122 Matching Annotations
  1. Apr 2021
  2. Nov 2019
  3. Oct 2019
    1. In the front row, an older lady was reading Summer's End by Danielle Steele.

      That same woman attends the event every year and is known to bring along the SMH to read. Seems she's realised her choice had come down to two mostly-fictional items of content and chose to join the growing cohort of ex-readers. Sorry you had to find out this way.

      On a positive note, this woman is clearly a candidate for one of the SMH's super duper 80 per cent off subscription deals.

      You should go and personally save this reader so that you get a good mention from management at the upcoming staff retrenchment function.

  4. Jul 2019
    1. The table 6.1 gives the mixing probabilities and the associated parametricvalues fork(number of components) = 2,3, and 4. It may be noted thatthe Log likelihood value is smaller fork= 4 (the results fork= 5 , 6 etc.are not better than that fork= 4 and hence are not given here). The fourcomponents Poisson Mixture model is given in table 6.2. It may be notedthat 58% of wards may have higher incidence/relative risk and the remainingwards have lesser/lower incidence for the Cancer disease. We computed theposterior probability for each component for each ward (see table 6.3). Eachward is assigned to a particular component so that the posterior probability islarger. These results are also given in table 6.3 Finally we present Choroplethmaps based on those results
    2. The Posterior Probability of Mixing Dis-tribution
    3. Algorithm
    4. EM Procedure
    5. Poisson Mixture
    6. Data Sources
    7. Poisson Mixtures Distribution
    1. Poisson Model
    2. We have analysed the Cancer data of patients in 155 wards of Chennai Cor-poration by the above described method. As preliminary analyses, we havecreated the Choropleth maps for Observed counts, Population of wards, ex-pected counts for patients and SMR's.The Choropleth map for the observed counts Figure 5.2 does not show anypattern. But the Choropleth map for the expected counts Figure: 5.4 indi-cate that the inner regions of the Chennai Corporations have lower expectedcounts and the regions along the border have larger counts of patients. As ameasure of spatial heterogeneity we have computed PSH= 0:7108:Hence ofthe total spatial random variation, nearly 71% is due to spatial heterogene-ity and the remaining 28:92% is due to Poisson variation. Thus the spatialvariation is present in the data.The Choropleth map for Empirical Bayes smoothed rates Figure 5.5 re-veals that only 13 sub regions have high risk values. The wards with numbers53, 64, 67, 70, 78, 93, 100, 103, 110, 117, 122, 147 and 151 have high riskvalues. Though this information could be used by the health managers toconcentrate their work on these regions, one can look for additional covariatesin these regions for further study
    3. Empirical Bayesian Smoothing
    4. Incidence Rate and SMR
    5. Spatial Analysis of Cancer PatientCount Data
    1. Haemocyte morphogenesis
    2. Spreading inhibitory behavior
    3. Inhibition of haemocyte aggregation
    4. Haemolymph protein profile
    5. Total haemocyte count assay
    6. Immunomodulatory
    7. Helicoverpa armiger
    8. Spodoptera litura
    9. Gut enzyme profile
    10. Insecticidal activity
    11. . Statistical analysis
    12. Inhibition of haemocytes spreading behavior
    13. . Inhibition of haemocytes aggregation behavior
    14. Haemolymph protein profiling
    15. Total haemocyte count (THC)
    16. Haemolymph collection
    17. Immunomodulatory
    18. Lactate dehydrogenase
    19. Asparate (AAT) and Alanine aminotransferase (ALT)
    20. Gut enzyme profile
    21. Oral toxicity bioassay
    22. Microinjection bioassay
    23. VS preparation
    24. Insect collection
    25. INSECTICIDAL AND IMMUNOMODULATORY ACTIVITY AGAINST INSECT PEST
  5. Jun 2019
    1. Estimation of Stevioside
    2. Extraction from the plant material
    3. Extraction from the plant material
    4. Extraction from the plant material
    5. Qmmtification of stevioside
    6. Estimation of Steviol
    7. Extraction from plant material
    8. Quantification of steviol
    9. Estimation of free aminoacids
    10. Estimation of soluble proteins
    11. Estimation of sugars
    12. Estimation of total phenols
    13. Determination of moisture
    14. Analytical methods
    15. The experimental part of the study was categorized into five sections for the convenience of reference viz. analytical, toxicological, molecular, biochemical and genomic quantitation.
    16. Plant material
    17. e5 tevia-the natural smeetenei
  6. Jan 2019
  7. Aug 2018
    1. It’s not enough to create best flow for the user, put the right tools in right context at perfect timing. We have to think harder how to delight users.

      Beyond user flow - Designing in "delight" - So many components to create "delight"? What are the features/components that criss-cross the intersections of delight and emotional experience?

  8. Nov 2016
    1. Hillary Clinton es la personificación de la palabra establishment. Desde que en 1979 se convirtiera en la primera dama de Arkansas, su nombre ha sido sinónimo de política. Nunca fue una primera dama al uso, ella quería tener una voz propia, se negaba a ser la sombra de su marido, algo que siempre ha molestado entre los círculos conservadores. Se la ha acusado de impertinente, de antipática y de poco carismática. Pero lo que más molesta de Clinton es el secretismo con el que ha gestionado su carrera.