WITNESS LIST
Public Education Committee
April 5, 2011 - 2:00 PM or upon final adjourn./recess
For:
Anthony, David (Cypress - Fairbanks ISD)
Freeman, Ray (Equity Center)
Registering, but not testifying:
For:
Beneski, Amy (Texas Association of School Administrators)
Flores, Rebecca (Houston ISD)
Lindsey, Andrew (Texas Parent Teacher Association)
Shields, Julie (Texas Assoc. of School Boards)
For:
Colbert, Paul (Self; El Paso ISD)
Freeman, Ray (Equity Center)
Grusendorf, Bill (Tex Assoc Rural Schools)
Hunkapiller, Jerry (Millsap ISD, Equity Center, TARS)
Knight, Roy (Lufkin ISD)
Whiteker, Mary (Self)
Woody, Tom (Vernon ISD)
On:
Melina Raab, Ted (Texas AFT (American Federation of Teachers))
Registering, but not testifying:
For:
Garner, Allen (Central ISD)
Martel, Gary (Diboll I.S.D.)
Schneider, Todd (Martin's Mill ISD)
Sheets, Gene (Texas Association of Rural Schools/ Muleshoe ISD)
Wright, Eric (Huntington ISD)
Against:
Brown, Kevin (Alamo Heights ISD/ Texas School Coalition)
Roach, Tracey (Texas School Coalition)
Rotan, Wayne (Glen Rose ISD/ Texas School Coalition)
Springs, Mary (Santa Gertrudis ISD)
Wellman, Nola (Eanes ISD)
For:
Casey, Daniel (Fast Growth School Coalition)
Grusendorf, Bill (TX Assoc Rural Schools)
1
WITNESS LIST
For:
Jerry, Hunkapiller (Millsap ISD, Equity Center, TARS)
Melina Raab, Ted (Texas AFT (American Federation of Teachers))
Moak, Lynn (Texas School Alliance)
Thompson, David (Texas Association of School Administrators)
Against:
Knight, Roy (Lufkin ISD)
On:
Anderson, David (Texas Education Agency)
Colbert, Paul (Self; El Paso ISD)
Giarratani, Dominic (Texas Association of School Boards)
Woody, Tom (Vernon ISD)
Registering, but not testifying:
For:
Exter, Monty (Association of Texas Professional Educators (ATPE))
Graham, Lloyd (La Porte ISD)
Green, Terry (Family & Consumer Sciences Teachers Assn. of TX)
Holcombe, Linda (TIVA - Texas Industrial Vocational Assoc)
Rogers, Don (Texas Rural Education Assn.)
Williams, Paige (Texas Classroom Teachers Association)
Young, Gerald (Agriculture Teachers Assn. of TX)
Against:
Craymer, Dale (Texas Taxpayers & Research Association)
Davis, Tricia (Self; Texas Royalty Council)
LeBas, James (Texas Chemical Council/ Texas Oil & Gas Association)
Scheberle, Drew (Greater Austin Chamber of Commerce)
York, Dwain (Wimberley ISD)
For:
Colbert, Paul (Self; El Paso ISD)
Trull, Paul (Paris ISD Board of Trustees)
Against:
Achtermann, Jeff (Self)
Brown, Kevin (Alamo Heights ISD/ Texas School Coalition)
Casey, Daniel (Fast Growth School Coalition)
Dadey, Catherine (Self)
Giarratani, Dominic (Texas Association of School Boards)
Hunkapiller, Jerry (Millsap ISD, Equity Center, TARS)
Moak, Lynn (Texas School Alliance)
Palmer, Richard (Piney East Perkins Consortium)
Rotan, Wayne (Glen Rose Independent School District/ Texas School Coalition)
Sheets, Gene (Texas Association of Rural Schools - President/ Muleshoe ISD -
Superintendent)
2
WITNESS LIST
Against:
Springs, Mary (Santa Gertrudis ISD (Kingsville))
Tarleton, Bill (Texas Rural Educators Association)
Thompson, David (Houston ISD/ Texas Assn of School Administrators)
Thompson, Marty (Career & Technology Education of Texas)
Whiteker, Mary Ann (TX Association of Community Schools)
On:
Anderson, David (Texas Education Agency)
Anthony, David (Cypress Fairbanks ISD)
Dawn-Fisher, Lisa (Texas Education Agency)
Eversol, Wes (Lake Dallas ISD)
Grusendorf, Bill (TX. Assoc Rural Schools)
Melina Raab, Ted (Texas AFT (American Federation of Teachers))
Pierce, Wayne (Equity Center)
Stinson, Gayle (Lake Dallas ISD)
Woody, Tom (Vernon ISD)
Zimmermann, Kathleen (NYOS Charter School)
Registering, but not testifying:
For:
Schneider, Todd (Martin's Mill ISD)
Against:
Garner, Allen (Central ISD)
Graham, Lloyd (La Porte ISD)
Green, Terry (Family & Consumer Sciences Teachers Assn. of TX)
Holcombe, Linda (TIVA - Texas Industrial Vocational Assoc.)
Martel, Gary (Diboll I.S.D.)
Painovich, Robin (Career & Technology Association of Texas)
Rue, Karen (Northwest I.S.D.)
Scheberle, Drew (Greater Austin Chamber of Commerce)
Weinberg, Tracy (Texas Association for the Gifted & Talented)
Wellman, Nola (Eanes ISD)
Wright, Eric (Huntington ISD)
York, Dwain (Wimberley ISD)
Young, Gerald (Agriculture Teachers Assn. TX)
On:
Thomas, Amanda (Texas Charter Schools Association)
For:
Packard, Ron (K12, Inc.)
Against:
Melina Raab, Ted (Texas AFT (American Federation of Teachers))
3
WITNESS LIST
On:
Bosse, Portia (Texas State Teachers Assn.)
Brownson, Amanda (Texas School Alliance)
Givens, Anita (Texas Education Agency)
Gregg, Brock (Assn. of TX. Professional Educators (ATPE))
Miller, Jeff (Disability Rights Texas)
Shields, Julie (Texas Assoc. of School Boards)
Statman, Rona (The Arc of Texas)
Williams, Paige (Texas Classroom Teachers Association)
Registering, but not testifying:
For:
Erben, Andrew (TX. Institute for Education Reform)
Lindsey, Andrew (Texas Parent Teacher Association)
Salinas, Nelson (The Texas Association of Business)
Weinberg, Tracy (Texas Association for the Gifted & Talented)
Against:
Carpenter, Bill (Texas Council of Administrators of Special Education)
McCraw, Ken (TX Assn of Community Schools)
For:
McLaughlin, Bill (Walcott I.S.D.)
Pierce, Wayne (Equity Center)
On:
Anderson, David (Texas Education Agency)
Dawn-Fisher, Lisa (Texas Education Agency)
Registering, but not testifying:
For:
Grusendorf, Bill (TX. Assoc. Rural Schools)
Perrin, John (Walcott ISD)
Sheets, Gene (Texas Association of Rural Schools - President/ Muleshoe ISD -
Superintendent)
For:
Golsan, James (Texas Public Policy Foundation)
Against:
Melina Raab, Ted (Texas AFT (American Federation of Teachers))
On:
Bosse, Portia (Texas State Teachers Assn.)
Brownson, Amanda (Texas School Alliance)
Givens, Anita (Texas Education Agency)
Gregg, Brock (Association of TX Professional Educators)
4
WITNESS LIST
On:
Shields, Julie (Texas Assoc. of School Boards)
Williams, Paige (Texas Classroom Teachers Association)
Registering, but not testifying:
For:
Erben, Andrew (TX. Institute for Education Reform)
Salinas, Nelson (The Texas Assoc. of Business)
Weinberg, Tracy (Texas Association for the Gifted & Talented)
5


Welcom to InternetBlogCo!
I’m glad that you guys have liked and supported the theme to reach 100 stars on Github. I would like to thank everyone who has supported the theme by using, starring and recommending it.
You can still do it if you haven’t yet,
Thank you!


A common approach
A common approach when utilizing the module pattern or something close to it, is to attach the end object to the window
, or return the object inside some sort of local variable to create a namespace for your module.
So you might end up having something like this:
Of course, the obvious problems with this are:
- You attach a lot of stuff to the global scope (this can be overcome with various techniques, though)
- You have to get the order of your
<script>
tags pretty exact (we’re pretending we’re not using a task runner here, like gulp)
… and probably several other I’m forgetting about. There are other ways to do this (a popular library like RequireJS, for example), but in my case, I wanted to try to use a basic object that would be attached to the window
, and have all of my dependencies attach to that global object.
A global dependencies object
For angular-state-manager, I utilized a global object called stateManagerDependencies
, or something along that line, to attach all of my modules to that would eventually go into the main stateManager
module.
The purpose of this was to only have one object (the stateManagerDependencies
object) be attached to the global scope (i.e. window
object), and that would hold all of the dependencies, as opposed to attaching each dependency to the global scope at the end of each module.
Obvious downsides to this approach
- You’re still attaching some strangely named global object to the
window
- In each module that depends on the
dependencies
object, there is no error-checking or method to list what modules are available inside thedependencies
object (a possible fix for this is to simply implement some of those methods, for example:.list()
, or.checkFor()
, etc.)


The information on this chart was taken from the following PDF file https://liveenergized.com/wp-content/uploads/2015/06/alkaline-food-chart-4.0.pdf and reflects their studies and finding.
Please note that one * marks that the food item is low in alkaline or acidity, two ** mark that the food item is medium in alkaline or acidity, and three *** mark that the food item is high in alkaline or acidity.
Beverages / Drinks
Alkaline List
- Almond Milk (unsweetened)*
- Carrot Juice (Fresh)*
- Chamomile Tea*
- Coconut Milk (unsweetened)*
- Grapefruit Juice*
- Lemon Juice*
- Tomato Juice (homemade)*
- Vegetable Juice***
- Water (Ionized)***
Acidic List
- Apple Cider Vinegar*
- Apple Juice*
- Coffee (Decaf)***
- Cola***
- Cow’s Milk***
- Goat’s Milk*
- Grape Juice**
- Hard Alcohol***
- Milk shake***
- Orange Juice**
- Rice Milk*
- Soft Drinks (Carbonated)***
- Soy Milk (Unsweetened)*
- Tap Water**
- Tea (black)**
- Tea (green)*
- Water (Most Bottled)**
- Wine(red)**
- Wine(white)***
Grains and Cereals
Alkaline List
- Brown Rice*
- Buckwheat Flour, Buckwheat Whole*
- Quinoa**
- Rice (Brown)*
- Whole Oats*
Acidic List
- Barley (Whole), Barley Flour**
- Corn (Processed)**
- Rice (White)*
- Wheat Flour (White), Wheat Flour (Whole)***
Nuts and Seeds
*All nuts and seeds on the list refers to the raw version.
Alkaline List
- Almonds**
- Cashews*
- Chestnuts*
- Flaxseed**
- Macadamia Nuts*
- Pine Nuts*
- Pumpkin Seeds**
- Sesame Seeds*
- Sunflower Seeds*
Acidic List
- Hazelnuts*
- Peanuts***
- Pecans*
- Pistachio Nuts*
- Soy Nut*
- Walnuts8
Fruits
Alkaline List
- Avocado***
- Grapefruit*
- Lemons**
- Limes**
- Olives (Green)*
- Pomegranates*
- Tomatoes**
- Watermelon*
Acidic List
- Apples**
- Apricots**
- Bananas**
- Berries (Black, Blue, Raspberry)*
- Cherries (Sour)*
- Cranberries*
- Dates (dried)***
- Grapes**
- Guava*
- Kiwi Fruit*
- Mangos**
- Oranges**
- Papayas*
- Peaches**
- Pears**
- Pineapples***
- Prunes***
- Raisins***
- Raspberries*
- Strawberries*
Vegetables
Alkaline List
- Artichokes**
- Asparagus***
- Beans (Black / Kidney / Lima / Navy)*
- Bell Pepper (Capsicum)***
- Broccoli***
- Brussels Sprouts**
- Cabbage (Red, White)**
- Carrots*
- Cauliflower**
- Celery***
- Chards (Swiss)***
- Chickpeas*
- Collard Greens***
- Corn (Fresh)*
- Cucumber***
- Dill Weed**
- Eggplant**
- Garlic*
- Ginger***
- Jerusalem Artichokes**
- Kale***
- Kohlrabi***
- Lentils*
- Lettuce (Leaf, Romaine)***
- Onions*
- Parsley***
- Peas*
- Pinto Beans*
- Potatoes (with Skin)*
- Spinach***
- Spring Onion**
- Squash*
- Sprouts***
- Watercress***
- Zucchini**
Acidic List
- Cantaloupe*
- Mushrooms***
- Rhubarb*
- Yams*
Various Foods
Alkaline List
- Almond Butter**
- Avocado Oil*
- Coconut Oil**
- Egg (Any Part)***
- Flaxseed Oil**
- Seaweed***
- Olive Oil*
- Salt (Sea, Himalayan)**
- Sesame Oil*
- Tahini Sauce*
Acidic List
- Apple Cider Vinegar*
- Balsamic Vinegar***
- Butter (Regular)**
- Canola Oil**
- Chocolate (Dark > 80%)*
- Chocolate (Milk)***
- Cacao (Raw)**
- Peanut Butter***
- Salt (Table)***
- Soybean Oil*
- Sunflower Oil*
- Tempeh (Fermented)*
- Tofu (Fermented)*
- Vegetable Oils (Most)**
Processed Foods
Alkaline List
- Hummus (Homemade)**
- Tomato Paste (Natural)*
Acidic List
- Corn Chips**
- Couscous (White Flour)**
- Crackers (White Flour)***
- French Fries***
- Ketchup***
- Mayonnaise***
- Mustard (Prepared)*
- Noodles (Most)***
- Pastrami***
- Popcorn (Salted)*
- Potato Chips (Baked, Fried)***
- Salad Dressing (Shop Bought)**
- Soy Sauce**
Baked Products
Acidic List
- Bagels***
- Baked Potato*
- Biscuits (Most)***
- Pita (White Flour)***
- Pretzels***
- Tortillas***
- Whole Wheat Bread**


[all packages]
[package ]
[class hierarchy]
[index]
public abstract class Grapher
(source file: Grapher.java)
java.lang.Object
|
+----Grapher
The pure class interface.
public abstract class Grapher
-
A class of `places that graphs can be drawn'. This is implemented
either using AWT calls to a graphics context, or with a PostScript
back end (all this stuff predates AWT1.1 PrintGraphics contexts).
- Author:
- Alan Jeffrey
- Version: v1.0 1998/06/11
- Grapher()
-
- black()
-
Set the colour to black.
- blue()
-
Set the colour to blue.
- close()
-
Close the output stream (if there is one).
- drawArrow(int, int, int, int)
-
Draw an arrow.
- drawCircle(int, int)
-
Draw a circle.
- drawDot(int, int)
-
Draw a dot.
- drawLine(int, int, int, int)
-
Draw a line.
- drawRectangle(int, int, int, int)
-
Draw a rectangle.
- drawText(int, int, String)
-
Draw some text.
- drawUTurn(int, int, int, int)
-
Draw a uturn
- purple()
-
Set the colour to purple (well, magenta actually).
- red()
-
Set the colour to red.
- setColour(PremonCat)
-
Set the appropriate colour for a given category
(blue for val, purple for central, red for
Grapher
public Grapher();
drawLine
public abstract void drawLine(int llX,
int llY,
int urX,
int urY);
-
Draw a line.
- Parameters:
- llX - the lower left x coordinate.
- llY - the lower left y coordinate.
- urX - the upper right x coordinate.
- urY - the upper right y coordinate.
drawArrow
public abstract void drawArrow(int llX,
int llY,
int urX,
int urY);
-
Draw an arrow.
- Parameters:
- llX - the lower left x coordinate.
- llY - the lower left y coordinate.
- urX - the upper right x coordinate.
- urY - the upper right y coordinate.
drawRectangle
public abstract void drawRectangle(int llX,
int llY,
int urX,
int urY);
-
Draw a rectangle.
- Parameters:
- llX - the lower left x coordinate.
- llY - the lower left y coordinate.
- urX - the upper right x coordinate.
- urY - the upper right y coordinate.
drawText
public abstract void drawText(int x,
int y,
String text);
-
Draw some text.
- Parameters:
- x - the left-hand x coordinate.
- y - the baseline y coordinate.
- text - the text to draw.
drawCircle
public abstract void drawCircle(int x,
int y);
-
Draw a circle.
- Parameters:
- x - the centre x coordinate.
- y - the centre y coordinate.
drawDot
public abstract void drawDot(int x,
int y);
-
Draw a dot.
- Parameters:
- x - the centre x coordinate.
- y - the centre y coordinate.
drawUTurn
public abstract void drawUTurn(int bot,
int left,
int top,
int right);
-
Draw a uturn
- Parameters:
- bot - the lower y coordinate.
- left - the left x coordinate.
- top - the upper y coordinate.
- right - the right x coordinate.
black
public abstract void black();
-
Set the colour to black.
blue
public abstract void blue();
-
Set the colour to blue.
purple
public abstract void purple();
-
Set the colour to purple (well, magenta actually).
red
public abstract void red();
-
Set the colour to red.
close
public abstract void close();
-
Close the output stream (if there is one).
setColour
public void setColour(PremonCat C);
-
Set the appropriate colour for a given category
(blue for val, purple for central, red for proc).
- Parameters:
- C - the category.
[all packages]
[package ]
[class hierarchy]
[index]
Grapher.html


Inserting & Modifying Data
SQLite
- How Do You Create Databases in SQLite Studio?
- How Do You Create Tables?
-
How Do You
AUTOINCREMENT
IDs?
- Adding Unique Constraints
- INSERT, UPDATE & DELETE
Knex JS
- What is Knex?
- Why Use Knex?
- How Do You Set Up Knex?
- CRUD Operations With Knex In a Node/Express Apps


This component is an inline element used to designate a plain-text editing control containing multiple lines.
It is useful for creating a form field for users to leave comments, messages or a description.
A very good example of using this component and the other form components can be found here:


fake-data (11)
- A simple ggplot of some measure against depth - September 10, 2018
- Paired line plots - January 22, 2019
- The statistical significance filter - April 17, 2019
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST -- Update - May 30, 2019
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
- What is the consequence of a Shapiro-Wilk test-of-normality filter on Type I error and Power? - August 8, 2019
- A comment on the novel transformation of the response in " Senolytics decrease senescent cells in humans: Preliminary report from a clinical trial of Dasatinib plus Quercetin in individuals with diabetic kidney disease" - October 2, 2019
- Normalization results in regression to the mean and inflated Type I error conditional on the reference values - October 16, 2019
- Using Wright's rules and a DAG to compute the bias of an effect when we measure proxies for X and Y - February 7, 2020
- Analyzing longitudinal data -- a simple pre-post design - March 19, 2020
- Bootstrap confidence intervals when sample size is really small - June 1, 2020
nhst (9)
- On alpha - April 23, 2018
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST - January 7, 2019
- Should we be skeptical of a "large" effect size if p > 0.05? - May 28, 2019
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST -- Update - May 30, 2019
- What does cell biology data look like? - June 9, 2019
- Is the power to test an interaction effect less than that for a main effect? - July 2, 2019
- What is the consequence of a Shapiro-Wilk test-of-normality filter on Type I error and Power? - August 8, 2019
- Analyzing longitudinal data -- a simple pre-post design - March 19, 2020
- What is the consequence of normalizing by each case in the control? - May 18, 2020
p-values (9)
- What is the range of reasonable P-values given a two standard error difference in means? - March 18, 2018
- Textbook error 101 -- A low p-value for the full model does not mean that the model is a good predictor of the response - September 11, 2018
- The statistical significance filter - April 17, 2019
- Should we be skeptical of a "large" effect size if p > 0.05? - May 28, 2019
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST -- Update - May 30, 2019
- Is the power to test an interaction effect less than that for a main effect? - July 2, 2019
- What is the consequence of a Shapiro-Wilk test-of-normality filter on Type I error and Power? - August 8, 2019
- Can a linear model reproduce a Welch t-test? - October 27, 2019
- What is the consequence of normalizing by each case in the control? - May 18, 2020
categorical-x (8)
- Interaction plots with ggplot2 - October 15, 2018
- Covariate adjustment in randomized experiments - April 12, 2019
- Is the power to test an interaction effect less than that for a main effect? - July 2, 2019
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
- Linear models with a covariate ("ANCOVA") - October 21, 2020
- How to estimate synergism or antagonism - November 3, 2020
- What is an interaction? - November 4, 2020
- How to make plots with factor levels below the x-axis (bench-biology style) - December 27, 2020
ancova (7)
- Bias in pre-post designs -- An example from the Turnbaugh et al (2006) mouse fecal transplant study - March 8, 2018
- Covariate adjustment in randomized experiments - April 12, 2019
- Blocking vs. covariate adjustment - April 27, 2019
- Normalization results in regression to the mean and inflated Type I error conditional on the reference values - October 16, 2019
- Analyzing longitudinal data -- a simple pre-post design - March 19, 2020
- ANCOVA when the covariate is a mediator affected by treatment - July 12, 2020
- Linear models with a covariate ("ANCOVA") - October 21, 2020
anova (6)
- Is the power to test an interaction effect less than that for a main effect? - July 2, 2019
- Estimate of marginal ("main") effects instead of ANOVA for factorial experiments - November 29, 2019
- Type 3 ANOVA in R -- an easy way to publish wrong tables - October 23, 2020
- How to estimate synergism or antagonism - November 3, 2020
- What is an interaction? - November 4, 2020
- How to make plots with factor levels below the x-axis (bench-biology style) - December 27, 2020
generalized-linear-models (6)
- Should the model-averaged prediction be computed on the link or response scale in a GLM? - May 13, 2018
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST - January 7, 2019
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST -- Update - May 30, 2019
- What does cell biology data look like? - June 9, 2019
- "Nested" random factors in mixed (multilevel or hierarchical) models - November 30, 2019
- Bootstrap confidence intervals when sample size is really small - June 1, 2020
interaction (6)
- Interaction plots with ggplot2 - October 15, 2018
- Is the power to test an interaction effect less than that for a main effect? - July 2, 2019
- Estimate of marginal ("main") effects instead of ANOVA for factorial experiments - November 29, 2019
- How to estimate synergism or antagonism - November 3, 2020
- What is an interaction? - November 4, 2020
- How to make plots with factor levels below the x-axis (bench-biology style) - December 27, 2020
effect-size (5)
- Combining data, distribution summary, model effects, and uncertainty in a single plot - March 27, 2018
- Reporting effects as relative differences...with a confidence interval - November 14, 2018
- Should we be skeptical of a "large" effect size if p > 0.05? - May 28, 2019
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
- Normalization results in regression to the mean and inflated Type I error conditional on the reference values - October 16, 2019
linear-mixed-model (5)
- Reanalyzing data from Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice - June 3, 2019
- Analyze the mean (or median) and not the max response - June 25, 2019
- Paired t-test as a special case of linear model and hierarchical (linear mixed) model - June 25, 2019
- "Nested" random factors in mixed (multilevel or hierarchical) models - November 30, 2019
- Analyzing longitudinal data -- a simple pre-post design - March 19, 2020
power (5)
- Should we be skeptical of a "large" effect size if p > 0.05? - May 28, 2019
- GLM vs. t-tests vs. non-parametric tests if all we care about is NHST -- Update - May 30, 2019
- Is the power to test an interaction effect less than that for a main effect? - July 2, 2019
- What is the consequence of a Shapiro-Wilk test-of-normality filter on Type I error and Power? - August 8, 2019
- Analyzing longitudinal data -- a simple pre-post design - March 19, 2020
causal-graph (4)
- Expected covariances in a causal network - January 3, 2019
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
- Using Wright's rules and a DAG to compute the bias of an effect when we measure proxies for X and Y - February 7, 2020
- ANCOVA when the covariate is a mediator affected by treatment - July 12, 2020
linear-model (4)
- Can a linear model reproduce a Welch t-test? - October 27, 2019
- ANCOVA when the covariate is a mediator affected by treatment - July 12, 2020
- Linear models with a covariate ("ANCOVA") - October 21, 2020
- What is an interaction? - November 4, 2020
microbiome (4)
- Bias in pre-post designs -- An example from the Turnbaugh et al (2006) mouse fecal transplant study - March 8, 2018
- Reanalyzing data from Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice - June 3, 2019
- Analyze the mean (or median) and not the max response - June 25, 2019
- Paired t-test as a special case of linear model and hierarchical (linear mixed) model - June 25, 2019
wright-style-path-analysis (4)
- Expected covariances in a causal network - January 3, 2019
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
- Using Wright's rules and a DAG to compute the bias of an effect when we measure proxies for X and Y - February 7, 2020
- ANCOVA when the covariate is a mediator affected by treatment - July 12, 2020
bias (3)
- Bias in pre-post designs -- An example from the Turnbaugh et al (2006) mouse fecal transplant study - March 8, 2018
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
- Normalization results in regression to the mean and inflated Type I error conditional on the reference values - October 16, 2019
model-averaged-coefficients (3)
- Model-averaged coefficients of a GLM - May 4, 2018
- An even more compact defense of coefficient model averaging - May 7, 2018
- On model averaging the coefficients of linear models - May 10, 2018
confidence-interval (2)
- Reporting effects as relative differences...with a confidence interval - November 14, 2018
- Bootstrap confidence intervals when sample size is really small - June 1, 2020
covariance (2)
- Expected covariances in a causal network - January 3, 2019
- What is the bias in the estimation of an effect given an omitted interaction term? - July 31, 2019
antagonism (1)
- How to estimate synergism or antagonism - November 3, 2020
blocking (1)
- Blocking vs. covariate adjustment - April 27, 2019
clda (1)
- Analyzing longitudinal data -- a simple pre-post design - March 19, 2020
correlation (1)
- Expected covariances in a causal network - January 3, 2019
covariates (1)
- Linear models with a covariate ("ANCOVA") - October 21, 2020
data.table (1)
- Melting a list of columns - April 27, 2020
glm (1)
- Model-averaged coefficients of a GLM - May 4, 2018
melt (1)
- Melting a list of columns - April 27, 2020
repeated-measures (1)
- Paired line plots - January 22, 2019
synergism (1)
- How to estimate synergism or antagonism - November 3, 2020


First IFA branches to cast presidential votes this evening
by Breifne O'BrienThe first votes will be cast by members of the Irish Farmers’ Association (IFA) this evening, Monday, November 25, to elect the organisation’s next president and deputy president.
Voting will take place at each of the IFA’s 944 local branch AGM’s and will be carried out on a ‘one member, one vote’ basis.
The branch AGM’s – and subsequent voting – will run until Friday, December 13, and it is hoped the new president and deputy president will be announced on Tuesday, December 17.
All IFA members are eligible to vote and to find out when your local branch meeting is, click here.
Running for the position of IFA president are:
- John Coughlan from the Buttevant branch in North Cork;
- Tim Cullinan from the Toomevara branch in North Tipperary;
- Angus Woods from the Barndarrig branch in Wicklow.
The candidates for IFA deputy president are:
- Thomas Cooney from the Laragh branch in Cavan;
- Brian Rushe from the Carbury/Cadamstown branch in Kildare.
IFA national returning officer Richard Kennedy has encouraged farmers to attend the association’s 944 branch meetings in the 29 county executives and vote for the positions of president and deputy president, saying:
Our presidential election gives every member the same say in choosing the next president of IFA.
“It’s an important exercise in democracy and it affords farmers across all enterprises, and in every part of the country, an equal voice in deciding who is best placed to represent Irish farmers 2020 onwards,” he said.
Among the branches voting on the opening night are: Goleen, West Cork; Aranmore Island, Donegal; Peterswell, Galway; Annascaul, Kerry; Ballyragget, Kilkenny; Walsh Island, Offaly; Knockcroghery, Roscommon; and Boolavogue, Wexford.


PIC:River baptism turns tragic as woman drowns after Madzibaba attempts to ra_pe her
by Sharon ChirisaRiver baptism turns tragic as woman drowns after Madzibaba attempts to ra_pe her
There are suspicions that a 26-year-old Gutu woman who slipped and drowned in a river met her tragic end after she tried to fight off a prophet who wanted to ra_pe her.
Priviledge Mabasa was found firmly clutching the self-styled prophet Benson Mutuzungara’s shirt in her hands when her body was retrieved by the Police from Mutorahuku River.
Masvingo Province Police spokesperson Assistant Inspector Kudakwashe Dhewa confirmed the tragedy to Masvingo Mirror.
The late’s uncle and family spokesperson Team Shereni Mabasa said Madzibaba Benson failed to explain why he removed his shirt when he was baptizing the deceased.
Madzibaba Benson claimed that a strong wind blew as he baptized the deceased and she slipped out of his hands, fell into the river and vanished .
A family spokesperson said elders agreed to bury Mabasa with the shirt clutched in her hands after they failed to remove it.
CHECK OUT THE TRENDING STORIES
BREAKING:Chief Ndiweni removed as chief with immediate effect
PHOTOS:The Day Jonathan Moyo Fled Zimbabwe During November 2017 Coup
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Woman who tried to save choking Wetherspoons pub diner claims staff were ill-prepared
"It was a sheer panic kind of cry"
by Tomas Malloy, Geoffrey BennettA woman who tried to save a man's life in a pub has claimed staff didn't know what to do.
But JD Wetherspoon, which runs The Palladium Electric in Midsomer Norton, has said staff did all they could to assist.
Kelly Cole was enjoying a family meal hours before the town carnival when she heard a man crying for help.
She told Somerset Live: "At first I thought it might have been a joke or a kid running around or something.
"Then I realized this was serious, it was a sheer panic kind of cry.
"I ran up to the man and started hitting him in the back from behind with my hand, and then he fell to the floor."
Ms Cole, who is first-aid trained, was guided on the phone by an ambulance call handler until paramedics arrived.
She says when the call handler asked if anyone knew CPR nobody knew what to do, so she stepped in.
She said: "I had to shout at the staff to stop letting customers into the pub as they were still letting people and children in and I didn't want people to walk in on what was happening.
"The staff were even still serving food at the time, there was a lady coming out with plates in her hands to serve to people.
"I find it disturbing that none of the staff there are first-aid trained - the manager told me that at the time.
"I personally think all staff should be first-aid trained at a place like that."
Sadly the man died after being taken to hospital.
JD Wetherspoon spokesman Eddie Gershon said: “First and foremost we send our sympathies to the family and friends of the customer who passed away.
“As soon as a member of staff was made aware of the man choking, staff and customers called the emergency services.
“The duty manager then spoke with the emergency services.
"He was guided through some procedures.
"A customer stepped in saying they were first-aid trained and started to give CPR until the paramedics arrived 5-10 minutes later and they then took over.
“At this time the duty manager started to clear the immediate area of customers and also stopped people coming into the pub."
'The family thanked the team for their efforts'
“The paramedics managed to revive the customer and then an air ambulance took the customer to hospital.
“The family of the customer called the pub the following day to say he had passed away and thanked the team for their efforts.
“We are confident that staff responded well to the situation and refute claims to the contrary.”
For the latest news in and around Bristol, visit and bookmark Bristol Live's homepage.


--- layout: page permalink: /tags title: All posts by Tags redirect_to: https://amnair.dev/tags --- {% for tag in site.tags%} {% assign tag_name = tag | first%} {% assign posts = tag | last %}


Existing Sensor Devices
- Low bandwidth communication
- Not designed to accommodate edge analytics
- Not designed to integrate sensor data with controller data
Controller Interface Software
- Proprietary
- Licensed
- Difficult user interface
- Requires Windows OS (Can't be used with embedded computers)
New Edge Device
- IoT-capable
- Capable of connecting to OPC-UA and MTConnect for controller data acquisition
- Capture and process high-frequency accelerometer data
- Capable of performing statistical classification algorithms
- Leverage open-source, royalty-free software
Case Study 1:
Georgia Tech Manufacturing Equipment
Case Study 1 Outline
- Setup Experiment
- Deploy edge device
- Deploy IoT architecture
- Generate benchmark toolpaths
- Perform Benchmark Study
- Execute benchmark toolpaths
- Create statistical model from cloud data
- Deploy model to the edge device
- Evaluate Model
- Execute additional toolpaths
- Perform model fit on edge
- Detect data changes due to tool health
Case Study 2:
Boeing Manufacturing Equipment
Case Study 2 Outline
- Setup Experiment
- Deploy edge device
- Deploy IoT architecture
- Perform Benchmark Study
- Record manufacturing data
- Create statistical model from cloud data
- Deploy model to the edge device
- Evaluate Model
- Perform model fit on edge
- Detect process variations due to recipe changes and part quality
Conclusion
- Formulate an IoT architecture which:
- Facilitates contextual machine health status
- Leverages both edge and cloud computing resources
- Demonstrate analytics on controller and sensor data in this framework:
- Bearing health
- tool wear
- process variation and uncertainty
- Evaluate Model
- Perform model fit on edge
- Detect process variations due to recipe changes and part quality
Accelerometer Data Acquisition
Microcontroller Flow Diagram
Sensor Kit
{"dateTime":"2019-03-08T15:43:44.808Z",
"assetId":"A1000",
"dataItemId":"Vibration",
"itemInstanceId": "Part_EPICS_1001",
"sensorId": "accelerometer1",
"samplingInterval":0.00048828125,
"values":[0.895,0.889,...,0.877]}
Sensor Kit
{"dateTime":"2019-08-20T11:23:35.704Z",
"assetId":"Okuma-Genos-3",
"dataItemId":"LS1Speed",
"value":"3024"}
Bearing Characteristics
- $n$ - number of rolling elements
- $\alpha$ - contact angle
Bearing Defect Frequencies
$$\begin{aligned}f_{bpi} &= n \frac{\mbox{RPM}}{2} \left ( 1 + \frac{D}{d_p} \cos{\alpha} \right )\\
f_{bpo} &= n \frac{\mbox{RPM}}{2} \left ( 1 - \frac{D}{d_p} \cos{\alpha} \right )\\
f_{bs} &= \mbox{RPM} \frac{d_p}{2D} \left [ 1 - \left ( \frac{D}{d_p} \cos{\alpha} \right )^2 \right ]\\
f_{ft} &= \frac{\mbox{RPM}}{2} \left ( 1 - \frac{D}{d_p} \cos{\alpha}\right )\end{aligned}$$
Root Mean Square
$$\mbox{RMS} = \sqrt{\dfrac{1}{n}\sum_{i=1}^{n}x^2_i}
$$
- Provides information on intensity of vibration
- As a bearing nears the end of its life, RMS value rapidly increases
Kurtosis
$$\mbox{Kurt} = \dfrac{\dfrac{1}{n}\sum_{i=1}^n(x_i - \bar{x})^4}{\left ( \dfrac{1}{n}\sum_{i=1}^n(x_i - \bar{x})^2 \right )^2} - 3
$$
- Provides information on impulsivity of vibration
- As a signal degrades, its kurtosis increases.
- A perfectly Gaussian signal will have a kurtosis of zero.
Spectral Kurtosis
- When a bearing defect manifests, it may cause amplitude modulation at very high frequencies.
- By analyzing the signal kurtosis at specific frequencies, it is possible to determine the bands in which this modulation occurs.
Background: Bearing Failure
Amplitude Demodulation
- This is a signal processing technique by which a highly modulated signal may be manipulated to reveal an underlying defect.
- The steps are as follows:
- Filter the signal about the modulating frequencies with a band-pass filter
- Rectify the filtered signal
- Use a low-pass filter to recover an envelope of the resulting signal
Background: Bearing Failure
Statistical Tools
- Bayes' Rule
- Clustering
- Kalman Filtering
- Dimensionality Reduction
- Control Charts
Background
Bayes' Rule
$P(A | B) = \dfrac{P(B|A) P(A)}{P(B)}$
Background: Statistical Tools


Welcome User, this is your dashboard where you may cast your votes. Don't forget to wash your hands
Some example text some example text. John Doe is an architect and engineer
See ProfileSome example text some example text. John Doe is an architect and engineer
See Profile


So we need goals. But then those goals can only come to fruition via process.
When the excitement of a new goal grows old, when the glitter wears off... what do you do?
There are no shortcuts or hacks to the performances we are after.
Do you focus on the next shiny thing that catches your eye? Do you choose comfort over discomfort? Or do you knuckle down and simply do the work.
There is only one real competitor and that is you against you. And you will be both your biggest supporter but also your biggest foe.
Folks want to know how to get mentally tough. We can read all the books we want, do written exercises etc. But real mental toughness only comes from choosing to be tough in the moment. Embracing to endure!
Coach wants you to do a 5 hour bike but weather is pants and turbo looms or when you're feeling tired or have every excuse under the sun. This is when you need to simply say screw it lets do it.
4k swim set!  Hey, guess what? Training is more often than not monotonous & boring. We don't always get to run in the trails with our friends on a glorious day or cycle on stunning roads with amazing scenery. But we are not in this for training 'entertainment'. We are in this to achieve the big audacious goals we have mapped out.
You are the obstacle.
Choose not to settle within the session when you are meant to be pushing it. I know there are some sessions I dread, but we (ahem, I) need to learn to deal mentally with each session. More power intervals then normal, so I will back off slightly as I mightn't be able to handle my usual wattage, No we say screw it let's do it. If we blow we blow. Don't be afraid to fail it!
Listen to you self chatter.. Is this sabatauging you?
A great goal this year is to find comfort in discomfort. Finding magic in the mundane. Embrace the sessions we dread.
Go ahead and dream or think big. But back that with bigger action and that does not mean epic 7 hour rides or hard track intervals it just means sticking to the consistency (day-in-day-out process) and working your mind every single opportunity you have.
Get after it.


Library
What's the ID of your withdrawal?.
New Return Date
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I worked on building CNN model for diagnosis of diabetic retinopathy. The research work is focused on design and implement effective and efficient deep learning models for Diabetic RetinopathY classification. Training time and model complexity was taken into consideration and a weekly supurvised annotation system was developed using saliency map techniques.
Research on applying sliding mode variable-structure control for active power filter to eliminate the nonlinear load imbalance feature which makes power system cause serious distortion of voltage waveform and current waveform and therefore improve the power quality dramatically.
Research Based Master in machine learning and deep learning area.
BENG majored in electrical and elelctronic engineering
UBC internation students award for research based graduate students.
Siyuan Scholarship for top 10% student in the EE department
Outstanding student award for high ranked students
“Gao is passionate about appled science problems and he always want to make this world better from enbineer side. As his cap stone project supervisor, I have communicated frequently with him since his second year in the Xi’an Jiaotong University. Such a history gives me full evidence about Gao’s performance in personality and academia. Gao won my trust almost at our first conversation. Gao is a hard-working research assistant with good problem-sloving skills and time management skills. He can always manage his coursework and research work very well and report his progress clearly and on time. His logic and analytical skills are impressive.”
Yingjie He, Associate Prof at XJTU“It is a special honor for me to recommend Mr.Gao Jiaxi for his future work.His solid problem-solving ability, team-work skills and rigorous attitude in research were the main reasons I accepted his invitation of being his referee.”
Yongmei Gan, Associate Prof at XJTU“I am working as an senior engineer in Xi’an Actionpower Electronics Company. During Mr.Gao’s internship in our company, I supervised his team’s research project. Gao’s outstanding theoretical capacity, leadership and English skill gave everyone a deep impression.”
Zheng Zhao, senior engineer at Xi’an Actionpower Electronics Company


class: center, middle, inverse, title-slide # Advanced plots and inference ## SISBID 2018
https://github.com/dicook/SISBID
### Di Cook (
<EMAIL_ADDRESS>,
@visnut
)
Heike Hofmann (
<EMAIL_ADDRESS>,
@heike_hh
) ### 07/25-27/2018 --- # Tidy data and random variables - The concept of tidy data matches elementary statistics - Tabular form puts variables in columns and observations in rows - Not all tabular data is in this form - This is the point of tidy data `$$X = \left[ \begin{array}{rrrr} X_1 & X_2 & ... & X_p \end{array} \right] \\ = \left[ \begin{array}{rrrr} X_{11} & X_{12} & ... & X_{1p} \\ X_{21} & X_{22} & ... & X_{2p} \\ \vdots & \vdots & \ddots& \vdots \\ X_{n1} & X_{n2} & ... & X_{np} \end{array} \right]$$` - `\(X_1 \sim N(0,1), ~~X_2 \sim exp(1) ...\)` --- # Grammar of graphics and statistics - A statistic is a function on the values of items in a sample, e.g. for `\(n\)` iid random variates `\(\bar{X}_1=\sum_{i=1}^n X_{i1}\)`, `\(s_1^2=\frac{1}{n-1}\sum_{i=1}^n(X_{i1}-\bar{X}_1)^2\)` - We study the behaviour of the statistic over all possible samples of size `\(n\)`. - The grammar of graphics is the mapping of (random) variables to graphical elements, making plots of data into statistics --- # Inference - Choice of plot implicitly sets `\(H_0\)`, `\(H_1\)` - Generically, we are thinking `\(H_0\)`: no pattern, `\(H_1\)`: pattern, but the choice of plot makes this much more explicit --- # Let's talk TB  There are many aspects of this plot, this is what we said earlier: - *Across all ages, and years, the proportion of males having TB is higher than females* - These proportions tend to be higher in the middle age groups, for all years. - Relatively similar proportions across years. --- # Null hypothesis The plot is constructed by plotting count against year, separately by age group, and coloured by gender. - By colouring by gender, we make this a primary comparison - Proportion of gender, conditional on age group and year is the query being addressed by this plot. *Null hypothesis*: TB incidence is spread equally among men and women, regardless of age and year. *Alternative hypothesis*: It isn't. --- ```r # Make expanded rows of categorical variables # matching the counts of aggregated data. # Gender needs to be converted to 0, 1 to # match binomial simulations tb_us_long <- expandRows(tb_us, "count") tb_us_long <- tb_us_long %>% mutate(gender01 = ifelse(gender=="m", 0, 1)) %>% select(-gender) # Generate a lineup of three, randomly choose one of the # positions to place true data. # Compute counts again. pos = sample(1:3, 1) l <- lineup(null_dist(var="gender01", dist="binom", list(size=1, p=0.5)), true=tb_us_long, n=3, pos=pos) l <- l %>% group_by(.sample, year, age) %>% dplyr::count(gender01) ``` ---  --- # More interesting null *Null hypothesis*: TB incidence is has the same proportion of men and women, regardless of age and year. *Alternative hypothesis*: It isn't. ```r # Compute proportion across all data tbl <- tb_us %>% group_by(gender) %>% summarise(count=sum(count)) tbl # A tibble: 2 x 2 gender count <chr> <int> 1 f 25915 2 m 55640 p <- tbl$count[1]/sum(tbl$count) pos = sample(1:3, 1) l <- lineup(null_dist(var="gender01", dist="binom", list(size=1, p=p)), true=tb_us_long, n=3, pos=pos) l <- l %>% group_by(.sample, year, age) %>% dplyr::count(gender01) ``` ---  --- # Important details - The null hypothesis is determined based on the plot type - It is not based on the structure seen in a data set --- # Lineup Embed the data plot in a field of null plots Ask: Which plot is the most different? --- # Evaluation - Computing `\(p\)`-values - Power `\(=\)` signal strength --- # p-values Suppose `\(x\)` individuals selected the data plot from a lineup of `\(m\)` plots, shown to `\(K\)` independent observers, then simplistically we can think about the probability of this happening, if the data plot is from the same distribution as the null plots. This yields a binomial formula: `$$P(X\geq x) = \sum_{i=x}^{K} \binom{K}{i} \left(\frac{1}{m}\right)^i\left(\frac{m-1}{m}\right)^{K-i}$$` For `\(x=4, K=17, m=20\)` ``` x simulated binom [1,] 4 0.0201 0.008800605 ``` --- # Simulation approach - Scenario I: in each of K evaluations a different data set and a different set of (m-1) null plots is shown. - Scenario II: in each of K evaluations the same data set but a different set of (m-1) null plots is shown. - Scenario III: the same lineup, i.e. same data and same set of null plots, is shown to K different observers. --- # Simulation Crucial idea: assign a p-value to each plot (data and null); under null hypothesis, this p-value is from U[0,1] Scenario I: - for the `\(k\)`th lineup evaluation do: - pick 20 `\(p\)`-values from `\(U[0,1]\)` - for data plot compute 'strength' of other plots: `\(q = (1-p_\text{data})/\sum_j(1-p_j)\)` - Use `\(q\)` to determine whether data was picked in simulation: `\(x_k \tilde B_{1,q}\)` - repeat above three steps `\(K\)` times, and find the number of data picks `\(X = \sum_k x_k\)` - Repeat N times to get distribution of `\(X\)` --- # Simulation Scenario II (same data, different nulls): - for the `\(k\)`th lineup evaluation pick 20 `\(p\)`-values from `\(U[0,1]\)`: - for data plot compute 'strength' of other plots: `\(q = (1-p_\text{data})/\sum_j(1-p_j)\)` - Use `\(q\)` to determine whether data was picked in simulation: `\(x_k \tilde B_{1,q}\)` - find the number of data picks `\(X = \sum_k x_k\)` - Repeat N times to get distribution of `\(X\)` --- # Simulation Scenario III (same data, same nulls): - for the `\(k\)`th lineup evaluation pick `\(p_\text{data} \sim U[0,1]\)`: - pick 19 `\(p\)`-values from `\(U[0,1]\)` - for data plot compute 'strength' of other plots: `\(q = (1-p_\text{data})/\sum_j(1-p_j)\)` - simulate number of data picks `\(X ~ B_{K, q}\)` - Repeat N times to get distribution of `\(X\)` --- # Null-generating mechanisms - Permutation: randomizing the order of one of the variables breaks association, but keeps marginal distributions the same - Simulation: from a given distribution, or model. Assumption is that the data comes from that model --- class: inverse middle # Your turn For these plot descriptions, decide on: - null hypothesis - null generating mechanism --- class: inverse middle # Your turn  --- class: inverse middle # Your turn  --- # More on making maps Make a choropleth map of the TB data across the globe. We will do something a little fancy first, by computing a linear regression model for each country, to extract the trend in TB counts. This trend will be used to colour the maps, to find the countries which have TB problems. A polygon map of the world is extracted from the maps package. *The names of countries needs to be synchronised between the TB data and the map data.* ```r world_map <- map_data("world") usa <- map_data("usa") tb_names <- tb %>% mutate(region=recode(country, "United States of America"="USA", "United Kingdom"="UK", "Russian Federation"="Russia")) ``` --- ```r # This is sophisticated code to compute the linear trend in counts # for each country. tb_names_inc <- tb_names %>% group_by(region) %>% nest() %>% mutate( model = purrr::map(data, ~ lm(count ~ year, data = .)) ) %>% unnest(model %>% purrr::map(broom::tidy)) %>% select(region, term, estimate) %>% spread(term, estimate) ``` --- One way to make the map is use `geom_map`, and link this dynamically with the TB data in the plotting code. ```r ggplot(tb_names_inc, aes(map_id = region)) + geom_map(aes(fill=year), map = world_map, color="grey70", size=0.3, na.rm=TRUE) + expand_limits(x = world_map$long, y = world_map$lat) + theme_few() + scale_fill_viridis("trend") + theme(legend.position = "bottom", axis.ticks = element_blank(), axis.title = element_blank(), axis.text = element_blank()) + guides(fill = guide_colorbar(barwidth = 15, barheight = .5)) ```  --- Another approach is to join the polygon data with the TB data. ```r tb_map <- left_join(world_map, tb_names_inc, by="region") ggplot(tb_map) + geom_polygon(aes(x=long, y=lat, group=group, fill=year)) + theme_few() + scale_fill_viridis("trend", na.value = "grey70") + theme(legend.position = "bottom", axis.ticks = element_blank(), axis.title = element_blank(), axis.text = element_blank()) + guides(fill = guide_colorbar(barwidth = 15, barheight = .5)) ```  --- class: inverse middle # Your turn Why is India showing a drastically increasing TB incidence. Make the plot of TB incidence for India. --- ```r tb_india <- tb %>% filter(country == "India") %>% filter(!(age %in% c("04", "014", "514", "u"))) %>% filter(year > 1996, year < 2013) %>% group_by(year, country) %>% summarise(count = sum(count, na.rm=TRUE)) india_map <- world_map %>% filter(region == "India") tb_map_india <- left_join(india_map, tb_india, by=c("region"="country")) %>% filter(group == 839) ``` ---  --- # Animate ```r p <- ggplot(tb_map_india) + geom_polygon(aes(x=long, y=lat, group=group, fill=count, label=region, frame=year)) + theme_few() + scale_fill_viridis("trend", na.value = "grey70", limits=c(0,630000)) + theme(legend.position = "bottom", axis.ticks = element_blank(), axis.title = element_blank(), axis.text = element_blank()) + guides(fill = guide_colorbar(barwidth = 15, barheight = .5)) ``` ```r ggplotly(p) ``` --- # Resources - Hofmann, H., Follett, L., Majumder, M. and Cook, D. (2012) Graphical Tests for Power Comparison of Competing Designs, http://doi.ieeecomputersociety.org/10.1109/TVCG.2012.230. - Wickham, H., Cook, D., Hofmann, H. and Buja, A. (2010) Graphical Inference for Infovis, http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.161. --- # Share and share alike This work is licensed under the Creative Commons Attribution-Noncommercial 3.0 United States License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/3.0/us/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.


"Changes and progress very rarely are gifts from above. They come out of struggles from below."
"Changes and progress very rarely are gifts from above. They come out of struggles from below."
"The biggest benefit of Apollo was the inspiration it gave to a growing generation to get into science and aerospace."


What is your age?
How many beans can you eat?
When are you available this summer?
When shall we have the meeting?
What month is your favorite?
What week is your favorite?
Set the time for your wifi fridge
What is your favourite color?
Choose an image to upload
75/100
30/100
75
25


It's true - cats may have an attitude. But they're also fluffy, fun-to-hold and soft. Here are some other fun facts about cats.
Did you know cats can't taste sweetness? Here are some treats they can't taste:
A small fried cake of sweetened dough, usually in the shape of a ring.
A sweet food that features sugar as the primary ingredient.
A carefully calculated motivational device that may or may not exist.


--- layout: archive title: Zulip Chat Archive permalink: /stream/116395-maths/topic/continuous.20functions.20into.20a.20topological.20X.20form.20an.20X.html ---
Do we already have
instance {α : Type u} {β : Type v} [topological_space α] [topological_space β] [has_mul β] : has_mul (subtype (@continuous α β _ _)) := ...
and all its friends available in mathlib?
Is there some efficient way to generate them all, if not?
We don't. We could hope to write a version of subtype_instance
/pi_instance
to get them, but I'm not sure the lemma naming convention are strong enough here
I guess it's actually pretty easy. You only have to do any work for has_add and has_mul; all the axioms are free.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


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Iterative Design Writeup
In this project, I worked in a group with 3 other UI/UX students. We took a startup's concept and created desktop website designs for that startup using an iterative design process.
We chose to create a laptop/desktop-friendly website for Strive School, a startup educational institution that aims to be the Lambda School of Europe.
Here's a short description of Strive School from Y Combinator's Summer 2020 Demo Day 1:
Strive School is building a Lambda School for Europe, leveraging income-share agreements to train software engineers who don't pay for the education until they get a job in the industry. Once a graduate lands a role, the ISA terms charge the person 10% of salary for four years with a maximum total of €18,000.
With this company blurb in mind, we had the following main goals for our website:
- Communicate the unique business model and curriculum of Strive School to prospective students
- Allow interest prospective students to easily create Strive School accounts and begin the admissions process
While creating the prototype and high-fi mock up of the website, we deliberately avoided looking at the startup's existing website so that we independently make our own design.
Our target audience was prospective students who were interested in starting software development careers without having to commit to traditional 4-year degrees. Thus, we did not include interfaces for enrolled students in our prototypes.
Too Long; Don't Want to Read
For impatient readers, here were my key takeaways from this project.
- It's really hard to design websites that are "exciting" and not plain when you're not a designer.
- Frequent feedback from independent parties helped us realize when we made unreasable assumptions about users visiting our product. For example, we initially provided inadequate description of what made our startup unique and desirable (i.e. income sharing agreement for education).
- Having each team member independently brainstorm design ideas greatly expanded the range of designs we considered in the early stages of sketching.
Now let's get to the nitty gritty details of this project!
Sketching and Wireframing
First, each group member made quick sketches of possible designs for the website. Each set of sketches included the following pages:
- Home Page: includes company introduction, catchy stats, link to admissions page/process
- Admissions Page: details admissions process, deadlines, includes link to sign up page/form
- Curriculum Page: includes various coding languages being offered by the company
Initial sketches are below. Click on any one of them to see the images at full size.
After creating our initial sketches, we compared each other's ideas and consolidated them into a final wireframe that contained the layouts that we like most.
We chose the design elements in the pages seen below for the following reasons:
- Home Page: In general, the goal we had in mind while designing this page was to get the user to apply to Strive School. Therefore, we made the "Apply Now" button very prominent: center on the screen and large in size. A person browsing the home page will likely only be on the page for a short while, so we put impressive statistics and prestigious companies on this page to succinctly provide flattering information to the user.
- Admissions Page: A timeline in Admissions page helps prosepctive students have a clear understanding of the admission process and be more confident on the sequence of steps for applying to the program.
- Curriculum Page: To give prospective students a broad overview of the technologies taught by courses in Strive School, we decided to list each topic out as cards grouped by curriculum track/focus. Clicking on each card would reveal more information about the respective technology (not implemented in the wireframe). We also wanted to emphasize that students could have choice in their Strive School learning experience.
Figma for final wireframe:
High Fidelity (Hi-fi) Mockup
Using our wireframe above, we got to work to create a hi-fi prototype of the webpage. We added additional pages to provide more information to the user, settled on a color scheme, and used varying font sizes and weights to draw the user's attention to certain aspects of the site.
Figma for hi-fi prototype:
Mockup Critique from Studio
Next, we presented our hi-fi prototype to other students and an industry critic in our studio for UIUX (CSCI 1300) by giving context for Strive School and walking through each page.
We collected the following points of feedback from our peers and industry critic.
- 'Apply Now' form should be a popup instead of modal so that users don't have to leave the page that they're on
- Make sure that 'Sign Up' page is GDPR compliant
- Allow users with accounts to log in; provide some sort of link or button for this
- Make the curriculum card modals scrollable
- Add more information/context on what Strive School is
- Add an About Us page
- Emphasize on home page and throughout website what differentiates Strive School from other coding bootcamps
Revised Hi-fi Prototype
With the feedback from the Studio Critique in mind, we updated our hi-fi prototype with the following revisions:
- Added a new 'Sign In' page, and renamed the Apply Now button in the navbar to 'Sign In'
- Added an 'About Us' page to give the startup more credibility
- Added a new section on the homepage to detail Strive School's unique business model
- Added additional checkboxes to 'Sign Up' page to better comply with GDPR
User Testing
To get a final round of feedback on our website prototype, we set up and executed user tests for 3 testers through the website UserTesting.
Each test in UserTesting consists of a scenario, which gives context to testers before they interact with the prototype, and a series of tasks that the testers perform and give audio feedback on.
Testing Setup
Scenario:
This interactive website prototype (NOT a real website) was created for a coding bootcamp startup, Strive School. A coding bootcamp is an intensive program that prepares students for entry-level software development careers. We want to inform prospective students on why Strive School is unique and why students should apply. Imagine you are someone who is interested in starting a new career in software engineering without going through a traditional 4 year university. **This is not an actual website but an interactive mockup made on prototyping software.
- Task 1: Without leaving the homepage, what are your initial impressions of the website? Explain your answer.
- Task 2: Imagine you are interested in starting an application to Strive School. Find the admissions process and navigate to a page where you can create a Strive School account.
- Task 3: Take as much time as you need to explore this website. Move on to the next task when you're ready.
- Task 4: Go to Google and find one other company that offers a similar service. Compare the two websites. State at least 2-3 differences. Which did you prefer? Why?
Link to the User Testing Videos: https://drive.google.com/drive/u/0/folders/1jOEnfGwVy2PF0MdfClRRi-2WG3rnNLBY
Feedback from Testers
Task 1: Homepage Impressions
- All three testers felt that the home page was plain and straightforward
- Some testers requested that the home page be more exciting and eye-catching
- It was not clear to one tester that there was more to the homepage than the top section with the image and
"Apply Now" button
- Requested smaller font
- Overall positive impression
- Analysis: Results were in line with our expectations, though we noted that it would likely be beneficial to include more information on the homepage.
Task 2: Finding Admissions Process and Sign Up Form
- Very straightforward task; all 3 testers completed the task quickly and without issue
- admissions page link and link to sign up pages were quickly found
- Analysis: Results were in line with our expectations. We consider this part of the test to be a great success.
Task 3: Website Exploration
- None of the 3 testers viewed all of the pages of the website
- Curriculum page
- Topic cards were not obviously clickable
- Some testers wished for more details on courses up front
- One tester thought that the fonts were boring and uniform across sections (requested more variety like bolding)
- A few testers did not feel that the curriculum page was exciting
- Some broken/confusing links threw off some testers
- About Us page was generally liked
- Gave more legitimacy to company
- Testers liked the pictures of employees on the page
- Analysis: We did discover a few things we might want to consider changing, but the results of this task were also largely in line with our expectations. Through the testers, we did discover a minor broken link ("Privacy Policy" being linked to the Terms and Conditions instead).
Task 4: Competitor Comparison
- Competing websites had more details on the homepage
- Other websites were flashier and more professional
- Only one tester noted the unique business model on the homepage
- Testers wanted our website to have more details on course timelines, dates, business model and tuition after graduation
- Analysis: Results were within our expectations. We had expected to not compare favorably with competitors in terms of pure design, but we noted that our website was light on course and business model details.
Potential Interface Changes
- More professional/exciting color palette and font choices
- More information about school curriculum on the homepage
- Responsive design to fit various laptop and desktop screens (website elements looked too big on smaller screens)
- In response to user who did not realize that they could scroll on the homepage because the top section filled their screen
- More animations and affordances to make clickable elements more clear (e.g. topic cards on the curriculum page)
- An explicit homepage link in the navbar (users were confused about how to return to the homepage from other pages)
- More details on timelines and dates on the admissions page and curriculum page


The smallest changes in population in the 1970s were on the east coast, and the provinces with the next smallest population changes were in the western provinces. Central Argentina seems to have changed the most, which is interesting because much of those provinces are devoted to farms and ranches.
There is a general trend of smaller to larger dams from south to north on the map, although the majority of dams are quite small (20k or less) and scattered relatively evenly throughout the state. It is also interesting to note the several large dams (200k or more) on the western border of the state.
There is a clear delineation between the smaller tracts around the center of the metropolitan area, and the larger tracts on the outskirts. On the outskirts there are many large areas of households that are both large and owner-occupied, where as in the center the tracts are more likely to be large and rented, small and owner, or small and rented. This probably has to do with high real estate prices closer to downtown.
The highest rates of precipitation are in the northeastern corner of the state, and the lowest are in the southwestern corner.
Minneapolis Census Tract Populations by Race in 2000
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Itaque earum nostrum suscipit ducimus nihil provident, perferendis rem illo, voluptate atque, sit eius in voluptates, nemo repellat fugiat excepturi! Nemo, esse.


--- layout: archive title: Zulip Chat Archive permalink: /stream/144837-PR-reviews/topic/.23717.20field_hom.html ---
@Kenny Lau I would like hear your thoughts. The PR seems like this wasn't too much of a change. Do you think it is fine/worth it? Or do you think we will hit roadblocks?
The main issue is the hierarchy of every ring hom is a group hom etc. I think what Cyril was talking about with unification hints might help here.
@Chris Hughes could you explain how rebasing and/or force-pushing is a bad idea?
Because then it's harder for me to see what has changed since I last looked at it. See https://github.com/leanprover-community/mathlib/compare/27883c109d31d3c8b7b6d49f09782b5ff3a89f94..52545586c6b32d58d353ed457367cf8ba768bfa4
The difference between two random commits is large?
Hey we have 1337 commits :-) Is that still a thing?
This is the PR that you force pushed, right?  I screwed up a PR recently (I rebased instead of merging when trying to update mathlib) and just decided to close and re-open.
You edited ring_theory/localization.lean
in November, and then the other day you told it that you edited src/ring_theory/localization.lean
in November, but that file wasn't even there in November. Or something.
Last updated: Apr 24 2020 at 19:02 UTC


Module helpers.file_tools
View Source
import json
def _find_my_yamls(myc_folder, specific_files=None):
"""Load all .yaml files in a folder or a specific list of yaml files."""
selected_files = []
if specific_files:
yaml_list = specific_files.replace(" ", "").split(",")
all_files = [myc_folder + yaml for yaml in yaml_list]
else:
all_files = glob.glob(myc_folder + "/*.yaml")
return all_files
def string_list_writer(file_name, list_holder, mode=None):
"""Writes an outfile froim a list of strings."""
if mode == None:
mode = "w"
with open(file_name, mode) as file:
for line_str in list_holder:
file.write(line_str + "\n")
def simple_text_writer(file_name, text, mode=None):
"""
Writes an outfile froim a list of strings.
Mode = r, w, etc str.
"""
if mode == None:
mode = "w"
with open(file_name, mode) as file:
file.write(text)
def load_local_json2(data_file):
"""Return data from compact json file on a line-by-line basis."""
for line in data_file:
json_thing = json.loads(line)
return json_thing
def load_local_json_generator(data_file):
"""Return data from compact json file on a line-by-line basis. Generator"""
for line in data_file:
json_thing = json.loads(line)
yield json_thing
Functions
load_local_json2
def load_local_json2(
data_file
)
Return data from compact json file on a line-by-line basis.
View Source
def load_local_json2(data_file):
"""Return data from compact json file on a line-by-line basis."""
for line in data_file:
json_thing = json.loads(line)
return json_thing
load_local_json_generator
def load_local_json_generator(
data_file
)
Return data from compact json file on a line-by-line basis. Generator
View Source
def load_local_json_generator(data_file):
"""Return data from compact json file on a line-by-line basis. Generator"""
for line in data_file:
json_thing = json.loads(line)
yield json_thing
simple_text_writer
def simple_text_writer(
file_name,
text,
mode=None
)
Writes an outfile froim a list of strings. Mode = r, w, etc str.
View Source
def simple_text_writer(file_name, text, mode=None):
"""
Writes an outfile froim a list of strings.
Mode = r, w, etc str.
"""
if mode == None:
mode = "w"
with open(file_name, mode) as file:
file.write(text)
string_list_writer
def string_list_writer(
file_name,
list_holder,
mode=None
)
Writes an outfile froim a list of strings.
View Source
def string_list_writer(file_name, list_holder, mode=None):
"""Writes an outfile froim a list of strings."""
if mode == None:
mode = "w"
with open(file_name, mode) as file:
for line_str in list_holder:
file.write(line_str + "\n")


|
IoTivity-Lite
|
#include "messaging/coap/coap.h"
#include "messaging/coap/transactions.h"
#include "oc_helpers.h"
#include "oc_ri.h"
#include "port/oc_connectivity.h"
Enumerations | |
| enum | oc_blockwise_role_t { OC_BLOCKWISE_CLIENT = 0, OC_BLOCKWISE_SERVER } |
| role of the transer More... | |
Functions | |
| oc_blockwise_state_t * | oc_blockwise_alloc_request_buffer (const char *href, size_t href_len, oc_endpoint_t *endpoint, oc_method_t method, oc_blockwise_role_t role) |
| allocate the request buffer More... | |
| oc_blockwise_state_t * | oc_blockwise_alloc_response_buffer (const char *href, size_t href_len, oc_endpoint_t *endpoint, oc_method_t method, oc_blockwise_role_t role) |
| allocate the response buffer More... | |
| const void * | oc_blockwise_dispatch_block (oc_blockwise_state_t *buffer, uint32_t block_offset, uint32_t requested_block_size, uint32_t *payload_size) |
| send the block More... | |
| oc_blockwise_state_t * | oc_blockwise_find_request_buffer (const char *href, size_t href_len, oc_endpoint_t *endpoint, oc_method_t method, const char *query, size_t query_len, oc_blockwise_role_t role) |
| find request buffer based on more information More... | |
| oc_blockwise_state_t * | oc_blockwise_find_request_buffer_by_client_cb (oc_endpoint_t *endpoint, void *client_cb) |
| find the request by client callback & endpoint More... | |
| oc_blockwise_state_t * | oc_blockwise_find_request_buffer_by_mid (uint16_t mid) |
| find the blockwise request based on mid More... | |
| oc_blockwise_state_t * | oc_blockwise_find_request_buffer_by_token (uint8_t *token, uint8_t token_len) |
| find the request by token More... | |
| oc_blockwise_state_t * | oc_blockwise_find_response_buffer (const char *href, size_t href_len, oc_endpoint_t *endpoint, oc_method_t method, const char *query, size_t query_len, oc_blockwise_role_t role) |
| find response buffer based on more information More... | |
| oc_blockwise_state_t * | oc_blockwise_find_response_buffer_by_client_cb (oc_endpoint_t *endpoint, void *client_cb) |
| find the response by client callback & endpoint More... | |
| oc_blockwise_state_t * | oc_blockwise_find_response_buffer_by_mid (uint16_t mid) |
| find the blockwise response based on mid More... | |
| oc_blockwise_state_t * | oc_blockwise_find_response_buffer_by_token (uint8_t *token, uint8_t token_len) |
| find the response by token More... | |
| void | oc_blockwise_free_request_buffer (oc_blockwise_state_t *buffer) |
| free the request buffer More... | |
| void | oc_blockwise_free_response_buffer (oc_blockwise_state_t *buffer) |
| free the response buffer More... | |
| bool | oc_blockwise_handle_block (oc_blockwise_state_t *buffer, uint32_t incoming_block_offset, const uint8_t *incoming_block, uint32_t incoming_block_size) |
| handle the incomming block (partial message) More... | |
| void | oc_blockwise_scrub_buffers (bool all) |
| free all blocks that are handled (refcount = 0) More... | |
| void | oc_blockwise_scrub_buffers_for_client_cb (void *cb) |
| scrub blocks for client side More... | |
| enum oc_blockwise_role_t |
| oc_blockwise_state_t* oc_blockwise_alloc_request_buffer | ( | const char * | href, |
| size_t | href_len, | ||
| oc_endpoint_t * | endpoint, | ||
| oc_method_t | method, | ||
| oc_blockwise_role_t | role | ||
| ) |
allocate the request buffer
| href | the href |
| href_len | the href length |
| endpoint | the endpoint |
| method | method |
| role | the role (clien or server) |
| oc_blockwise_state_t* oc_blockwise_alloc_response_buffer | ( | const char * | href, |
| size_t | href_len, | ||
| oc_endpoint_t * | endpoint, | ||
| oc_method_t | method, | ||
| oc_blockwise_role_t | role | ||
| ) |
allocate the response buffer
| href | the href |
| href_len | the href length |
| endpoint | the endpoint |
| method | method |
| role | the role (clien or server) |
| const void* oc_blockwise_dispatch_block | ( | oc_blockwise_state_t * | buffer, |
| uint32_t | block_offset, | ||
| uint32_t | requested_block_size, | ||
| uint32_t * | payload_size | ||
| ) |
send the block
| buffer | the buffer (whole message) |
| block_offset | the block offset |
| requested_block_size | blocksize to be send |
| payload_size | the send payload size |
| oc_blockwise_state_t* oc_blockwise_find_request_buffer | ( | const char * | href, |
| size_t | href_len, | ||
| oc_endpoint_t * | endpoint, | ||
| oc_method_t | method, | ||
| const char * | query, | ||
| size_t | query_len, | ||
| oc_blockwise_role_t | role | ||
| ) |
find request buffer based on more information
| href | the href |
| href_len | the href lenght |
| endpoint | the endpoint |
| method | the method |
| query | the query parameters |
| query_len | the query lenght |
| role | the role (client or server) |
| oc_blockwise_state_t* oc_blockwise_find_request_buffer_by_client_cb | ( | oc_endpoint_t * | endpoint, |
| void * | client_cb | ||
| ) |
find the request by client callback & endpoint
| endpoint | the endpoint |
| client_cb | the callback |
| oc_blockwise_state_t* oc_blockwise_find_request_buffer_by_mid | ( | uint16_t | mid | ) |
find the blockwise request based on mid
| mid | the message id |
| oc_blockwise_state_t* oc_blockwise_find_request_buffer_by_token | ( | uint8_t * | token, |
| uint8_t | token_len | ||
| ) |
find the request by token
| token | the token |
| token_len | the token lenght |
| oc_blockwise_state_t* oc_blockwise_find_response_buffer | ( | const char * | href, |
| size_t | href_len, | ||
| oc_endpoint_t * | endpoint, | ||
| oc_method_t | method, | ||
| const char * | query, | ||
| size_t | query_len, | ||
| oc_blockwise_role_t | role | ||
| ) |
find response buffer based on more information
| href | the href |
| href_len | the href lenght |
| endpoint | the endpoint |
| method | the method |
| query | the query parameters |
| query_len | the query lenght |
| role | the role (client or server) |
| oc_blockwise_state_t* oc_blockwise_find_response_buffer_by_client_cb | ( | oc_endpoint_t * | endpoint, |
| void * | client_cb | ||
| ) |
find the response by client callback & endpoint
| endpoint | the endpoint |
| client_cb | the callback |
| oc_blockwise_state_t* oc_blockwise_find_response_buffer_by_mid | ( | uint16_t | mid | ) |
find the blockwise response based on mid
| mid | the message id |
| oc_blockwise_state_t* oc_blockwise_find_response_buffer_by_token | ( | uint8_t * | token, |
| uint8_t | token_len | ||
| ) |
find the response by token
| token | the token |
| token_len | the token lenght |
| void oc_blockwise_free_request_buffer | ( | oc_blockwise_state_t * | buffer | ) |
free the request buffer
| buffer | buffer to be freed |
| void oc_blockwise_free_response_buffer | ( | oc_blockwise_state_t * | buffer | ) |
free the response buffer
| buffer | buffer to be freed |
| bool oc_blockwise_handle_block | ( | oc_blockwise_state_t * | buffer, |
| uint32_t | incoming_block_offset, | ||
| const uint8_t * | incoming_block, | ||
| uint32_t | incoming_block_size | ||
| ) |
handle the incomming block (partial message)
| buffer | the whole message |
| incoming_block_offset | the block offset |
| incoming_block | the incomming block to be added |
| incoming_block_size | the size of the incomming block |
| void oc_blockwise_scrub_buffers | ( | bool | all | ) |
free all blocks that are handled (refcount = 0)
| all | : including ref count != 0 |
| void oc_blockwise_scrub_buffers_for_client_cb | ( | void * | cb | ) |
scrub blocks for client side
| cb |


Welcome to Valiant Gaming India, a network of Dota 2 tournaments set up by gamers, for gamers. We are a group united by one ambition; to turn eSports into the most exciting, diverse sport on the planet
The people who play games not just for the sake of gaming.


😀
Run Lighthouse after building to see the perfect scores!
* Browser extensions may negatively impact scores so run in incognito windowRun Lighthouse after building to see the perfect scores!
* Browser extensions may negatively impact scores so run in incognito window


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Error code seen in browser after using Admin > update & check button
Fatal error: Call to a member function fetch_object() on a non-object in /usr/share/emoncms/www/Modules/admin/update_class.php on line 67
I had seen this before while testing the debian packages but never got to the reason why it occurred. now that I seen it a few times I think there is a pattern. Is it possible this error is the result of initiating an "update & check" and there was no update to perform?
When I tried U&C (update & check) this morning on a out of date v8 pre-release I got the error
later I tried it on a v8 pre-release updated to v8.0.3-3 and still got the error
again on a fresh install of v8.0.3-3 the error occurred
BUT after installing the event module package I tried U&C and it did not error, it displayed the proposed updates which I agreed to, it then completed them without fault and displayed attached screenshot.
And then when I clicked "check for further updates" it resulted in the same error, which i now get again each time i click Admin > U&C button.
I haven't noticed any other related issues so I think functionally all is ok but this error message does crop up each time the U&C button is used.
Paul
Re: EmonCMS update & check error
Exactly the same situation here! I get this message every time I press 'Update&Check'.
Jörg.
Re: EmonCMS update & check error
Here a bit more info on this.
The issue is definitely linked to whether it thinks an update to the database is required. I tried it again on a fresh install of emoncms and got the same results ie one shot at U&C and yet using apt-get to remove and then reinstall the event module does not give you another go probably because the db/index is still there.
As a side note "My Electric Config" page appears to be dependent on being able to perform a U&C as on my original install i could not get the boxes to populate, but when i updated to v8.0.3-3 the couple of feeds i had previously created appeared in the dropdown box. But as I created more feeds the list remained the same and it wasn't until i installed the event module and was able to use U&C that the rest of my feeds appeared in the my electric dropdown boxes.
I assume the list is not getting updated and requires a manual U&C but that's not currently possible.( I think this may be part of the problem over on this thread as maybe the my elec boxes are just not populating)
Is there a way to trick emoncms into thinking it needs the U&C performed to test this theory?
Paul
Re: EmonCMS update & check error
I get the same error on a v8.0.3 shared linux host install. Other than this particular error, and not being able to make my feeds public (clicking the padlock icon has no effect) it appears to be working OK.
Bill
Re: EmonCMS update & check error
Problem solved for me after updating some files to V8.0.4!
Thank you very much, Trystan!
Re: EmonCMS update & check error
Yup! all fixed when I upgraded to v8.0.7 using apt
(very minor point the on-screen version still says v8.0.6 (from apt))
Paul
Re: EmonCMS update & check error
Unfortunately the debian packaging process just adds "(from apt)". I should probably introduce some kind of validation that errors out if it tries to build a version against a mis-matching tag?
Re: EmonCMS update & check error
In time im sure Il tag and update the version in the index.php file correctly :)
Re: EmonCMS update & check error
Hi.
I have emonCMS installed in a linux machine (server - not shared hosting). When I Update & Check I got a blank page like the one you can see in the attached file.
Re: EmonCMS update & check error
Hi Bruno, not sure exactly why you are getting that blank page but I can see somethings not quite right, the raspberrypi module, (and more recently the node nodule and myelectric modules) has been depreciated so you may have installed an out of date version and added a module that's no longer used. What guide did you follow?
Paul
Re: EmonCMS update & check error
Hi Paul!
I've followed the "Install Emoncms v8 on Ubuntu / Debian Linux" - https://github.com/emoncms/emoncms/blob/master/docs/LinuxInstall.md
I shouldn't had installed raspberry pi module, just realized that after it was done. I don't know how to uninstall modules :p
My Electric and Node modules are not used anymore?
Edit: Anyone? :)


The following programs of LearnOpenGl are implemented in javascript / typescript, using WebGl2. Not all browsers support WebGl2. The latest versions of Google Chrome and Windows Edge can be used to view the results.
Chapter 48 of the book that accompanies the site LearnOpenGl is about text. The C++ program accompanying the book uses the FreeType library to produce bitmaps and metrics for letters. When using programs in the html context many other options are available.
font 3D Using Earcut to triangulate font shapes


Traction: Book Review
Gabriel Weinberg and Justin Mare’s Traction: How Any Startup Can Achieve Explosive Customer Growth is a wonderful aggregation of interviews, insights, real-world trial and errors, and inspiration. It’s packed with information that is actionable and easy to stick in your back pocket for when you face interesting issues that you would never consider being prepared for.
I was interested in Traction not only because it was an interesting topic but also because I was heavily involved in DuckDuckGo — using the service, advocating the Instant Answer platform at meetups, and submitting code on their open source repos as a part of DuckDuckHack. To immerse myself more in the privacy, growth, and startup culture I figured what better way than to read the CEO’s book.
How to gain traction
There are a few ways your product can get traction, 19 actually. They’re:
- Blogs
One of the most popular forms of marketing and the most effective form of content marketing. Blogging helps users find your product or service based on similar issues, problems, and stories that you’re writing about.
- Publicity
This requires some spotlight — maybe even some finagling for the sake of fame. Publicity will come when you do something grand, speak with someone popular, or just shout in a crowded room. Most say that no publicity is bad publicity. If people are talking and you’re on their minds, they already care about you and your products at least a little.
- Unconventional PR
My main idea for this type of PR is following Y Combinator’s Paul Graham methodology of doing things that don’t scale. This might involve publicity stunts and even going door-to-door — things that clearly won’t work in the long run but that are somehow managing to get people looking at you right now.
- Search Engine Marketing
Clearly, yegg knows this topic very well. DDG does make revenue on advertising as do all search engines. If anyone tells you Google is in the business of cloud storage, Android phones, or video, you can tell them they’re not wrong but that they’d be more accurate if they simply said they’re in the advertising business. Everything else is just shiny products to deliver ads and it’s a great tool to use to gain some traction.
- Social and Display Ads
Banner ads
- Offline Ads
Think commercials and Times Square. I always feel Super Bowl ads get me hooked on products and love watching the new ways companies innovate with only a 30-second time slot.
- SEO
There are entire departments of tech companies that devote themselves to SEO. The reality is that sometimes you need to be at the top of the list for someone to click you and it’s very important you’re on the top of that list no matter what their original query was.
- Content Marketing
Ultimately similar to the blog tactic above but more granularly covering the main objective here which is to get people’s eyes on your content because it relates to them then selling them things.
- Email Marketing
A great way to reach your customer or user directly. Send them personalized notes and ultimately sell them stuff!
- Viral Marketing
Companies like Viral Loops have entire businesses based on helping you utilize this tactic. Dropbox is one of the largest case studies for Viral marketing. Getting free storage - which seems like a tangible and valuable thing - just for getting a friend to sign up for a service was an incredibly successful move by Dropbox and helped get them a large user base.
- Engineering
Building tools and products to help grow your brand is a great way to get more eyes on you and your products. If you’re writing a book on photography and build a photography app that helps take better pictures using some of the tactics you discuss in the book, it’s going to get people talking!
- Business Development
Sales but grander. Big things to keep in mind with this is that both parties have to come out happy. We help you integrate our service so your users can have more variety and easy access and in turn, we’re getting more traction because we’re available on more platforms.
- Sales
Instead of partnering with businesses like Business Development, you’re partnering with paying customers. Selling is important for any business that intends to create revenue and good sales approaches will ensure quality traction for your company and product.
- Affiliate Programs
Even if you never heard the word ‘affiliate’ you’ve probably been the victim of an Amazon affiliate link where someone got a commission from something you bought. It’s a solid example of how using other channels to provide access to another channel can be beneficial for multiple parties.
- Existing Platforms
Using apps and services that already have large user bases and audiences is a quick way of accessing many people at once. If you’re able to utilize someone else’s audience by providing them with information or any other value, you can shine a big ad on a lot of people.
- Trade Shows
This may seem old-fashioned if you’re heavily in the startup community glaring at your codebase all day, but there are many business owners, consumers, and everyone in between that attend trade shows just waiting to be hooked on your traction train.
- Offline Events
Similarly, events such as meetups and conferences offer huge and specialized audiences that can help grow a fanbase.
- Speaking Engagements
Sometimes within offline events and sometimes their own entity, if someone who is well-known is speaking at some public place you better believe people are flocking there - those are the people that can help gain traction.
- Community Building
As a Community Leader at DuckDuckGo, I can say for certain that I’ve gained friendships and partnerships with people and companies that are fans of the platform and that would love to assist in the future and who I wouldn’t hesitate to help either. Hosting and organizing events and gathering likeminded people is one of the most powerful ways to garner a community and gain traction.
Now that you’re illuminated with nearly twenty different tactics that can be used to get your business going, you’ll be glad to hear that it’s impossible to know which will be your most successful method. Testing will have to be done to help understand which is working well and which might be working better than expected. The idea is to hit every single option and track which areas are performing well. If billboards and speaking engagements are where you’re converting most often, it might be time to turn some of your copywriters into meetup organizers.
Product vs. Marketing
It may surprise you just how highly Traction regards marketing. Toward the start of the text, the 50% rule is introduced outlining how half of your time should focus on the product while an entire second half should be focused on marketing and ultimately getting traction. Some might glorify not focusing on traction because it would imply they have a superior product that didn’t require marketing, but Silicon Valley investors disagree. Marc Andreessen says:
The number one reason that we pass on entrepreneurs we’d otherwise like to back is focusing on product to the exclusion of everything else. We tend to cultivate and glorify this mentality in the Valley. We’re all enamored with lean startup mode. Engineering and product are key. There is a lot of genius to this, and it has helped create higher quality companies. But the dark side is that it seems to give entrepreneurs excuses not to do the hard stuff of sales and marketing. Many entrepreneurs who build great products simply don’t have a good distribution strategy. Even worse is when they insist that they don’t need one, or call no distribution strategy a “viral marketing strategy.”
We hear it all the time: “We’ll be like Salesforce.com—no sales team required, since the product will sell itself.” This is always puzzling. Salesforce.com has a huge, modern sales force. The tagline is “No software,” not “No sales.” AH is a sucker for people who have sales and marketing figured out.
It might sound outlandish or even trite depending on what your philosophies are, but traction and the methods of getting it are sometimes more important than the product itself. There’s a reason Apple, a company that makes products perfectly capable of "selling themselves", still has extremely well-paid marketing executives like Phil Schiller.
Meta Marketing
One of the best parts of the Traction book wasn’t even anything in the text but the metadata that the authors provide about how they sold the book and the different channels they used along the way. Even during the process of selling the book after launch and all the events, ad campaigns, and whatnot are documented in great detail and provide extremely insightful information.
Selling a book can be seen as a microcosm of starting a business. There are goals and metrics but just one product without any employees so it’s much easier to manage. Sharing the things like Amazon results, sources, and more truly provide value for someone who hasn’t gone through this rigamarole just yet. Similarly interesting is the insights provided about how many books were sold and on which platforms.
I do plan on using some of these same tactics on my own and when I have the opportunities to. I won’t be buying billboards for my mere blog posts but certainly see the value in other companies investing in things like that such as Snapchat in Times Square. The idea of tackling all facets of marketing and drilling into the ones that stick is a principle that can be applied to many things in business as well. I’m excited to use the ideas in Traction and can’t wait for any updated versions.
Gabriel Weinberg and Justin Mare’s Traction: How Any Startup Can Achieve Explosive Customer Growth was one of my very first startup books. Around the same time is when I picked up Nir Eyal’s Hooked and started idolizing figures like Ben Horowitz and other business gurus — I’m glad I’m part of it now.


Analyze repertory grids, a qualitative-quantitative data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across various domains ranging from clinical psychology to marketing. The package contains functions to quantitatively analyze and visualize repertory grid data (see e.g. Bell, 2005, <doi:10.1002/0470013370.ch9>; Fransella, Bell, & Bannister, 2004, ISBN: 978-0-470-09080-0).
| Version: | 0.1.12 |
| Imports: | methods, graphics, grid, utils, stats, grDevices, plyr, stringr, abind, rgl, colorspace, GPArotation, psych, XML, tcltk, pvclust, openxlsx |
| Published: | 2018-05-31 |
| Author: | Mark Heckmann [aut, cre] |
| Maintainer: | Mark Heckmann <heckmann.mark at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://openrepgrid.org, https://github.com/markheckmann/OpenRepGrid |
| NeedsCompilation: | no |
| Citation: | OpenRepGrid citation info |
| Materials: | NEWS |
| CRAN checks: | OpenRepGrid results |
| Reference manual: | OpenRepGrid.pdf |
| Package source: | OpenRepGrid_0.1.12.tar.gz |
| Windows binaries: | r-devel: OpenRepGrid_0.1.12.zip, r-release: OpenRepGrid_0.1.12.zip, r-oldrel: OpenRepGrid_0.1.12.zip |
| OS X binaries: | r-release: OpenRepGrid_0.1.12.tgz, r-oldrel: OpenRepGrid_0.1.12.tgz |
| Old sources: | OpenRepGrid archive |
Please use the canonical form https://CRAN.R-project.org/package=OpenRepGrid to link to this page.


public class DefaultRoomnumberSet extends java.lang.Object implements RoomnumberSet
| Modifier and Type | Field and Description |
|---|---|
STreeMap<java.lang.String,CMIntegerGrouper> |
root |
| Constructor and Description |
|---|
DefaultRoomnumberSet() |
| Modifier and Type | Method and Description |
|---|---|
void |
add(RoomnumberSet set)
Adds a set of room ids to this object
|
void |
add(java.lang.String str)
Adds the given room id to this object
|
int |
compareTo(CMObject o) |
boolean |
contains(java.lang.String str)
Returns whether the given room id is stored here
|
int[] |
convertRoomID(long coded) |
java.lang.String |
convertRoomID(java.lang.String prefix,
long coded) |
CMObject |
copyOf()
Similar to Cloneable.clone(), but does its best to make sure that
any internal objects to this class are also copyOfed.
|
java.util.Iterator<java.lang.String> |
getAreaNames()
Returns an enumerator for all area names in this object
|
CMIntegerGrouper |
getGrouper(java.lang.String areaName)
Returns the number parts of the room ids stored in this
object for a given area.
|
java.util.Enumeration<java.lang.String> |
getRoomIDs()
Returns an enumerator for all room ids in this object
|
java.lang.String |
ID()
The CoffeeMud Java Class ID shared by all instances of
this object.
|
void |
initializeClass()
Called ONCE after all objects are loaded, but before the map is read in
during initialization.
|
boolean |
isEmpty()
Returns whether any rooms at all are defined.
|
java.lang.String |
name()
The displayable name of this object.
|
CMObject |
newInstance()
Returns a new instance of this class.
|
void |
parseXML(java.lang.String xml)
Restores this object from an xml document
|
java.lang.String |
random()
Returns a random, fully qualified room id from those
stored in here.
|
void |
remove(java.lang.String str)
Removes a single room id from this object
|
int |
roomCount(java.lang.String areaName)
Returns the number of room ids stored for the
given Area name.
|
int |
roomCountAllAreas()
Returns the total number of room ids stored here
|
java.lang.String |
xml()
Converts the contents of this object into an xml
document.
|
public STreeMap<java.lang.String,CMIntegerGrouper> root
public DefaultRoomnumberSet()
public java.lang.String ID()
CMObject
public java.lang.String name()
CMObject
name
in interface CMObject
Environmental.Name()
public int compareTo(CMObject o)
compareTo
in interface java.lang.Comparable<CMObject>
public CMObject newInstance()
CMObject
newInstance
in interface CMObject
public void initializeClass()
CMObject
initializeClass
in interface CMObject
public CMObject copyOf()
CMObject
public void add(RoomnumberSet set)
RoomnumberSet
add
in interface RoomnumberSet
set
- the room ids to addpublic void remove(java.lang.String str)
RoomnumberSet
remove
in interface RoomnumberSet
str
- the room id to remove from this objectpublic int roomCountAllAreas()
RoomnumberSet
roomCountAllAreas
in interface RoomnumberSet
public boolean isEmpty()
RoomnumberSet
isEmpty
in interface RoomnumberSet
public int roomCount(java.lang.String areaName)
RoomnumberSet
roomCount
in interface RoomnumberSet
areaName
- the Area to count the rooms ofpublic java.lang.String random()
RoomnumberSet
random
in interface RoomnumberSet
public int[] convertRoomID(long coded)
public java.lang.String convertRoomID(java.lang.String prefix, long coded)
public java.util.Iterator<java.lang.String> getAreaNames()
RoomnumberSet
getAreaNames
in interface RoomnumberSet
public CMIntegerGrouper getGrouper(java.lang.String areaName)
RoomnumberSet
getGrouper
in interface RoomnumberSet
areaName
- the area name to look forCMIntegerGrouper
public boolean contains(java.lang.String str)
RoomnumberSet
contains
in interface RoomnumberSet
str
- the room id to look forpublic java.lang.String xml()
RoomnumberSet
xml
in interface RoomnumberSet
public void parseXML(java.lang.String xml)
RoomnumberSet
parseXML
in interface RoomnumberSet
xml
- contents for this object as an xmlpublic void add(java.lang.String str)
RoomnumberSet
add
in interface RoomnumberSet
str
- a room idpublic java.util.Enumeration<java.lang.String> getRoomIDs()
RoomnumberSet
getRoomIDs
in interface RoomnumberSet


|
BitMagic-C++
|
Encoding utilities for serialization (internal) More...
Go to the source code of this file.
Data Structures | |
| class | bm::encoder |
| Memory encoding. More... | |
| class | bm::decoder_base |
| Base class for all decoding functionality. More... | |
| class | bm::decoder |
| Class for decoding data from memory buffer. More... | |
| class | bm::decoder_little_endian |
| Class for decoding data from memory buffer. More... | |
| class | bm::bit_out< TEncoder > |
| Byte based writer for un-aligned bit streaming. More... | |
| class | bm::bit_in< TDecoder > |
| Byte based reader for un-aligned bit streaming. More... | |
| class | bm::gamma_encoder< T, TBitIO > |
| Functor for Elias Gamma encoding. More... | |
| class | bm::gamma_decoder< T, TBitIO > |
| Elias Gamma decoder. More... | |
Namespaces | |
| bm | |
Typedefs | |
| typedef decoder | bm::decoder_big_endian |
| Class for decoding data from memory buffer. More... | |
Encoding utilities for serialization (internal)
Definition in file encoding.h.


Data Fields | |
| int | iSize |
| Must be set to sizeof( ADLMVPUCaps ). | |
| int | iAdapterCount |
| Number of adapters. | |
| int | iPossibleMVPUMasters |
| Bits set for all possible MVPU masters. MVPU_ADAPTER_0 .. MVPU_ADAPTER_3. | |
| int | iPossibleMVPUSlaves |
| Bits set for all possible MVPU slaves. MVPU_ADAPTER_0 .. MVPU_ADAPTER_3. | |
| char | cAdapterPath [4][256] |
| Registry path for each adapter. |
This structure is used to store information about MultiVPU capabilities. This structure is used by the ADL_Display_MVPUCaps_Get() function.
Must be set to sizeof( ADLMVPUCaps ).
Number of adapters.
Bits set for all possible MVPU masters. MVPU_ADAPTER_0 .. MVPU_ADAPTER_3.
Bits set for all possible MVPU slaves. MVPU_ADAPTER_0 .. MVPU_ADAPTER_3.
| char ADLMVPUCaps::cAdapterPath[4][256] |
Registry path for each adapter.