Abstract The identification of territorial clusters where the population suffers from worse health conditions is an important topic in social epidemiology, order to identify inequalities cities and provide policy interventions. This objective particularly challenging because mechanism self-selection individuals into neighborhoods, which causes selection bias. aim this paper consists neighborhoo...

Competitive learning mechanisms for clustering in general suffer from poor performance for very high dimensional ( ) data because of “curse of dimensionality” effects. In applications such as document clustering, it is customary to normalize the high dimensional input vectors to unit length, and it is sometimes also desirable to obtain balanced clusters, i.e., clusters of comparable sizes. The ...

Data distribution and load balancing become increasingly important in large-scale distributed storage system. This paper focuses on the problem of designing an optimal, self-adaptive strategies for balanced distribution and reorganization of replicated objects among a dynamically heterogeneous nodes, and presents a novel decentralized algorithm, Dynamic Interval Mapping, which maps replicated o...

When clustering objects to be allocated on a number of nodes, most researches focus only on either the communication cost between clusters or the balancing of the workload on the nodes. Load balancing is a technique to distribute workload evenly across two or more computers, network links, CPUs, hard drives or other resources, in order to, get optimal resource utilization, maximize throughput, ...

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract K-means Clustering Algorithm, among the various clustering algorithms proposed till date, has proved its superiority by its simplicity and usability. However, it is prone to a number of limitations, one being lack of balance in clusters. Clusters o...

A distinctive feature of a clustered observational study is its multilevel or nested data structure arising from the assignment of treatment, in a non-random manner, to groups or clusters of units or individuals. Examples are ubiquitous in the health and social sciences including patients in hospitals, employees in firms, and students in schools. What is the optimal matching strategy in a clust...

In the last several years, tightly coupled PC clusters have become widely applied, cost effective resources for lattice gauge computations. This paper discusses the practice of building such clusters, in particular balanced design requirements. I review and quantify the improvements over time of key performance parameters and overall price to performance ratio. Applying these trends and technol...

In the last several years, tightly coupled PC clusters have become widely applied, cost effective resources for lattice gauge computations. This paper discusses the practice of building such clusters, in particular balanced design requirements. I review and quantify the improvements over time of key performance parameters and overall price to performance ratio. Applying these trends and technol...

A coupled cell network describes interacting (coupled) individual systems (cells). As in networks from real applications, coupled cell networks can represent inhomogeneous networks where different types of cells interact with each other in different ways, which can be represented graphically by different symbols, or abstractly by equivalence relations. Various synchronous behaviors, from full s...