义密码子使用频率的关系 ,求出了猪瘟病毒基因组各同义密码子的相对使用频率 ,得到了作为表征基因表达水平的各类基因的信息熵 ,所得结果与已有的研究结论相符 .本研究表明 :对于猪瘟病毒的单股正链RNA结构 。

Ontology-based similarity measure for text clustering

A method that combines category-based and keyword-based concepts for a better information retrieval system is introduced. To improve document clustering, a document similarity measure based on cosine vector and keywords frequency in documents is proposed, but also with an input ontology. The ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology, and by means of semantic knowledge, the ontology can improve the effects of document similarity measure and feedback of information retrieval systems. Two approaches to evaluating the performance of this similarity measure and the comparison with standard cosine vector similarity measure are also described.

Modeling of the Multi-Target Locating and Tracking in the Field Artillery System

A method for the multi target locating and tracking with the multi sensor in a field artillery system is studied. A general modeling structure of the system is established. Based on concepts of cluster and closed ball, an algorithm is put forward for multi sensor multi target data fusion and an optimal solution for state estimation is presented. The simulation results prove the algorithm works well for the multi stationary target locating and the multi moving target tracking under the condition of the sparse target environment. Therefore, this method can be directly applied to the field artillery C 3I system.

A SPATIAL CLUSTER METHOD SUPPORTED BY GIS FOR URBAN-SUBURBAN-RURAL CLASSIFICATION

This study was undertaken to construct a preliminary spatial analysis method for building an urban-suburban-rural category in the specific sample area of central California and providing distribution characteristics in each category, based on which, some further studies such as regional manners of residential wood burning emission (PM2.5, the term used for a mixture of solid particles and liquid droplets found in the air, refers to particulate matter that is 2.5 mu m or smaller in size) could be carried out for the project of residential wood combustion. Demographic and infrastructure data with spatial characteristics were processed by integrating both Geographic Information System (GIS) and statistics method (Cluster Analysis), and then output to a category map as the result. It approached the quantitative and multi-variables description on the major characteristics variations among the urban, suburban and rural; and perfected the TIGER's urban-rural classification scheme by adding suburban category. Based on the free public GIS data, the spatial analysis method provides an easy and ideal tool for geographic researchers, environmental planners, urban/regional planners and administrators to delineate different categories of regional function on the specific locations and dig out spatial distribution information they wanted. Furthermore, it allows for future adjustment on some parameters as the spatial analysis method is implemented in the different regions or various eco-social models.

DCAD:a Dual Clustering Algorithm for Distributed Spatial Databases

Spatial objects have two types of attributes： geometrical attributes and non-geometrical attributes, which belong to two different attribute domains （geometrical and non-geometrical domains）. Although geometrically scattered in a geometrical domain, spatial objects may be similar to each other in a non-geometrical domain. Most existing clustering algorithms group spatial datasets into different compact regions in a geometrical domain without considering the aspect of a non-geometrical domain. However, many application scenarios require clustering results in which a cluster has not only high proximity in a geometrical domain, but also high similarity in a non-geometrical domain. This means constraints are imposed on the clustering goal from both geometrical and non-geometrical domains simultaneously. Such a clustering problem is called dual clustering. As distributed clustering applications become more and more popular, it is necessary to tackle the dual clustering problem in distributed databases. The DCAD algorithm is proposed to solve this problem. DCAD consists of two levels of clustering： local clustering and global clustering. First, clustering is conducted at each local site with a local clustering algorithm, and the features of local clusters are extracted clustering is obtained based on those features fective and efficient. Second, local features from each site are sent to a central site where global Experiments on both artificial and real spatial datasets show that DCAD is effective and efficient.

A Modified Genetic Algorithm for Product Family Optimization with Platform Specified by Information Theoretical Approach

Many existing product family design methods assume a given platform, However, it is not an in-tuitive task to select the platform and unique variable within a product family. Meanwhile, most approaches are single-platform methods, in which design variables are either shared across all product variants or not at all. While in multiple-platform design, platform variables can have special value with regard to a subset of product variants within the product family, and offer opportunities for superior overall design. An information theoretical approach incorporating fuzzy clustering and Shannon's entropy was proposed for platform variables selection in multiple-platform product family. A 2-level chromosome genetic algorithm (2LCGA) was proposed and developed for optimizing the corresponding product family in a single stage, simultaneously determining the optimal settings for the product platform and unique variables. The single-stage approach can yield im-provements in the overall performance of the product family compared with two-stage approaches, in which the first stage involves determining the best settings for the platform and values of unique variables are found for each product in the second stage. An example of design of a family of universal motors was used to verify the proposed method.

Quantum Information Splitting of an Arbitrary Three-Qubit State by Using Cluster States and Bell States

A new application of cluster states is investigated for quantum information splitting （QIS） of an arbitrary three-qubit state. In our scheme, a four-qubit cluster state and a Bell state are shared by a sender （Alice）, a controller （Charlie）, and a receiver （Bob）. Both the sender and controller only need to perform Bell-state measurements （BSMs）, the receiver can reconstruct the arbitrary three-qubit state by performing some appropriately unitary transformations on his qubits after he knows the measured results of both the sender and the controller. This QIS scheme is deterministic.

Mining Knowledge from Result Comparison Between Spatial Clustering Themes

This paper introduces some definitions and defines a set of calculating indexes to facilitate the research, and then presents an algorithm to complete the spatial clustering result comparison between different clustering themes. The research shows that some valuable spatial correlation patterns can be further found from the clustering result comparison with multi-themes, based on traditional spatial clustering as the first step. Those patterns can tell us what relations those themes have, and thus will help us have a deeper understanding of the studied spatial entities. An example is also given to demonstrate the principle and process of the method.

Application of Clustering Fusion on Foreign Fibers Measure-Control System

According to the structure characteristics of foreign fibers detection system,the foreign fiber flow flux mathematical model and fiber detection system were designed.The information fusion clustering structure of foreign fiber flow flux was put forward.The data of the pressure difference,pressure,temperature,and density sensor which had impacted on flux were integrated and output by the Adaptive Resonance Theory-2(ART-2)network and BP network to clustering analysis of output space.The clustering control strategy will keep the output flow pressure stable,when the output pressure and temperature change.

Study of Fussy Clustering of Engineering Geological Environment with GIS

Based on previous evaluating methods, a new method which combines GIS with Fussy Clustering algorithm is proposed and applied in evaluating the engineering geological environment of the research area of XuZHou City in this paper. By analyzing the characteristics and formation of engineering geological environment,the major problems are discussed, including stability of basement rock, sandy soil liquefaction and cultural stratum.According to effecting factors of these problems, the stability of every engineering geological problem in the worked area is classified into different classes. Then, the Fussy Clustering method is used in assessing all conditions of engineering geological environment. Finally, the evaluation is fulfilled in the whole studied area. The calculating result shows the method is feasible.

Strengthening the Competitiveness of SMEs by Using the Cluster-Based Approach： A Case Study of the Ratchaburi Orchid Cluster in Thailand

This paper studies the application of the cluster-based approach in the enhancement of the competitiveness of Thailand＇s SME industry. The author had employed a qualitative method through the in-depth interview. The result showed that Ratchaburi orchid cluster in Thailand has employed the concept of the cluster-based approach since they realized that it was useful and could enable them to produce good quality orchids for the international market. The finding also showed how individuals have worked together and helped each other, in order to build a good horizontal network of support and creating competitive advantages. In addition, the research paper related to knowledge management because knowledge management refers to a method for development which requires cluster members to exchange information, interact with each other, sharing and distribute information, create closer business relationship and build mutual benefit. Therefore, the cluster members will help each other to create a culture that values learning through making a commitment and sharing information to strengthen the cluster.

Personalized Metaheuristic Clustering Onto Web Documents

Optimal clustering for the web documents is known to complicated cornbinatorial Optimization problem and it is hard to develop a generally applicable oplimal algorithm. An accelerated simuIated arlneaIing aIgorithm is developed for automatic web document classification. The web document classification problem is addressed as the problem of best describing a match between a web query and a hypothesized web object. The normalized term frequency and inverse document frequency coefficient is used as a measure of the match. Test beds are generated on - line during the search by transforming model web sites. As a result, web sites can be clustered optimally in terms of keyword vectofs of corresponding web documents.

Realization of R-tree for GIS on hybrid clustering algorithm

The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.

Motivations of Individuals Participating in Social Media： A Cultural Perspective

Social media is an information technology that allows users to communicate and share information. With steadily rising number of users across the globe, individuals participate in various activities, like connecting with friends and community members, sharing information, posting political messages, disaster recovery activities, reading daily news, learning, and entertainment, each driven by different sets of motivations. Culture has an influence on the kind of motivation―pro-social and personal needs oriented―that drives social media usage by individuals. Using Hofstede’s （1984b） cultural dimensions, the paper suggests that each of the dimensions will have influences on the social media behaviors differently. Such a cultural perspective helps future social media users to plan the kind of activity and information sharing based on the kind of motivation driving the target audience and the platform providers to design and market accordingly.

Research on Parallel K-Medoids algorithm based on MapReduce

In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a parallel algorithm MapReduce programming model based on the research of K-Medoids algorithm. This algorithm increase the computation granularity and reduces the communication cost ratio based on the MapReduce model. The experimental results show that the improved parallel algorithm compared with other algorithms, speedup and operation efficiency is greatly enhanced.

Research on the Applications of Probability Model and Matrix Transformation in Data Analysis and Management under the Environment of Information Time

In this paper, we research the probability theory and matrix transformation based technique to manage the data for processing and analysis. Clustering analysis research has a long history, over the decades, the importance and the cross characteristics with other research direction to get the affirmation of the people. The probability theory and linear algebra act as the powerful tool for analyzing and mining data. The experimental result illustrates the effectiveness. In the near future, we plan to conduct more theoretical analysis on the topic.

Research on Application of Data Mining in Virtual Community of Foreign Language Learning

The construction of virtual community in foreign language learning is a comprehensive foreign language learning environment integrated with foreign language vocabulary database construction and vocabulary retrieval, combining the virtual reality technology to construct the language environment of foreign language learning. The virtual community of foreign language leaming can improve the sense of language authenticity in foreign language learning and improve the quality of foreign language teaching. A method of building a virtual community for foreign language learning is proposed based on data mining technology, data acquisition and feature preprocessing model for building semantic vocabulary of foreign language learning is constructed, the linguistic environment characteristics of the semantic vocabulary data of foreign language learning is analyzed, and the semantic noumenon structure model is obtained. Fuzzy clustering method is used for vocabulary clustering and comprehensive retrieval in the virtual community of foreign language learning, the performance of vocabulary classification in foreign language learning is improved, the adaptive semantic information fusion method is used to realize the vocabulary data mining in the virtual community of foreign language learning, information retrieval and access scheduling for virtual communities in foreign language learning are realized based on data mining results. The simulation results show that the accuracy of foreign language vocabulary retrieval is good, improve the efficiency of foreign language learning.