I trust you all had a wonderful weekend and to my friends in the Mid-Atlantic, I hope you have dug out from last week’s Nor’Easter. We are getting closer and closer to Spring and hopefully we’ll forget all about this winter’s wild and cold weather. However, if you do want to remember maybe a few of these foods from Chapter 4 ~ Memory Savers will help.
I don’t worry so much about losing my memory due to aging, but the fact that I have too much information in my head which may can cause more forgetfulness. How many times have you walked into a room only to forget what you went in there for? (raise your hand).
Exercising the brain and body helps as we get older and blogging is great brain exercise because of the constant reading, learning and creating. In addition to mental exercises these foods can improve our brain’s performance.
Raisins – tiny fruit with a brain boost, try with peanut butter, sliced banana on a graham cracker as an afternoon snack
All of these food items, with the exception of the wine were ones that my grandmother taught us to eat. I believe that getting this book from my aunt, her last remaining daughter is her way of reminding me to eat right – thanks Mama (RIP).
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I do not recognize these markings. It looks like it may well a bus lane, but I’m not sure. I would like to know what these are for.
If the lines are yellow, it is a no passing zone but the guy driving the paint truck was either drunk or higher.
Sometimes these lines will include refl ective raised pavement markers which make the lines more visible, or the markers may be used to simulate the lines………………………
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The best way to understand the nature of traditional validation procedures is to look at how they fit the simple knowledge generation model(R) described below:
The above formula indicates that we can generate knowledge(K) in different ways depending on whether or not we are focused only on theory(T) or only on practice(E) or only on perceptions(P) or focused in any combination of them at the same time. One of the main implications of the above model is that we can generate knowledge even in the absence of theory.
According to the formula 1 there can be three types of extreme knowledge models: those where only theory is important(K1 = Tep); models where only the practice is important(K2 = tEp); and models where only perceptions are important(K3 = teP). Since all these extreme knowledge models operate or are developed unconnected with the other two factors, they are not subjected to validation procedures, and basically operate from dogmatic points of view. For example, those who regard pure theory as the cream of knowledge will hold their theories up high even if they do reflect neither the practice nor the perceptions. On the other hands, those who regard experience as paramount will defend their practical models even when they lack theoretical and perceptional bases. Extreme knowledge models appears to promote uncoupling specialization pressures, which underline the usual divisions separating theoretical, practical, and perceptional knowledge. Notice that if we drop all the components that are not important for each of the extreme knowledge models above, we can see more clearly their deep nature: K1 = T ; K2 = E ; and K3 = P.
According to formula 1 there can be three types of pseudo-scientific models: those where both theory and practice are important (K4 = TEp); models where only theory and perceptions are important(K5 = TeP); and those where both practice and perceptions are important(K6 = tEP). Notice that all these pseudo-scientific models are subject to partial validation procedures as each of them assumes that one of the components of knowledge is not important. The fact that validation gaps exist, do not erode the scientific quality attached to those models. Most traditional research methods are based on the premise that the theory must match the practice or that the theory must match the perceptions, and not many traditional models appear to be focused on the other possible notion according to formula 1 that the practice must match the perceptions. Notice that if we drop the factor that is not important in each of the pseudo-scientific knowledge models described above we are given an illusion of completeness by eliminating complexity and we get K4 = TE ; K5 = TP ; and K6 = EP. This is what really happens when we assume away complexity to simplify things, and the most common models used under these conditions is K4 = TE or K5 = TP
According to formula 1, there can be only one true scientific knowledge model, those where the theory, the practice, and the perceptions are important at the same time(K7 = TEP). Only then, full validation procedures are considered binding because the theory, the practice, and the perceptions must match at the same time. Here as much complexity as possible is included to reflect full validation procedures and to achieve consistency by using knowledge gaps to validate or invalidate or create new types of knowledge: theoretical, practical, perceptional, or any combination of them.
Validation procedures based on quantitative methods usually work at the level of pseudo-scientific models as most of them usually assume that behavior, which is closely related to perceptions can be easily predicted and/or regulated or can be assumed as homogenous. Qualitative methods are not usually associated with validation goals as they operate in my opinion in the area of extreme knowledge models as they are usually interested on particular theories or on particular practices or on particular perceptions as they relate to one or few cases. Because qualitative methods have no strong emphasis on validation procedures they are considered be less scientifically sound than quantitative methods are thought to be. Yet, as pointed out above, even quantitative research is usually subjected only to partial validation procedures because of its heavy reliance of assuming complexity away.
To show in simple terms how these validation procedures can be implemented and replicated, considered the following hypothetical information:
b) theories(T) in dichotomy form indicate that we should expect these three factors F1, F2, and F3 to display strong pressures on deforestation(S);
c) it was found that the dichotomy practice(E) indicates that factor F1 shows increasing pressures on deforestation(1); factor F2 reflects decreasing pressures on deforestation(2) and factor F3 displays also decreasing pressures on deforestation(2)
d) it was found that dichotomy perceptions(P) suggest that factor F1 is a very important causal factor(VI); and that both factor F2 and factor F3 are considered to be not very important deforestation factors(NVI).
Now, based on the information in the table above, we can summarize how each of the qualitative validation procedures can be applied and its implications:
F1 = S.1.VI = strong theoretical role(S), increasing pressures in practice(1), and very important perceptions(VI)
F2 = S.2.NVI = strong theoretical role(S) does not match decreasing practical pressures(2) and not very
An examples of information generated when the validation procedures described above are apply to ideal data is provided below:
Examples of information generated when the validation procedures described above are apply to real data are provided below:
the dimensions of color | defound - industrial design blog / inspirational and interesting design finds	
what are the ‘real’ primary colors? the red, yellow and blue of the conventional color wheel? or the printer’s yellow, magenta and cyan? or the primaries for mixing colored lights – red, green, and blue?
these and a lot of other questions are discussed at http://www.huevaluechroma.com, a website by david briggs on the dimensions of color and light perception.
sometimes a bit heavy on the technical side of things. and it may leave you even more confused then before. but still a great read for anybody interested in more than the absolute basics of color theory.