Avanish Kumar

A modified method for solving the unbalanced assignment problems

It has been noticed that in real life situations, one finds it difficult to balance between jobs and machines, therefore most of the time we face unbalanced assignment problems. The methods suggested in the literature is based on the assumption to assign some of the jobs to dummy or fictitious machines, those jobs are executed on dummy machines which later may be ignored. The present paper suggests a modified method for solving the unbalanced assignment problems. The method is capable of assigning all the jobs to machine optimally. The method is presented in an algorithmic form and implemented on the several sets of input data to test the performance and effectiveness of the algorithm. The developed algorithm is coded into C++. A comparison is also made with the existing approach and it is recorded that our algorithm gives better results.

Performance Intensification of DRTS under Static Load Sharing Scheme

istributed Real Time System (DRTS) provides enormous platform for parallel applications. It is an alternative for highly expensive parallel machines. Task allocation for parallel applications over it, is a crucial phase where strategy for task allocation should be chosen to maximize the throughput and enhance the overall processor utilization. Task allocation is NP-hard or NP-complete problem. A new heuristic for this problem has been suggested and implemented in this paper. To achieve this goal, tasks should be clustered in such a way that it can minimize the inter-task communication cost as well as it must also be taken care that the execution cost of tasks must also be minimum over the processor where the tasks are going to get assigned. Here k- mean clustering has been used to cluster the tasks in the required number of clusters. The proposed model has been simutated in matlab. General Terms

Modified Clustered Approach for Performance Escalation of Distributed Real-Time System

In Distributed Real-Time Systems the execution of computational tasks must be completed within time else catastrophe may ensue. This constraint can be achieved by optimal task allocation in DRTS. In the process of task allocation, an appropriate and efficient load sharing strategies can improve the performance of distributed system. In this paper an efficient, two level clustering approach has been proposed. The initial level of clustering will be done on the basis of execution cost and inter task communication cost and second at the stage of task allocation. In the allocation of tasks a more scalable active approach is being followed which iteratively refines the performance of DRTS. The proposed model has been simulated in MATLAB 7.11.0. Two examples have been demonstrated to illustrate the model and algorithm for performance improvement in distributed system.

Physics Forceps: A New Sensation in Exodontia?

more predictably, and with less trauma for the patient.1 They dramatically reduce the amount of time required to extract teeth and make the whole procedure more comfortable and pleasant for both the operator and the patient. The physics forceps (Fig. 1) is a device that uses a first-class lever mechanism for atraumatic extraction of a tooth from its socket.2 There are two handles, one of which is connected to a bumper that functions as the fulcrum during extraction. It is applied to the buccolabial aspect, usually at the mucogingival junction. The other beak is applied to the palatolingual aspect of the tooth into the gingival sulcus, at a lower level than the bumper.3 This “beak and bumper” design aids the extraction without the use of excessive force.

Importance of Cheiloscopy

A total of 90 individuals (45 males and 45 females) of rural and urban localities aged 15 to 57 years were selected. Of these, 56 were the natives of Patna, Bihar, India. To study the variation in age groups, the entire study population was divided into three groups: Group I – 20 years and below, Group II – 21 to 40 years, and Group III – 41 to 60 years (Table 2). Those with any disease or deformity of the lips were excluded from the study.