Earticle

With the quickly development of Natural Science Foundation of China (NSFC) foundations, management of mass fund-relevant digital data, such as researchers and institutions, academic achievement, funds and so on, is becoming more and more important for supporting basic scientific research. In this paper, we fully introduce the design and implementation of NSFC cloud platform that will be implemented in the service system of knowledge base. Firstly, the whole cloud platform architecture is presented. Then we introduce the system software and equipment environment of our platform. Lastly, we present the construction of private cloud, network components, storage components, and computing components, respectively, with illustrative figures and tables.

This paper presents an operating and cost optimization model for Micro Grid (MG). This model takes into account emission costs of CO2, SO2 and NOx, together with the operation, maintenance and startup costs. Photovoltaic (PV) arrays, Wind Turbine (WT), Fuel Cell (FC), Micro Turbine (MT) and Diesel Generator (DG) with different capacities are considered in this model. The aim of the optimization is minimizing operation cost according to constraints, supply demand and safety of system. The proposed Bender’s Decomposition (BD) is used to optimize the micro grid operation.

In order to predict network users’ access behavior accurately, this paper proposes a new prediction model based on Web access behavior. To improve prediction performance and reduce the state-space complexity, the model uses hybrid-order Markov chain structure and stores the sequences which share the same prefix. The problems that lower-order models have poor prediction performance and higher-order models result in high state-space complexity are solved in this paper. Simulation results have shown that the prediction model based on Web access behavior can improve the precision and recall to some extent.

In order to solve the efficiency of buffer analysis of line elements, adopt plane graph model and according to the characteristic of simple feature model, making the bounding-edges of the line elements into plane graph model, then According to certain rules to filter the lines of plane graph model to gain the bounding edges of buffer and then gain the results. In this algorithm, firstly, As required, do parallel lines and polylines vertex processing for the line elements extracted from the objects which need buffer analysis , and gain the Intermediate line objects, then Generate line elements of graph model through computing intersecting points and clip lines using static R tree index, Moreover using the multiple programming standard OPENMP, Optimize the parallelism of every step of the vector buffer analysis algorithm, This algorithm can solve buffer efficient of large data and it’s is better than other algorithm in physical problem.

The main problem of wireless sensor network is congestion occur due to buffer-overloading. Due to this issue, the performances of the network such as network throughput and packet loss are affected. To reduce the buffer-overloading from the WSN a comparative study has been done between AODV and QAODV using queue length buffer-overloading equation. In this paper, we proposed QAODV using queue length buffer-overloading equation through which major cause of congestion, buffer-overloading is reduced from the network.

As to the problems that can been solved by genetic algorithm in Big Data, genetic algorithm research has profound significance. To meet the need of social development, many researchers have been doing a lot of work in thought and theory of that and come up with specific thought and theory. In the paper, firstly look up papers about the implementation rationale, model and specific implementation of genetic algorithm in HADOOP. Summarise two implementation models of genetic algorithm in HADOOP, vertical strategy and horizontal strategy. And deeply analyze the two implementation models, their design and implementation. Based on above, come up with improved model of genetic algorithm in HADOOP, its detailed design and general implementation steps. The improved implementation model is tested by test data to verify its correctness and validity. Experimental results prove to be that the improved implementation model of this paper is correct and valid. Finally, the improved implementation model of this paper is applied to solving facility location of emergency system.

With the increase of computer network crimes and the changes of the forms, the work of the network electronic forensics is becoming more and more important, and it is required that the technology of electronic forensics should be adapted to the development of complex network crimes. In this paper, the traditional electronic evidence collection technology and the electronic evidence collection method in recent years are studied, and then the hybrid network electronic evidence collection model based on cloud computing environment is proposed, which can work for electronic forensics in dynamic, fast and real-time ways so as to fight against network crimes more effectively.

Technology and concept of cloud computing have changed the traditional application pattern of computing resources. Here we briefly introduce the concept and typical applications of cloud computing, and put forward the software services based on cloud computing technology in medical informatization and the application of a cloud storage service model. We also discuss the challenges faced in the application of the cloud computing technology during medical informatization.

This work aims to study a variety of distributed power access based on the theory of operation microgrid control. It provided a theoretical reference and reference for the development of micro-engineering application grid technology. In this paper, the risk characteristics of grid operations management side under the background of the smart grid, from project investment, load forecasting, renewable energy power purchase access, economic dispatch, information security, and constructed investment project set risk transfer model, load forecasting risk transfer model, considering the economic dispatch model smart grid element of risk transfer. It takes into account price and load uncertainties purchase risk transfer element optimization model, smart grid information security risk assessment element transfer model to study the dynamics of the smart grid from a risk point of view under the grid-side operational risk management.

Propagation structure has a vital role in designing the Mobile ad-hoc networks (MANETs). Propagation structure is employed for computing signal strength about each data packet at the destination. Propagation Structures in MANETs are characterized into three categories such as Free Space structure, Two-Ray Ground structure and Shadowing structure. Here in this paper, the effect of Two-Ray Ground propagation structure and Shadowing propagation structure on the performance of DSR routing protocol is conferred. Propagation Structure has a great impact on the simulation results. The simulation is accomplished using NS 2 simulator and the various Performance Attributes used for the evaluation of the performance of DSR protocol are Average Delay, Packet Delivery Ratio, Energy Consumption and Throughput.

Label propagation algorithm (LPA algorithm) is gotten widely attention by its simplicity, rapidity and greater effectiveness. Aimed at the problem of label updating process is sensitive to the order of nodes in LPA algorithm, an improved algorithm is proposed in this paper. The algorithm starts from the nodes with maximum degree in the network, according to its neighbor nodes’ community similarity index to decide whether its label setting, and then completes label setting in the first round; On this basis, it continues to carry out the iteration in label propagation algorithm, completes the entire network of community structure detection. The experimental results show that the improved algorithm is slightly better than the original algorithm at running time and number of iterations, has higher robustness, prevents the occurrence of the trivial solution.

Web Map Tile Services (WMTS) have been widely used for quick and convenient sharing of geospatial information. In practice, when streaming requests to servers increase in scale, unacceptable response times and service unavailability might result. To address this scalability problem, we implemented a scalable WMTS framework on a high performance cluster (HPC), enabling the realization of elastic deployment as the client users grow in number. This scalable and high-concurrency WMTS is built totally with open-source software, including Nginx, GeoWebCache, and MongoDB. In this architecture, Nginx acts as a powerful load balancer for routing client requests; GeoWebCache is customized to publish the required WMTS and process client requests; while MongoDB is used to store the large volume of tile images in the HPC. Evaluation experiments were carried out to assess the efficiency and scalability of our WMTS system, using one synthetic workload. Experimental results illustrate that this distributed WMTS framework can achieve about 15% performance improvement when the service nodes are increased with a 0.5~2s reduction in the load time and a 5~10MB increase in network throughput.

Compute Unified Device Architecture (CUDA) is a mature parallel computing architecture, which can significantly accelerate performance of the computation intensive algorithm. In this paper, FastSLAM algorithm based on the probability model is further studied and the resampling algorithm for the path estimation is improved. In the resampling phase, resampling rules are redesigned and the previous data limitations are broken for the purpose of parallelization. We propose the FastSLAM algorithm based on CUDA, which accelerates robot localization and mapping. The experiment results show that FastSLAM_CUDA can achieve a significant speedup over the FastSLAM with many particles.

The whole operation mode and management way of education system is undergoing tremendous changes, and the education management informatization has become a necessary condition for the transition from ‘education management’ to ‘education governance’. In this paper, based on Internet +, using the theories and methods of computer science and other related disciplines, we explore the new concept of education governance based on Internet +, and then we analyze the top-level design idea and design principles of the public cloud platform of education governance, mainly focus on the overall architecture, core modules and big data application architecture of the public cloud platform of education governance. Finally we provide a series of effective recommendations for the implementation of the public cloud platform of education governance.

In deregulated power system with competitive electricity market environment, the provision of strategic bidding option to the market participants and its consequences are open up new challenging tasks to the system operator. The market economic efficiency is mainly dependent on transmission system support. The inability of transmission system support to drive market cleared schedule is known as congestion and which is not desirable. The remedial actions to relieve congestion in the transmission system known as congestion relief approaches and are differ in various markets around the world. The objective of this paper is to illustrate some of the technical and non-technical approaches using simple case studies.

With the rapid development of science and technology, people's life style has changed greatly. Under the background of that, the electronic commerce, conforming to the historical tide, has been used by more and more businesses man and customers. At the same time, the logistics management, which was born along with the electronic commerce, makes a lot difference to social development. This article cites the theory of logistics management to establish the Grey correlation methods of analytic hierarchy process and data envelopment analysis through analyzing the chain operation enterprise. And after a comprehensive analysis from some specific examples, it also draws a conclusion that the main factors which affect the logistics management are the cost and the availability of investment, and the choice of logistics management mode is the third party logistics management model and joint distribution logistics management mode. The research of the theory points out the emphasis of the construction of logistics management, and guides the development direction of logistics management.

Centered on the WebGIS technology of J2EE and combined with the distributed GIS special database, this paper researches on the WebGIS-based stadium intelligent service system. Through deep research of multiple traditional optimal path algorithms, improved algorithm is worked out. Then, after in-depth analyses of users’travel modes, this paper finally devises the optimal path of accessibility of stadiums which can be realized in the WebGIS-based stadium service system. The results show that this optimal path design makes it easier for users to check real-time stadiums and helps users achieve the most accurate information about stadiums, hotels, which provides convenience for users to make the best decisions and improves the efficiency of urban transport. Taking full advantage of mobile Internet and GPS technology, this design lays a foundation for the construction of smart city.

Traditional methods UBCF have limitations of poor recommendation quality and problems of data sparsity. To alleviate these problems, a novel collaborative filtering algorithm is designed, which firstly get the users’ ratings and time intervals for each attribute from the users’ ratings for items, then produce two methods to calculate the similarity between users, introduce a weighting parameters to control the weight between the two similarity methods in order to get a fusion similarity between two users. The results show that this method is able to improve the accuracy of predicted values, resulting in improving recommendation quality of the collaborative filtering recommendation algorithm.

The vigorous development of various technologies in the cloud computation field promotes the development and progress of cloud services. But with the large accumulation of information data in the cloud services, in order to meet user’s needs of cloud services multi-function, the operation capacity of a single cloud service is not enough. Now, combining two or many cloud services is a hot research problem. The other hot research problem is that the task of data construction is assigned to different cloud service platforms. However, the combination schemes are too much, so how to ensure the optimal scheme is credible? It has become the key to solve the problem. After reading a large number of literatures, the paper proposes the big data reliable combination evaluation method based on the cloud service QoS model. By getting the contribution of each of the services in the combination scheme set, the method chooses the optimal cloud service combination scheme. Then the optimal scheme is evaluated its reliability.

Massive calculation tasks always show as a regular problem in the area of data mining. Many traditional data mining algorithms can only deal with small-scale input data and will run slower or even collapse when the input data increase. The problem above is always a bottleneck of traditional data mining algorithm. Better performance can be achieved if we can transplant these algorithms in cloud computing platform and make them run in parallel. Thus, whether the algorithm can be run in parallel properly or not becomes the key to solve the problem mentioned above. By analyzing the process of local linear regression algorithm, the bottleneck and the aspect which can be parallelized in these algorithms corresponding MapReduced algorithms are proposed, which handle the key problem of efficiency successfully. The research achievements gained in this paper provide a solution for MapReducing algorithms of data mining, and the experiment results show the effectiveness of the solution.

With the development of the Internet, enterprise database has accumulated a huge amount of business data; the previous data mining technology is difficult to meet the current technical ability. In cloud computing environment, resources are stored in a distributed form, which is more efficient. In this paper, the authors analyze the sports industry financing mechanism by using data mining technology. Different from the developed countries, China's sports industry is still in its infancy, and sports industry investment and financing is the key to achieve the rapid development. Based on the analysis, we find that China sports industry investment and financing market degree is low, Capital market is difficult to achieve effective allocation of resources, and the improper allocation of resources tends to delay the development of sports industry. On this basis, we put forward relevant policy recommendations.

The user-based collaborative filtering algorithm has been widely used in various kinds of personalized recommendation systems. But it has a serious shortcoming: with the increasing number of the users and commodities, its calculation work grows rapidly. To address the problem of vast time consumption by big dataset, we utilize MapReduce programming idea to do parallelized transformation of the algorithm; finally deploy it to be run in Hadoop cloud computing platform. Experiments have revealed that if computing data is reasonably distributed and the data volume is big, then the algorithm performance of the algorithm can realize favorable linearly speeding effect.

The rapid development of digital technology promotes the media industry, which makes the contemporary mass media has been widely used. In this paper, the author study on smart multimedia classroom and work mode of college instructors based on cloud computing. Cloud computing has changed the traditional PC centric computing model, all of the program data are all hosted in the cloud server. With the application of the social media platform, the instructor can transfer the education information to the college students at any time and at any place. Social media is interactive for college students to browse educational information; students can also use instant messaging tools. This interaction model can avoid the didactic education; and could enhance the recognition and trust of college counselors.

The thesis mainly studies bi-criteria no-wait flexible flow shop problem, whose optimi-zation objective is to minimize the maximum completion time and the maximum delay time. This problem is NP hard, yet enjoying important theoretical research value, thereby this thesis proposes elite particle swarm optimization (EPSO) to solve bi-criteria no-wait flex-ible flow shop problem. EPSO algorithm applies five modified heuristic algorithms and random methods to generating initial population. Moreover, for the particle personal best, this thesis puts forward elite crossover algorithm, which retains continuous fragments of the identical workpieces among excellent individuals, avoiding the destruction of good continuity between solutions of workpieces. In addition, in order to avoid algorithm into local optimum, this thesis raises double insertion disturbance algorithm to help particles jump out the local optimal state and expand the feasible search range. For the purpose of effectively evaluating algorithm quality, there is a comparison among EPSO algorithm, PSO algorithm and ICA algorithm in simulation experiment that is respectively aimed at small-scale problem and large-scale scheduling problem, the results of which show that the proposed EPSO algorithm, due to better validity and accuracy, is superior to the PSO algorithm and ICA algorithm.

Location problem of multi-distribution center is a kind of NP hard problem. To solve such problems, this paper proposes a chaos adaptive mutation particle swarm optimization algorithm. The algorithm uses the ergodic property of chaos to initialize the particle swarm to enhance the diversity of the population, according to the variance of population fitness to adjust the probability of mutation, and adjust the inertia weight factor to improve the global and local search capability of the whole population. In this paper, the algorithm is applied to the location problem of multi-distribution center, established the multi-factor constraints of mathematical model which aiming at timeliness, and on this basis, the corresponding algorithm is designed. It can be seen from the location instance simulation results that the optimization results and efficiency of the adaptive mutation particle swarm optimization algorithm is better than the genetic algorithm and the standard particle swarm optimization algorithm.

This paper investigates a novel LED lamp arrangement to reduce SNR fluctuation in indoor visible light communication system. In VLC system, the signal sources often come from several LED lamps. The different positions of the LED lamps will influence the system quality. In our proposed scheme, the LED lamp arrangement consists of N LED lamps spreading in the ceiling. The heights of all lamps are the same of 3 meters which is the height of communication room. An optimal LED arrangement with the firework algorithm is presented for the minimum SNR factor and SNR fluctuation on the light receiver plane no matter the number of lamps. In order to compare the effect of SNR distributions, the total power of N LED lamps is identical. Our studies show that the SNR factor under such a LED arrangement is reduced from 118.5 to 4.09 with 16 LED lamps multi-input system which effectively reduces the SNR fluctuation between different users. Such arrangement guarantees all users obtain almost identical communication quality regardless of users’ locations.

With the rapid development of science technology, the multi-core processor system has been become one of the hottest issues in the high performance computation field at present. At the same time, there are some problems in the application and the process of development. In order to find the more efficient task scheduling algorithm, this paper will research the multi-core processors task scheduling algorithm. With exploring the existing task scheduling algorithm principle, the heterogeneous multi-core processor system task scheduling mathematical model is be built, and based on the genetic algorithm, the paper proposes the heterogeneous multi-core processor system scheduling based on population genetic algorithm. Then, through the feasibility, parameter analysis, verification algorithm, the improved genetic algorithm effectively improves the system performance, and reduces the running time. The model, in a certain extent, increases the application and development of artificial intelligence, and provides a theoretical basis for related research.

With the rapid growth of the economy and the increasing improvement of life, the large electricity consumption gradually intensifies power grid transmission pressure. In order to solve this problem, the paper analyses the trend of tremendous development in computer, electronic and electric power technology and makes a deep related research. Based on the further analysis of key technologies, the author sets constraint conditions, analyzes the supporting effect, and establishes an optimal configuration model with multiple purposes for distribution network topological structure. On the basis of the minimal module ideal point algorithm, the over all planning is conducted through deep consideration to assure the further optimal configuration of the model. Then the value will be calculated by using the POS algorithm. At last, four optimization plans are obtained and the fourth one whose weight value can be adjusted is chosen to achieve automation and the more rationalized and optimal development of the distribution network topological structure. In addition, this optimal plan provides a stronger basis of theory to the practical application of related work and industries.

For order acceptance and scheduling with hybrid blocking in flow shop, the improved artificial bee colony (IABC) with NEH_BV heuristic algorithm, local search and artificial bee colony (ABC) is proposed for resolving the problem. In this algorithm, we first use NEH_BV heuristic algorithm to get some initial solutions, then updating the above initial solutions with improved artificial bee colony. In updating process, employed bees, onlooker bees and scout bees are inserted heuristic will increase exploitation and exploration of the algorithm. At last, we will get the near optimal solution by IABC algorithm. The effectiveness and efficiencies of the IABC algorithm has been proved by the case’s analysis and been compared with artificial bee colony and harmony search (HS).

A cloud computing resource clustering framework based on fuzzy theory is constructed. There are five steps: characteristics and requirements set, data standardization process, data normalization process, fuzzy similarity matrix, cluster partition. In the clustering partition, the transitive closure method is improved, and the special elements in the fuzzy similarity matrix are used as the control points to simplify the optimization process and improve the optimization accuracy. The experimental results show that the cloud computing resource based on the improved transitive closure method is fast and the resource utilization rate is high after clustering.