There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Data Mining - Concepts and Techniques.

http://brainimaging.waisman.wisc.edu/~chung/neuro.processing/literature/rubinov.2010.NI.network.pdf

Complex network measures of brain connectivity: uses and interpretations.

In large-scale data-intensive applications data play a pivotal role in the execution of these applications, and data transfer is a primary cause of job execution delay. In environments such as the data grids where execution of jobs that require large amounts of data is undertaken, a smart collaborative environment between the scheduling and data management services to achieve a synergistic effect on the performance of the grid becomes essential. This paper presents an intelligent data grid framework where job scheduling and data and replica management are coupled to provide an integrated environment for efficient access to data and job scheduling. The data management service predicts and estimates the appropriate locations of replica and proactively replicates the data sets in these locations while the intelligent tabu-search-based scheduler incorporating information about the data sets dispatches the jobs to the sites expected to facilitate minimum job execution time and better overall system utilization. Evaluation of the framework shows significant improvement in the performance of the grid and job execution time. Copyright © 2008 John Wiley & Sons, Ltd.

Intelligent scheduling and replication: a synergistic approach

Distributed storage systems, e.g., Hadoop Distributed File System (HDFS), have been widely used in datacenters for handling large amounts of data due to their excellent performance in terms of fault tolerance, reliability and scalability. However, these storage systems usually adopt the same replication and storage strategy to guarantee data availability, i.e., creating the same number of replicas for all data sets and randomly storing them across data nodes. Such strategies do not fully consider the difference requirements of data availability on different data sets. More servers than necessary should thus be used to store replicas of rarely-used data, which will lead to increased energy consumption. To address this issue, we propose an energy-efficient storage strategy for cloud datacenters based on a novel hypergraph coverage model. According to users’ requirements of data availability in different applications, our proposed algorithm can selectively determine the corresponding minimum hyperedge coverage, which represents the minimum set of data nodes required in the datacenter. Hence, some other data nodes can be turned off for the purpose of energy saving. We have also implemented our proposed algorithm as a dynamic runtime strategy in a HDFS based prototype datacenter for performance evaluation. Experimental results show that the variable hypergraph coverage based strategy can not only reduce energy consumption, but can also improve the network performance in the datacenter.

An Energy-Efficient Storage Strategy for Cloud Datacenters Based on Variable K-Coverage of a Hypergraph

Over the past decade the computational grid has emerged as an attractive platform to tackle various large-scale problems, especially in science and engineering. One primary issue associated with the efficient and effective utilization of heterogeneous resources in a grid is scheduling. Grid scheduling involves a number of challenging issues mainly due to the dynamic nature of the grid. In this paper, we propose a novel scheduling algorithm, called the Multiple Queues with Duplication (MQD) algorithm for bag-of-tasks applications in grid environments. The proposed algorithm makes scheduling decisions implicitly taking the recent workload pattern of resources into account. In addition, it adopts a duplication scheme in order to achieve better resource utilization and to lead to better schedules. In our evaluation study a number of intensive experiments with various simulation settings have been conducted. Based on the experimental results, MQD confidently demonstrated its practicability and competitiveness with four previously proposed algorithms.

A Grid Scheduling Algorithm for Bag-of-Tasks Applications Using Multiple Queues with Duplication

Wireless sensor networks have very promising future to many applications. Ensuring that sensor nodes locations are verified and are protected from malicious attacks will enable sensor networks deployment in mission critical applications. Due to the deployment nature, sensor nodes are highly vulnerable to localization attacks where an adversary can capture the nodes, changes its location or replaces it with a malicious node. In this paper we study this problem and present a secure localization scheme where nodes can securely locate themselves and send a message about their location to the neighboring nodes, eventually that message reaches the cluster leader and then to a secure base station. To find the location of nodes, we take advantage of triangulation method and protect the message transmission with a secure triple key management scheme.

Secure localization in wireless sensor networks

Most of bioinformatics data distributed on the Internet is organized in an unstructured manner, which makes it hard to construct applications that need to integrate them. In this paper, we proposed an XML schema based data indexing mechanism to integrate sequence databases stored in a DHT overlay network. The construction of large-scale distributed applications therefore can be greatly simplified with the support of structured distributed data. We present a system that can seamlessly integrate sequence databases and computing resources together to provide BLAST query services based on the data indexing mechanism. Our experiments show that, with a data centric scheduling algorithm to improve the processor utilization, the BLAST service can achieve scalable high throughput

Albert Y. Zomaya

Papers

Intelligent scheduling and replication: a synergistic approach

An Energy-Efficient Storage Strategy for Cloud Datacenters Based on Variable K-Coverage of a Hypergraph

A Grid Scheduling Algorithm for Bag-of-Tasks Applications Using Multiple Queues with Duplication

Secure localization in wireless sensor networks

A BLAST service built on data indexed overlay network