The State, Local Community and Participatory Governance Practices: Prospects of Change

In policy discourse of 1990s, more inclusive spaces have been constructed for realizing full and meaningful participation of common people in education. These participatory spaces provide an alternative possibility for universalizing elementary education against the backdrop of a history of entrenched forms of social and economical exclusion; inequitable education provisions; and shrinking role of the state in today-s neo-liberal times. Drawing on case-studies of bottom-up approaches to school governance, the study examines an array of innovative ways through which poor people gained a sense of identity and agency by evolving indigenous solutions to issues regarding schooling of their children. In the process, state-s institutions and practices became more accountable and responsive to educational concerns of the marginalized people. The deliberative participation emerged as an active way of experiencing deeper forms of empowerment and democracy than its passive realization as mere bearers of citizen rights.

A Fault Tolerant Token-based Algorithm for Group Mutual Exclusion in Distributed Systems

The group mutual exclusion (GME) problem is a variant of the mutual exclusion problem. In the present paper a token-based group mutual exclusion algorithm, capable of handling transient faults, is proposed. The algorithm uses the concept of dynamic request sets. A time out mechanism is used to detect the token loss; also, a distributed scheme is used to regenerate the token. The worst case message complexity of the algorithm is n+1. The maximum concurrency and forum switch complexity of the algorithm are n and min (n, m) respectively, where n is the number of processes and m is the number of groups. The algorithm also satisfies another desirable property called smooth admission. The scheme can also be adapted to handle the extended group mutual exclusion problem.

Concurrency without Locking in Parallel Hash Structures used for Data Processing

Various mechanisms providing mutual exclusion and thread synchronization can be used to support parallel processing within a single computer. Instead of using locks, semaphores, barriers or other traditional approaches in this paper we focus on alternative ways for making better use of modern multithreaded architectures and preparing hash tables for concurrent accesses. Hash structures will be used to demonstrate and compare two entirely different approaches (rule based cooperation and hardware synchronization support) to an efficient parallel implementation using traditional locks. Comparison includes implementation details, performance ranking and scalability issues. We aim at understanding the effects the parallelization schemes have on the execution environment with special focus on the memory system and memory access characteristics.

On Bounding Jayanti's Distributed Mutual Exclusion Algorithm

Jayanti-s algorithm is one of the best known abortable mutual exclusion algorithms. This work is an attempt to overcome an already known limitation of the algorithm while preserving its all important properties and elegance. The limitation is that the token number used to assign process identification number to new incoming processes is unbounded. We have used a suitably adapted alternative data structure, in order to completely eliminate the use of token number, in the algorithm.

Tracking Objects in Color Image Sequences: Application to Football Images

In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.