Comparative Study Of Congestion Control Techniques In High Speed Networks

Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially to handle bursty traffic of todays very high speed networks. Since late 90s numerous schemes i.e. [1]...[10] etc. have been proposed. This paper concentrates on comparative study of the different congestion control schemes based on some key performance metrics. An effort has been made to judge the performance of Maximum Entropy (ME) based solution for a steady state GE/GE/1/N censored queues with partial buffer sharing scheme against these key performance metrics.Comment: 10 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS November 2009, ISSN 1947 5500, http://sites.google.com/site/ijcsis

Adopting AHP in evaluating nurse scheduling methods

When comparing and evaluating two or more scheduling methods the need to use a multiple criteria decision making technique arises.Instead of just employing a qualitative approach of evaluating the methods, one can integrate the qualitative and the quantitative data in the evaluation process through the use of the analytic hierarchy process (AHP).Hence, this paper reports the evaluation of two nurse scheduling methods where the AHP technique is employed to support the selection process of these methods.Five decision criteria are used in the process.The main objective of the scheduling methods (models) is to assign work shifts and off days of the nurses in a particular hospital unit such that, it fulfils certain specified constraints while ensuring continuous high-quality patient care services.The first method is a heuristic procedure that is currently in practice.The other one is a prototype in which a memetic algorithm is adopted in the approach.The application of AHP has been found to provide a better transparency of the capability and efficiency of the scheduling methods. Consequently, the memetic algorithm approach stands out to be the better one based on the evaluation scheme

Comparison Of Smartphones Using Data Envelopment Analysis.

In today's digital era, competition for smart gadgets is often fierce. The last few years have witnessed the emergence of smartphones with each manufacturer trying to out do its competitor in terms of attractive features

Efficiency in the worst production situation using data envelopment analysis

Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) without considering noise in data.The least efficient DMU indicates that it is in the worst situation.In this paper, we measure efficiency of individual DMU whenever it losses the maximum output, and the efficiency of other DMUs is measured in the observed situation.This efficiency is the minimum efficiency of a DMU.The concept of stochastic data envelopment analysis (SDEA) is a DEA method which considers the noise in data which is proposed in this study.Using bounded Pareto distribution, we estimate the DEA efficiency from efficiency interval. Small value of shape parameter can estimate the efficiency more accurately using the Pareto distribution.Rank correlations were estimated between observed efficiencies and minimum efficiency as well as between observed and estimated efficiency.The correlations are indicating the effectiveness of this SDEA model

Wage augmented stochastic frontier model with truncated normal distribution

This study considered wage augmented production frontiers with inefficiency effects model proposed by Battese and Coelli (1992) where the efficiency wage hypotheses was tested.An unbalanced panel data on 31 manufacturing firm for the period 1989 to 2000 was used in this study.The wage augmented CobbDouglas production function was originated to be an unsatisfactory representation of the data compared to wage augmented Translog frontier model.The results showed that the wage level was one of the significant factors contributing to the output and technical efficiency in truncated normal distribution which was found to be of inferior quality in manufacturing industry in Bangladesh

Live cell imaging of low- and non-repetitive chromosome loci using CRISPR-Cas9.

Imaging chromatin dynamics is crucial to understand genome organization and its role in transcriptional regulation. Recently, the RNA-guidable feature of CRISPR-Cas9 has been utilized for imaging of chromatin within live cells. However, these methods are mostly applicable to highly repetitive regions, whereas imaging regions with low or no repeats remains as a challenge. To address this challenge, we design single-guide RNAs (sgRNAs) integrated with up to 16 MS2 binding motifs to enable robust fluorescent signal amplification. These engineered sgRNAs enable multicolour labelling of low-repeat-containing regions using a single sgRNA and of non-repetitive regions with as few as four unique sgRNAs. We achieve tracking of native chromatin loci throughout the cell cycle and determine differential positioning of transcriptionally active and inactive regions in the nucleus. These results demonstrate the feasibility of our approach to monitor the position and dynamics of both repetitive and non-repetitive genomic regions in live cells