Refine your search
Collections
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Senthilkumar, B.
- Generalized Robust Statistics Method for Estimating Average Length of Stay in Hospitals
Abstract Views :571 |
PDF Views:93
Authors
Affiliations
1 National Institute of Epidemiology, Ayyapakkam, Chennai – 600 077, IN
1 National Institute of Epidemiology, Ayyapakkam, Chennai – 600 077, IN
Source
Indian Journal of Science and Technology, Vol 5, No 1 (2012), Pagination: 1859-1862Abstract
Hospital length of stay is an important performance indicator for hospital management and a key measure of efficiency in health care. However, it is difficult to analyze as most distributions pertaining to hospital length of stay are asymmetric due to outliers. The objective of the present study is to suggest a new method to estimate average length of stay (ALOS). Data on LOS in the year 2010 from a corporate hospital was considered for analysis. ALOS was calculated using generalized robust statistics method (GRSM) and other existing methods. The comparison of results shows that GRSM is a better alternative over other existing methods.Keywords
Health Management, Hospital Stay, Health CareFull Text
References
- Concepcion Ausin, Rose E Lillo, Fabrizio Ruggeri and Michael P. Wiper (2003) Bayesian modeling of hospital bed occupancy times using mixed generalized Erlang distributions, Bayesian Statistics, Oxford University Press.7, 1-10,
- Kulinskaya E, Knight E, Kornbrot DE and Benton P (2001) The use of log and power transformations in the analysis of length of stay data, Case mix Quarterly, 3, 79-89.
- Kulinskaya E, Kornbrot DE and Haiyan Gao (2005) Length of stay as a performance indicator: Robust statistical methodology. IMA J. Management Math. 16, 369-381.
- Lave JR and Leinhard S (1976) The cost and length of a hospital stay. Inquiry. 13, 327-343.
- Marazzi A, Paccaud F, Ruffieux C and Beguin C (1998) Fitting the distributions of length of stay by parametric models. Med. Care. 36(6), 915-927.
- Ramakrishnan N et.al., (2009) Quality indicators for ICU. Indian society of critical care medicine. Electronic references. Retrieved on 8.01.2011 from www.isccm.org/PDF files/Section8.pdf.
- Ruffieux C, Marazzi A and Paccaud F (1993) Exploring models for the length of stay distribution. Soz Preventive Med. 38(2),77-82.
- Ruffieux C, Paccaud F and Marazzi A (2000) Comparing rules for truncating hospital length of stay. Casemix Quaterly. 2(1),1-10.
- Tracy R. McMillan and Robert C. Hyzy (2007) Bringing quality improvement into the intensive care unit. Critical Care Med. 35, S59-S65.
- Weissman C (1997) Analyzing intensive care unit length of stay data: problems and possible solutions. Critical Care Med. 25(9), 1594-1600.
- Wright SP, Verouhis D, Gamble G, Swedberg K, Sharpe N, Dought RN (2003) Factors influencing the length of hospital stay for patients with heart failure, The Eur. J. Heart Failure. 5, 201-209.
- Fuzzy Based Implementation Resource Allocation in Cognitive Radio Networks for Secondary Users
Abstract Views :158 |
PDF Views:8
Authors
Affiliations
1 Sri Balaji Chockalingam Engineering College, Arni, Tamilnadu, IN
2 St. Joseph College of Engineering, Chennai, Tamilnadu, IN
1 Sri Balaji Chockalingam Engineering College, Arni, Tamilnadu, IN
2 St. Joseph College of Engineering, Chennai, Tamilnadu, IN
Source
Wireless Communication, Vol 5, No 8 (2013), Pagination: 340-343Abstract
The efficient use of Available licensed spectrum is becoming more and more critical with increasing demand and usage of the radio spectrum. In practice, the spectrum allocated to licensed primary users is not utilized properly. The secondary unlicensed users can sense and utilize the unutilized spectrum. In this paper we propose new method for fuzzy logic control which enables cognitive secondary user to achieve its required rate of transmission and quality, at the same time minimizing interference to the primary users and other concurrent secondary users. In this work Fuzzy logic based system is proposed where the secondary users can opportunistically use the spectrum. Existing Fast barrier method users’ iterative Numerical method based Resource Allocation. To reduce the delay and complexity Fuzzy Based approach is proposed. So that fast optimal Resource Allocation is possible.Keywords
Cognitive Radio Networks, Fuzzy Logic System, Spectrum Utilization.
- Temperature Prediction using Finite Element Modeling on Friction Stir Welding of AA6061-AZ61
Abstract Views :159 |
PDF Views:0
Authors
Affiliations
1 Department of Mining Machinery Engineering, Indian School of Mines, Dhanbad-826 004, Jharkhand, IN
2 Department of Production Engineering, Sri Sairam Engineering College, Chennai-600 044, Tamil Nadu, IN
1 Department of Mining Machinery Engineering, Indian School of Mines, Dhanbad-826 004, Jharkhand, IN
2 Department of Production Engineering, Sri Sairam Engineering College, Chennai-600 044, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 31 (2015), Pagination:Abstract
Background/Objectives: The objective of this paper is on developing a thermo-mechanical model to predict the thermal histories of the FSW butt joint of AA 6061-AZ61. Methods/Statistical Analysis: The FEM model is developed for the temperature and residual stress characteristics of the weld material. The friction serves as the heat source which exists between the pin and plate as well as the shoulder and plate. To understand the dynamics of the Friction Stir Welding thermal and residual effects,the thermal history and the evolution of longitudinal, lateral residual stresses in the friction stirred weld are simulated using ANSYS. Findings: The temperature influences on Von-mises stress and strain on the different zones are analyzed. The contour technique using Coordinate Measuring Machine (CMM) is used to measure the residual stress of the welded plate.It is found that the proposed model is correlated with experimental result. Application/ Improvements: The developed FEM model can be used as one of the tool for correlating the temperature and residual stresses on the weld zone. The CMM also can be used to predict the residual stresses through contour measurement.Keywords
Finite Element Method, Friction Stir Welding, Residual Stress, Temperature Distribution,Thermo-Mechanical ModelFull Text
- Temperature Prediction using Finite Element Modeling on Friction Stir Welding of AA6061-AZ61
Abstract Views :155 |
PDF Views:0
Authors
Affiliations
1 Department of Mining Machinery Engineering, Indian School of Mines, Dhanbad-826 004, Jharkhand, IN
2 Department of Production Engineering, Sri Sairam Engineering College, Chennai-600 044, Tamil Nadu, IN
1 Department of Mining Machinery Engineering, Indian School of Mines, Dhanbad-826 004, Jharkhand, IN
2 Department of Production Engineering, Sri Sairam Engineering College, Chennai-600 044, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 31 (2015), Pagination:Abstract
Background/Objectives: The objective of this paper is on developing a thermo-mechanical model to predict the thermal histories of the FSW butt joint of AA 6061-AZ61. Methods/Statistical Analysis: The FEM model is developed for the temperature and residual stress characteristics of the weld material. The friction serves as the heat source which exists between the pin and plate as well as the shoulder and plate. To understand the dynamics of the Friction Stir Welding thermal and residual effects,the thermal history and the evolution of longitudinal, lateral residual stresses in the friction stirred weld are simulated using ANSYS. Findings: The temperature influences on Von-mises stress and strain on the different zones are analyzed. The contour technique using Coordinate Measuring Machine (CMM) is used to measure the residual stress of the welded plate.It is found that the proposed model is correlated with experimental result. Application/ Improvements: The developed FEM model can be used as one of the tool for correlating the temperature and residual stresses on the weld zone. The CMM also can be used to predict the residual stresses through contour measurement.Keywords
Finite Element Method, Friction Stir Welding, Residual Stress, Temperature Distribution,Thermo-Mechanical ModelFull Text