Emotions, Biosensors, Signals & Control system

Picture: Emotions Mapped In The Human Body, 'Most Accurate' Visualization Of Emotion-Related Bodily Sensations

Basic actions: Do, Feel, Control, Contribute

Genre: Horror (Fear), Tragedy (Sorrow), Humor (Happiness), Romance (Love), Action (Courage), Hero (Pride),

Research: Fundamental (understand), Applied (use),


Bio receptors



Picture: Sensors; Biological-Chemical-Physical, Bio-sensors, Bio-transducer, Slideshare

To transduce: to convert (as energy or a message) into another form <essentially sense organs transduce physical energy into a nervous signal>. Latin transducere to lead across, transfer, from trans- + ducere to lead


Example: Gut-feeling = To smell the right way 
"Cells have an infallible sense of smell that tells them which direction to grow in to move closer to the source of a scent. Now, researchers have now learned how this sense of smell works."

Picture: The PS (polarity site, yellow traces) is a Sensor, Processor and Motor all in one – a multi-fuctional instrument that controls cell growth and movement. Source

"A frequent problem faced by cells is that they are surrounded by a promising cloud of scent and must determine the direction of its source. Nerve cells, for example, form long extensions that are attracted to signals from other cells in order to produce the network that forms the nervous system; similarly, scavenger cells recognise the scent of harmful germs in order that they can pursue and destroy them."

"The essential components of the machinery include; 
1) Protein Cdc42 (the Wheel) , which carries Receptors (the Nose, forwards the signal ) on the membrane. 
2) Protein Cdc24 (the Brake) 
PS is moving across the cell membrane and looking for a stronger chemical signal. PS then creates a bulge in the cell at this location, which continues to grow towards the source of the signal
"The computer mode helped us to reduce the complexity to a few essential components"

Control systems

 
Picture: Basic control system.


Matching (to target) system
 
Picture: PID-controller (Proportional (height), Integral–derivative

Picture: Negative feedback system - Set Points promotes stability. Positive feedback accelerates

Picture: Controller takes the signal, compares with the Set-Point, and gives a recommendation
Homeostasis: to be in balance/equilibrium link



Picture: Reflex (self control) bypass the slower Central Control (spinal cord).


Signals: Conveys information (message), Signal-processing
Noice is an unwanted signal.
Any signal can be categorised/labeled - sampled into "accounts".

Blogs: Data/Information Visualisation, Signal book (Stephen Fry)


Philosophy now oct/nov-2015 (page 12)
The above is also valid within Philosophy/Sociology/Psychology

Two views:
* Freedom from restrictions - right to deviate
* Protection from deviations
Bell curve - the mountain


Deviate from the Norm
a) external motivation - requires energy
     To drift into a Norm - least resistance (unreflectively imitate others)
b) internal motivation - less energy
Bell curve - the valley (depressions)

Individuals are most likely to be their own best judge. Also the most motivated.
But some needs help (f.e. to protect their rights)
...


Good Communication/Signal --> Cells live longer --> Longer/Happier Life

Summary: Good (quality) Relationships makes you live longer = Good Communication/Signals



Addictions (drugs, media, etc) is a substitute for Low Quality Connections


+

Our Outlier-actions doesn't always define us.
Terrorists, creates fear in minorities.
Poverty is the opposite of Justice.

Asteroids that Hit Earth last 20yrs - Threat/Opportunity

Picture: All asteroids that hit earth - 1m-20m in size. Nasa, Near Earth Object Program.

Roughly 600 object during 20years = 30/yr. With better sensors, roughly 1/week. Dark matter?


An Opportunity

Picture: Planetary Resources see this as an opportunity, now when it's legal to mine.




Picture: The fuel consumption growth; actual and estimated


Profit Influencing Factors: 
1. Is it Technically feasible?, 
2. How much will it Cost/Risk (spread)?, and
3. Expected Revenues/Risk (spread)? 
=Profitable return ?

Mining sensor

Picture: This is a flawless two inch SrI2 crystal grown in the Burger Lab for use in new generation of gamma-ray spectrometers.


Quantum computer now possible

Picture: 
A team of Australian engineers has proven -- with the highest score ever obtained -- that a quantum version of computer code can be written, and manipulated, using two quantum bits in a silicon microchip. The advance removes lingering doubts that such operations can be made reliably enough to allow powerful quantum computers to become a reality.  

Scientific search engine & Visualisations - an normal Saturday on Internet

A normal Saturday on internet, published just for fun ;-) ...
Here is where it started (found via FutureTimeline, from my Feedly feed)


Picture: Search engine for Research&Development papers - built on Machine Learning Technology

Picture: Search word: "Business Model". Similar conclusions (pdf), but not yet there.

Picture: Semantic clusters - Dimensions, Measures, ... you understand, right ;-)

Conclusion: We'll get a Linguistic-convergence + a Unified Language either by general (is so good it can be used for several cases), or specific (optimised for specialised case). A function that serves a special purpose. Example; a hammer has a specific function + it include a bi-directional function (do and undo) - which is essential for all progress; political parties, trends, + and -,

Subjective = value by an evaluator precedes the Objective = un-valuated.

Note: You save the Unified Language components in ppt (under download).
Link: UML (history), paper
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Picture: Shares (continuous/distribution or non-c.), Compares, and Relations (incl. co-relations + to time). Almost right.


Charts can be classified into
1. 'Shares/Parts of a Group': that can be non-continuous (left), or continuous/sequential (-->distribution). Shares always compares, and usually benefits from being ranked, and accumulated (pareto).
A second Group can be Overlayed (continuous or non-continuous); like a Target, or a Years.

2. Relations: means input-output relation; that is algorithmic/processual. The purpose is to visualise a correlation.

Colors can be used, but are somewhat limited; try do a subtraction (grey75% -grey50% = grey 25%).

------
There are several type of engineers; process (mtrl, money, time, info, ...) - the fundamental dimensions/measures.
They all process something for a specific purpose. Logistics - the movement, process, efficiently (at low "cost"), effectively (at high revenue).


Picture: Fundamental Physical units (dimensions/measures) - how about Fundamental (business) Value units.


The reason the Business Model Canvas is wrong, is because it doesn't contain the basic business dimensions and measures.

Picture: The Business-model and the Data/information-model must coincide. 

It's closer to right than wrong - like the first map-makers of the world - but still not right. For instance Yes relationships are important but not just with the customer . and it's definitely not one of the basic dimensions in a company.

...low battery...

How concepts are born + MindControl

We disassemble words into phenom, that is assemble to words; concepts to read/write.

Picture: How we learn words. 


Interpretation: Powerful tool
1. disassemble a word stream, from media A: TV
2. disassemble a word stream, from media B: Twitter
3. correlate the streams, and
3.1: read the current discussion,
3.2: write the future discussion

Conclusion: Thought/Discussion Influencing Factors
Awareness is advised, since it will be used for both good/evil purposes.

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In computer science and information science, an ontology is a formal naming and definition. An ontology compartmentalizes the variables needed for some set of computations and establishes the relationships between them. The word element onto- comes from the Greek ὤν, ὄντος, ("being", "that which is"). There is also generally an expectation that the features of the model in an ontology should closely resemble the real world (related to the object).^[3]

The Zachman Framework is an enterprise ontology and is a fundamental structure for Enterprise Architecture, which provides a formal and structured way (methodology to discern) of viewing and defining an enterprise. 


Picture: 1. Contextual model, 2. Conceptual model, 3. Information model, 4. Data model

The definition of contextual is depending on the context, or surrounding words, phrases, and paragraphs, of the writing. An example of contextual is how the word "read" can have two different meanings depending upon what words are around it.

A pattern is a discernible regularity in the world - it follows certain rules - observable by analysis.
Any of our senses may directly observe patterns - as the governing rules.

Systems theory is the interdisciplinary study of systems in general, with the goal of discovering patterns and elucidating principles. A central topic of systems theory is self-regulating (governing) systems, i.e. systems self-correcting through feedback. 

Taxonomy is the practice and science of classification. 
A meronomy or partonomy is a type of hierarchy that deals with part–whole relationships, in contrast to a taxonomy whose categorisation is based on discrete sets. The part–whole relationship is sometimes referred to as HAS-A, and corresponds to object composition in object-oriented programming.^[1] 

The study of meronomy is known as mereology, and in linguistics a meronym is the name given to a constituent part of, the substance of, or a member of something.

In philosophy and mathematical logic, mereology (from the Greek μέρος, root: μερε(σ)-, "part" and the suffix -logy "study, discussion, science") is the study of parts and the wholes they form. Whereas set theory is founded on the membership relation between a set and its elements, mereology emphasizes the meronomic relation between entities, which—from a set-theoretic perspective—is closer to the concept of inclusion between sets.

The Math of Matching Humans (OKCupid)

R&D for Organizing HR

 

Picture: Match2=nRoot(A x B)

Interpretation
Match Influencing Factors
1. Define object A - Likes: cooperative consumes: A=B --> Good
2. Define object B - Likes: competing consumes A=B --> Bad
3. Define object A - Values: ethical rules + aspirations/target A=B --> Essential
4, Define object A - Importance: weight of each answer: A=B --> Good

Conclusion:
GroupOptimisation: MatchN(--> most effective) + Leader (--> most efficient)
...interesting




Unpublished:
http://ed.ted.com/lessons/michael-mitchell-a-clever-way-to-estimate-enormous-numbers
http://ed.ted.com/lessons/kevin-slavin-how-algorithms-shape-our-world

Faster than Light speed - 0 refraction index

"Although this infinitely high velocity sounds like it breaks the rule of relativity, it doesn't. Nothing in the universe travels faster than light carrying information -- Einstein is still right about that. But light has another speed, measured by how fast the crests of a wavelength move, known as phase velocity. This speed of light increases or decreases depending on the material it's moving through.

When the refraction index is reduced to zero, really weird and interesting things start to happen.

In a zero-index material, there is no phase advance, meaning light no longer behaves as a moving wave, traveling through space in a series of crests and troughs. Instead, the zero-index material creates a constant phase -- all crests or all troughs -- stretching out in infinitely long wavelengths. The crests and troughs oscillate only as a variable of time, not space.

It could also improve entanglement between quantum bits, as incoming waves of light are effectively spread out and infinitely long, enabling even distant particles to be entangled."

Link


Unpublished
First life 4.1Billion years ago

New dimensions measured in vacuum

"So far, physicists have assumed that it is impossible to directly access the characteristics of the ground state of empty space. Now, a team of physicists has succeeded in doing just that. They demonstrated a first direct observation of the so-called vacuum fluctuations by using short light pulses while employing highly precise optical measurement techniques."

"The existence of vacuum fluctuations is already known from theory as it follows from Heisenberg's uncertainty principle, one of the main pillars of quantum physics. This principle dictates that electric and magnetic fields can never vanish simultaneously. As a consequence, even total darkness is filled with finite fluctuations of the electromagnetic field, representing the quantum ground state of light and radio waves."

'Leitenstorfer was stunned by the research results himself: "We have had a few years of sometimes sleepless nights -- all possibilities of potentially interfering signals had to be excluded," smiles the physicist. "All in all we found out that our access to elementary time scales, shorter than the oscillation period of the light waves we investigate, is the key to understand the surprising possibilities that our experiment opens up."

Source: ScienceDaily

Excel Machine Learning Addin

Machine Learning inside Excel.

Try without installing:

Source: Jen Underwood tweet


How to make an intelligence:

'Deep learning (neural networks)' 

Link: Twitter flow, Machine Lerning


Recurrent Neural Networks (RNN) - one of many neural network patterns.
"The idea behind RNNs is to make use of sequential information. In a traditional neural network we assume that all inputs (and outputs) are independent of each other. But for many tasks that’s a very bad idea. If you want to predict the next word in a sentence you better know which words came before it. RNNs are calledrecurrent because they perform the same task for every element of a sequence, with the output being depended on the previous computations. Another way to think about RNNs is that they have a “memory” which captures information about what has been calculated so far. In theory RNNs can make use of information in arbitrarily long sequences, but in practice they are limited to looking back only a few steps (more on this later). 

Here is what a typical RNN looks like:


Semantic analysis: http://news.mit.edu/2015/more-flexible-machine-learning-1001
Cheat sheets: * http://designimag.com/2015/06/best-machine-learning-cheat-sheets/



Other
* Power BI Custom Visualisation Competition - Developer tools, Start page
* http://thevisualcommunicationguy.com/wp-content/uploads/2015/06/Infographic_RulesOfPunctuation1.jpg
* the Dark net (TED-talk)
* Human made mini Brain
* Extra dimensions in vacuum, measured

Life older than earth

"As life has evolved, its complexity has increased exponentially, just like Moore’s law which states that the number of transistors on an integrated circuit doubles approximately every two years. Extrapolate this trend backwards and life is older than the Earth itself."
Link



Addition information

Input - Process - Output

Happy to see that 'all these different models' are moving towards my generic model.

Picture: Different types of sensors (input), in various places.

Picture: Via a process (network*), driven (push and pulled) and ruled (do and don't do) by people.

* "connectivity"

Picture: To enable various enhanced products.

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Appendix:

Pictures: From the mix of the various sensors.

Source: link

Cyber attack map - in real time

Real time map link: Interactive map

Article (via LinkedIn forum)

Excellence = Consistency x Quality. Language tree

Good formulas - they lead in the right direction.

Beautiful tree. Now let each tree ring represent another measure, like a year. A real Tree chart.
Use contour lines (or heat map) be one dimension.

Languages evolve to become more efficient. Transmitting more in less time.
A study showed languages more towards "dependency length minimization" (DLM).


History of data visualizations, what do they tell us, link
ourworldindata: Energy use + GDP, per capita

Unpublished:
The fractals at the heart of African designs

Online courses - edX

Link