Geetha Srinivasan

Bio: Geetha Srinivasan is an academic researcher from All India Institute of Medical Sciences. The author has contributed to research in topics: Glaucoma & Intraocular pressure. The author has an hindex of 18, co-authored 52 publications receiving 1359 citations. Previous affiliations of Geetha Srinivasan include Defence Research and Development Organisation & International Maize and Wheat Improvement Center.

GRAFICS—a nonhierarchical clustering algorithm for group technology

Abstract: An efficient nonhierarchical clustering algorithm, based on initial seeds obtained from the assignment method, for finding part-families and machine cells for group technology (GT) is presented. By a process of alternate clustering and generating seeds from rows and columns, the zero-one machine-component incidence matrix was block-diagonalized with the aim of minimizing exceptional elements (intercell movements) and blanks (machine idling). The algorithm is compared with the existing nonhierarchical clustering method and is found to yield favourable results.

Two-generation marker-aided backcrossing for rapid conversion of normal maize lines to quality protein maize (QPM)

Abstract: The low nutritive value of maize endosperm protein is genetically corrected in quality protein maize (QPM), which contains the opaque2 gene along with numerous modifiers for kernel hardness. We report here a two generation marker-based backcross breeding program for incorporation of the opaque2 gene along with phenotypic selection for kernel modification in the background of an early maturing normal maize inbred line, V25. Using the flanking marker distances from opaque2 gene in the cross V25×CML176, optimum population size for the BC2 generation was computed in such a way that at least one double recombinant could be obtained. Whole genome background selection in the BC2 generation identified three plants with 93 to 96% recurrent parent genome content. The three BC2F2 families derived from marker identified BC2 individuals were subjected to foreground selection and phenotypic selection for kernel modification. The tryptophan concentration in endosperm protein was significantly enhanced in all the three classes of kernel modification viz., less than 25%, 25–50% and more than 50% opaqueness. BC2F3 lines developed from the hard endosperm kernels were evaluated for desirable agronomic and biochemical traits in replicated trials and the best line was chosen to represent the QPM version of V25, with tryptophan concentration of 0.85% in protein. The integrated breeding strategy reported here can be applied to reduce genetic drag as well as the time involved in a conventional line conversion program, and would prove valuable in rapid development of specialty corn germplasm.

A clustering algorithm for machine cell formation in group technology using minimum spanning trees

Abstract: I address the machine cell part family formation problem in group technology. The minimum spanning tree (MST) For machines is constructed from which seeds to cluster components are generated. Seeds to cluster machines are obtained from component clusters. The process of alternate seed generation and clustering is continued until feasible solutions are obtained. Edges are removed from the MST to identify alternate starting seeds for clustering. The algorithm is tested with matrices available in the literature. The results compare favourably with existing methods.

Planning for sustainable solid waste management in urban India

Abstract: Planning for sustainable urban solid waste management (USWM) in developing countries has to address several interdependent issues such as public health, environment, present and future costs to society and the livelihood of the “actors” in the informal recycling sector. This article presents a system dynamics model which captures the dynamic nature of interactions among the various components of the USWM system in a typical metropolitan city in India. The model provides a platform for debate on the potential and systemic consequences of various structural and policy alternatives for sustainable USWM. © 1997 John Wiley & Sons, Ltd.

Utility values among glaucoma patients: an impact on the quality of life.

Abstract: Aim: To ascertain utility values and associated quality of life with different severity and duration of glaucoma among Indian patients. Methods: Utility values of 105 consecutive patients with primary glaucoma of at least 12 months’ duration were evaluated in a cross sectional study. Utility values were ascertained in five groups using both the time-trade off and standard gamble methods: group 1 (best corrected visual acuity in the better eye of 6/9 or better), group 2 (best corrected visual acuity in the better eye of 6/18 to 6/12), group 3 (best corrected visual acuity in the better eye of 6/36 to6/24), group 4 (best corrected visual acuity in the better eye of 3/60 to 6/60), and group 5 (best corrected visual acuity in the better eye of 3/60 or worse). Results: The mean utility value for the glaucoma group as a whole was 0.64 (SD 0.69; 95% confidence interval (CI), 0.58 to 0.70) with the time-trade off method and 0.86 (SD 1.00; 95% CI, 0.81 to 0.90) with the standard gamble method for a gamble of death and 0.97 (SD 1.00; 95% CI, 0.94 to 0.99) for a gamble of blindness. The mean utility results by the time-trade off method were as follows: group 1 = 0.66, group 2 = 0.66, group 3 = 0.62, group 4 = 0.55, and group 5 = 0.61. The utility value was much lower (0.46) in those with no formal education or only primary education compared to those with postgraduate education (0.75) (p = 0.038). Those patients with glaucoma of less than 5 years’ duration had a utility score of 0.62 while those with glaucoma for more than 10 years had a score of 0.74 (p = 0.40). Conclusions: Visual acuity loss occurring secondary to glaucoma is associated with a substantial decrease in patient utility value (and quality of life) in a developing country like India. The utility value is directly dependent on the degree of visual acuity loss associated with the disease and educational status and not on the duration of disease, the number of medications, or the visual field indices.

Metaheuristics: A bibliography

Abstract: Metaheuristics are the most exciting development in approximate optimization techniques of the last two decades. They have had widespread successes in attacking a variety of difficult combinatorial optimization problems that arise in many practical areas. This bibliography provides a classification of a comprehensive list of 1380 references on the theory and application of metaheuristics. Metaheuristics include but are not limited to constraint logic programming; greedy random adaptive search procedures; natural evolutionary computation; neural networks; non-monotonic search strategies; space-search methods; simulated annealing; tabu search; threshold algorithms and their hybrids. References are presented in alphabetical order under a number of subheadings.

The clinical effectiveness and cost-effectiveness of screening for open angle glaucoma: a systematic review and economic evaluation.

Abstract: OBJECTIVES: To assess whether open angle glaucoma (OAG) screening meets the UK National Screening Committee criteria, to compare screening strategies with case finding, to estimate test parameters, to model estimates of cost and cost-effectiveness, and to identify areas for future research. DATA SOURCES: Major electronic databases were searched up to December 2005. REVIEW METHODS: Screening strategies were developed by wide consultation. Markov submodels were developed to represent screening strategies. Parameter estimates were determined by systematic reviews of epidemiology, economic evaluations of screening, and effectiveness (test accuracy, screening and treatment). Tailored highly sensitive electronic searches were undertaken. RESULTS: Most potential screening tests reviewed had an estimated specificity of 85% or higher. No test was clearly most accurate, with only a few, heterogeneous studies for each test. No randomised controlled trials (RCTs) of screening were identified. Based on two treatment RCTs, early treatment reduces the risk of progression. Extrapolating from this, and assuming accelerated progression with advancing disease severity, without treatment the mean time to blindness in at least one eye was approximately 23 years, compared to 35 years with treatment. Prevalence would have to be about 3-4% in 40 year olds with a screening interval of 10 years to approach cost-effectiveness. It is predicted that screening might be cost-effective in a 50-year-old cohort at a prevalence of 4% with a 10-year screening interval. General population screening at any age, thus, appears not to be cost-effective. Selective screening of groups with higher prevalence (family history, black ethnicity) might be worthwhile, although this would only cover 6% of the population. Extension to include other at-risk cohorts (e.g. myopia and diabetes) would include 37% of the general population, but the prevalence is then too low for screening to be considered cost-effective. Screening using a test with initial automated classification followed by assessment by a specialised optometrist, for test positives, was more cost-effective than initial specialised optometric assessment. The cost-effectiveness of the screening programme was highly sensitive to the perspective on costs (NHS or societal). In the base-case model, the NHS costs of visual impairment were estimated as 669 pounds. If annual societal costs were 8800 pounds, then screening might be considered cost-effective for a 40-year-old cohort with 1% OAG prevalence assuming a willingness to pay of 30,000 pounds per quality-adjusted life-year. Of lesser importance were changes to estimates of attendance for sight tests, incidence of OAG, rate of progression and utility values for each stage of OAG severity. Cost-effectiveness was not particularly sensitive to the accuracy of screening tests within the ranges observed. However, a highly specific test is required to reduce large numbers of false-positive referrals. The findings that population screening is unlikely to be cost-effective are based on an economic model whose parameter estimates have considerable uncertainty. In particular, if rate of progression and/or costs of visual impairment are higher than estimated then screening could be cost-effective. CONCLUSIONS: While population screening is not cost-effective, the targeted screening of high-risk groups may be. Procedures for identifying those at risk, for quality assuring the programme, as well as adequate service provision for those screened positive would all be needed. Glaucoma detection can be improved by increasing attendance for eye examination, and improving the performance of current testing by either refining practice or adding in a technology-based first assessment, the latter being the more cost-effective option. This has implications for any future organisational changes in community eye-care services. Further research should aim to develop and provide quality data to populate the economic model, by conducting a feasibility study of interventions to improve detection, by obtaining further data on costs of blindness, risk of progression and health outcomes, and by conducting an RCT of interventions to improve the uptake of glaucoma testing.

Biased random-key genetic algorithms for combinatorial optimization

Abstract: Random-key genetic algorithms were introduced by Bean (ORSA J. Comput. 6:154---160, 1994) for solving sequencing problems in combinatorial optimization. Since then, they have been extended to handle a wide class of combinatorial optimization problems. This paper presents a tutorial on the implementation and use of biased random-key genetic algorithms for solving combinatorial optimization problems. Biased random-key genetic algorithms are a variant of random-key genetic algorithms, where one of the parents used for mating is biased to be of higher fitness than the other parent. After introducing the basics of biased random-key genetic algorithms, the paper discusses in some detail implementation issues, illustrating the ease in which sequential and parallel heuristics based on biased random-key genetic algorithms can be developed. A survey of applications that have recently appeared in the literature is also given.