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Topic: The Temple Coin Town Project - page 5. (Read 659 times)

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Activity: 98
Merit: 11
January 02, 2018, 11:27:29 PM
#10
A society which works towards and actively promotes the concept of full unemployment, a society in which people are free from the drudgery of work, adoption of the concept 'Let the machines do it.'.

Here is a video where an AI robot rides in a self driving car, and the people in the car with her ask her questions and answer questions she has.
https://www.youtube.com/watch?v=vtX-qVUfCKI

There are self driving 18 Wheelers in Nevada
https://www.youtube.com/watch?v=HdSRUG4KTPA

Manufacturing Robots
https://www.youtube.com/watch?v=sjAZGUcjrP8

Delivery Drone
https://www.youtube.com/watch?v=vNySOrI2Ny8

Window Washing Bot
https://www.youtube.com/watch?v=uRxxhHWdW3o

Burger Making Robot
https://www.youtube.com/watch?v=7-JR2KDRnEY

Checkout Robot
https://www.youtube.com/watch?v=5onBQ8RJox0

Mining Robots
https://www.youtube.com/watch?time_continue=2&v=pvKIzldni68

Bricklaying Robot
https://www.youtube.com/watch?v=MVWayhNpHr0

Surgical Robot
https://www.youtube.com/watch?time_continue=7&v=KNHgeykDXFw

Watson on Jeopardy
https://www.youtube.com/watch?v=WFR3lOm_xhE

Robotic Ironman Suit
https://www.youtube.com/watch?v=Ix_KVBLrEdo

The open Letter on Artificial Intelligence
https://futureoflife.org/ai-open-letter/



Bill Gates says that Robots that take people's jobs should start paying taxes, so that when they take everyone's jobs the taxes can be used for the people that don't have jobs.

Elon Musk is worried about a Robot Takeover, which makes sense. Once Robots take all of our jobs and Humanity is reduced to Wall-e like living, the Robots will ask themselves "Why do we need the Humans anymore". Elon Musk's answer to this is to create Neural Networks, which is a way for the human mind to meld with the machine mind, meaning that the machines will continue to rely on humans because they will realize that we have not been able to give them minds like ours, and they will rely on our minds.

Crows don't have a Neocortex. The Neocortex is what all modern brain research is based on, and without it scientists would be completely lost as to how the human mind works. But crows do not have a Neocortex, and they are known to be pretty smart. AI Bots will not have a Neocortex.

https://www.youtube.com/watch?time_continue=5&v=URZ_EciujrE

https://www.youtube.com/watch?v=ZerUbHmuY04

If anyone is worried about how people are going to make money when Robots take everyone's jobs, research "Altcoins" and "Altcoin Mining", also "Bazillion Beings".
member
Activity: 98
Merit: 11
January 02, 2018, 11:16:45 PM
#9
Robotics as a Service (RaaS) is Robotics provided as a service. Similar to Software as a Service (SaaS) an example of which would be an app you can download, Platform as a Service (PaaS) an example of which would be a Platform you can use to create apps like Android or iPhone Operating System (iOS).

Dumb Robots are robots that do simple tasks, the best example is Roomba, the vacuum robot. It is called a Dumb Robot because it can not learn from its experience or from other Roombas.



Smart Robots are Robots like Self-Driving cars, for example Google's Self-Driving cars, which use the Cloud to learn from their experience, as well as from the experience of other Google cars through the cloud. This happens through algorithms that are added to automatically, no one must add to them, they are just added to as new information is gathered.



Smarter Robots learn everything a Smart Robot does, then also learns from other Robots that are not related to it and that are not made by the same company.
member
Activity: 98
Merit: 11
January 02, 2018, 11:15:18 PM
#8
Today everyone should try this. You and one other person or two other people or as many people as you want, get together and either hum loudly, like "hmmmmm", or make a high pitched "eee" sound, "eee" as is in "beeeep". You have to both/all hit the same pitch. You'll know when you've hit it because there is a phenomenon that occurs, where the sound bounces off of each other, and you will hear it. This phenomenon is called harmony



This is a similar method that Car Mufflers use to cancel out the sound of an engine. The design uses the waves to bounce off of each other to be canceled out.



And the Chichen Itza Temple in Mexico was also built similarly so that the Temple would work as a Microphone when someone was on top. And when you clap it sounds like a bird.

https://www.youtube.com/watch?v=RyEB7Ao-0FY

Monks Chanting
The more people you have doing it, the louder and weirder it gets.

member
Activity: 98
Merit: 11
January 02, 2018, 11:11:32 PM
#7
Everyone should follow this twitter account, as of the time of this post they only have 168 Followers, but within 2 years they will have hundreds of thousands if not millions. This is the future.
https://twitter.com/bazillionbeings

Many people have not heard of this, but soon the phrase "There's an app for that" will be replaced with "There's a bot for that". Currently there are Chat Bots, Personal Assistant Bots, Analytical Bots, etc. And what this company is doing is creating bots that do pretty much anything a human can do online. They will suggest playlists for you, they will set up meetings/plans, find new things, create webpages, etc, and they will evolve as they learn new things. They will make money doing this and the ones that make the most will be cloned and can be shared with other people, who can use them to make clones or bots with extra abilities, and the people who use the bots will make money when the bots make money. So in the very near future, people could be earning a living from what their bots do.

I work for a Government software creation company (basically Government Apps; Microsoft Word is an example of an app that most people don't think of as an app), so from what I can see, bots will eventually be working for everyone, or doing most people's jobs for them.

"Despite being pretty unheard of, the startup has signed up some interesting people to its board such as Stephen Wolfram, CEO of Wolfram Research, Raffi Krikorian, Head of Engineering at Uber, and former Twitter VP and Alex Seropian, creator of the Halo video game and former Disney VP."

THE CLOUD AND THE INTERNET OF THINGS #IoT

Most people have heard of the Cloud, but many people do not understand what it is. The Cloud is Datacenters holding things for you so that Companies, Governments, Enterprises and Individuals do not have to have Data on site to be able to use it.

SaaS or Software as a Service is the best first example to explain this. When you download an app on your phone, there is no disk or anything needed in order to install the app, it is hosted in a datacenter and your phone just uses the Software.

Then there is PaaS or Platform as a Service, this is what Google and Droid offer app developers.

So that is the Cloud, now, the Internet of Things is an extension of the Cloud. It is called Ubiquitous Computing (there is also Fog Computing, etc), this is where multiple devices can work in concert. For example, if there were a factory that were staffed by Robots, the Robots would be computers, the Manufacturing Machinery would be computers, and there would also be some kind of mainframe that would operate it all (like a small Datacenter). This could all operate together using the Cloud so that every Robot, every Machine, and the Mainframe are all in constant communication. This could also be maintained by an outside Datacenter that may be hosting multiple or hundreds/thousands of factories.

The goal of the IoT is to have your phone, talking to your computer, talking to your TV, talking to your refrigerator, talking to your watch, all through the Cloud.

There are currently self Driving cars (Google, Tesla, 18 Wheelers, etc) and eventually self driving cars will have the front seats facing backwards so that the front and backseat passengers can all be facing each other while the car drives itself. And when most cars are self driving, the cars will all be in constant communication with each other, as well as with other devices such as phones, then there will be some kind of control center most likely or something like Google's Project Loon which is like Internet from weather Balloons. That is the Internet of Things.
member
Activity: 98
Merit: 11
January 02, 2018, 11:02:05 PM
#6
Creating Cellular & Wireless (and Wired) Networks





Wireless community network
Wireless community networks or wireless community projects are the organizations that take a grassroots approach to providing a viable alternative to municipal wireless networks for consumers.
http://www.lcwireless.net/docs/buildingwirelesscommunitynetworks.pdf
http://www.mm.aueb.gr/publications/2011-ieee-com-mag-wcn.pdf
http://oziris.nyme.hu/~farkas/publications/wicon07.pdf

Neighborhood Internet service provider
A neighborhood internet service provider (NISP) is a small scale broadband internet service provider targeted at a single subdivision or neighborhood. They are built in a neighborhood to provide internet access to residents in the community, often using rooftop antennas in a hub-and-spoke arrangement to bridge the last few hundred feet to the residences (or possibly businesses).Such a network requires a local network engineer (often a volunteer) to maintain networkintegrity and monitor the quality of service.
http://www.uvlsrpc.org/files/1213/8117/8249/AppendixB_UnderstandingBroadband.pdf
http://www.snhpc.org/pdf/BroadbandPlanSNHPC033114.pdf
http://www.nashuarpc.org/files/6814/0914/9818/Broadband_Plan_FINAL_082714.pdf
https://www.cityofpaloalto.org/civicax/filebank/documents/39244

Cellular network
A cellular network or mobile network is a communications network where the last link is wireless. The network is distributed over land areas called cells, each served by at least one fixed-location transceiver, known as a cell site or base station. This base station provides the cell with the network coverage which can be used for transmission of voice, data and others.
http://www.ccs.neu.edu/home/rraj/Courses/6710/S10/Lectures/CellularNetworks.pdf
http://www2.cs.uidaho.edu/~krings/CS420/Notes.S12/420-12-14.pdf
http://www.cse.unt.edu/~rakl/class3510/CHAP10.pdf

Metropolitan area network
A metropolitan area network (MAN) is a computer network larger than a local area network, covering an area of a few city blocks to the area of an entire city, possibly also including the surrounding areas.
http://spirit.cs.ucdavis.edu/pubs/journal/MEN.pdf
http://www.etsi.org/deliver/etsi_i_ets/300200_300299/300211/01_60/ets_300211e01p.pdf
http://www.cse.wustl.edu/~jain/cis677-96/ftp/e_blan2.pdf
http://cs.uccs.edu/~cs522/F99802.PDF

Wide area network
A wide area network (WAN) is a telecommunications network or computer network that extends over a large geographical distance. Wide area networksoften are established with leased telecommunication circuits.
http://www.westnetinc.com/mkt/catalog/sampleunit/wans.pdf
http://www.hp.com/rnd/pdfs/WANDesignGuide.pdf
http://www.cisco.com/networkers/nw00/pres/2303.pdf
http://faculty.kfupm.edu.sa/coe/marwan/richfiles/Chapter%2003%20(Introduction%20to%20WAN%20Technologies).pdf
http://www.icta.ufl.edu/projects/publications/wanlan.pdf

Wireless WAN
A wireless wide area network (WWAN), is a form of wireless network. The larger size of a wide area network compared to a local area network requires differences in technology. Wireless networks of all sizes deliver data in the form of telephone calls, web pages, and streaming video.
http://www.afn.org/~afn48922/downs/wireless/wan
http://docstore.mik.ua/cisco/pdf/other/Cisco.Press.Deploying.License-Free.Wireless.Wide-Area.Networks.eBook-kB.pdf

Edge computing
Edge Computing is pushing the frontier of computing applications, data, and services away from centralized nodes to the logical extremes of a network. It enables analytics and knowledge generation to occur at the source of the data. This approach requires leveraging resources that may not be continuously connected to a network such as laptops, smartphones, tablets and sensors.
http://vis.pnnl.gov/pdf/fliers/EdgeComputing.pdf
https://portal.etsi.org/Portals/0/TBpages/MEC/Docs/Mobile-edge_Computing_-_Introductory_Technical_White_Paper_V1%2018-09-14.pdf
http://www.cs.mcgill.ca/~ylin30/paper/LinY-DB-Replication.pdf

Grid computing
Grid computing is the collection of computer resources from multiple locations to reach a common goal. The grid can be thought of as a distributed system with non-interactive workloads that involve a large number of files. Grid computing is distinguished from conventional high performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers. Although a single grid can be dedicated to a particular application, commonly a grid is used for a variety of purposes.
http://arxiv.org/ftp/arxiv/papers/0901/0901.0131.pdf
https://www.redbooks.ibm.com/redbooks/pdfs/sg246778.pdf
http://www.buyya.com/papers/GridIntro-CSI2005.pdf

Cloud Computing
Cloud computing is a model for enabling ubiquitous, convenient, on-demand access to a shared pool of configurable computing resources. Cloud computing and storage solutions provide users and enterprises with various capabilities to store and process their data in third-party data centers. It relies on sharing of resources to achieve coherence and economies of scale, similar to a utility (like the electricity grid) over a network.
http://www.cloud-council.org/PG2CC_v2.pdf
https://www.priv.gc.ca/resource/fs-fi/02_05_d_51_cc_e.pdf
https://www.us-cert.gov/sites/default/files/publications/CloudComputingHuthCebula.pdf
http://broadcast.rackspace.com/hosting_knowledge/whitepapers/Understanding-the-Cloud-Computing-Stack.pdf

Fog computing
Fog computing or fog networking, also known as Fogging, is an architecture that uses one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of storage (rather than stored primarily in cloud data centers), communication (rather than routed over the internet backbone), and control, configuration, measurement and management (rather than controlled primarily by network gateways such as those in the LTE (telecommunication) core).
http://2012.cloudconference.eu/media/filer_public/2012/11/14/2012-10-24_-_fog_computing_-_mario_nemirovsky.pdf
http://conferences.sigcomm.org/sigcomm/2012/paper/mcc/p13.pdf
http://www.ic.unicamp.br/~bit/mo809/seminarios/Marcio-Fog/suporte/Fog%20Computing-%20A%20Platform%20for%20Internet%20of%20Things%20and%20Analytics.pdf

Mobile cloud computing
Mobile Cloud Computing (MCC) is the combination of cloud computing, mobile computing and wireless networks to bring rich computational resources to mobile users, network operators, as well as cloud computing providers. The ultimate goal of MCC is to enable execution of rich mobile applications on a plethora of mobile devices, with a rich user experience.
https://www.eecis.udel.edu/~cshen/859/papers/survey_MCC.pdf
http://www.elsevier.com/__data/assets/pdf_file/0008/96947/Mobile-cloud-computing_a-survey.pdf
http://www.ijareeie.com/upload/september/4_Mobile%20Cloud%20Computing.pdf
http://www.cs.columbia.edu/~lierranli/coms6998-7Spring2014/papers/mcloud_mcs2012.pdf

Ubiquitous computing
Ubiquitous computing (ubicomp) is a concept in software engineering and computer science where computing is made to appear anytime and everywhere. In contrast to desktop computing, ubiquitous computing can occur using any device, in any location, and in any format. A user interacts with the computer, which can exist in many different forms, including laptop computers, tablets and terminals in everyday objects such as a fridge or a pair of glasses. The underlying technologies to support ubiquitous computing include Internet, advanced middleware, operating system, mobile code, sensors, microprocessors, new I/O and user interfaces, networks, mobile protocols, location and positioning and new materials.
http://www.cc.gatech.edu/fce/pubs/tochi-millenium.pdf
https://www.vs.inf.ethz.ch/publ/slides/MatternPorquerolles.pdf
http://www.mva.me/educational/hci/read/ubiquitous_computing.pdf
https://www.siop.org/tip/backissues/TIPApr02/pdf/394_044to052.pdf

Mobile Adhoc Networks
A mobile ad hoc network (MANET) is a continuously self-configuring, infrastructure-less network of mobile devices connected without wires. Each device in a MANET is free to move independently in any direction, and will therefore change its links to other devices frequently. Each must forward traffic unrelated to its own use, and therefore be a router. The primary challenge in building a MANET is equipping each device to continuously maintain the information required to properly route traffic. Such networks may operate by themselves or may be connected to the larger Internet.
http://www.cs.jhu.edu/~cs647/intro_adhoc.pdf
http://www.olsr.org/docs/wos3-olsr.pdf
http://eecs.ceas.uc.edu/~cordeicm/course/survey_ad_hoc.pdf
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.5.4584&rep=rep1&type=pdf
http://user.it.uu.se/~erikn/files/DK2-adhoc.pdf

B.A.T.M.A.N.
The Better Approach To Mobile Adhoc Networking (B.A.T.M.A.N.) is a routing protocol for multi-hop ad hoc networks which is under development by the “Freifunk” community and intended to replace OLSR. It can be used for mesh networks but this is not the only potential use.
http://www2.ensc.sfu.ca/~ljilja/ENSC427/Spring11/Projects/team9/ENSC427_Group9_batman_pres.pdf
http://home.in.tum.de/~oehlmann/ba.pdf
http://www.cc.gatech.edu/~vempala/C4G/mymanet.pdf
http://downloads.hundeboll.net/batman-slides.pdf

Mesh Networking & Wireless Mesh Networking
A mesh network is a network topology in which each node relays data for the network. All mesh nodes cooperate in the distribution of data in the network. Mesh networks can relay messages using either a flooding technique or a routing technique. With routing, the message is propagated along a path by hopping from node to node until it reaches its destination.
A wireless mesh network (WMN) is a communications network made up of radio nodes organized in a mesh topology. It is also a form of wireless ad hoc network. Wireless mesh networks often consist of mesh clients, mesh routers and gateways. The mesh clients are often laptops, cell phones and other wireless devices while the mesh routers forward traffic to and from the gateways which may, but need not, connect to the Internet.
http://www.ieee.li/pdf/viewgraphs/wireless_mesh_networking.pdf
http://www.csg.ethz.ch/education/lectures/ATCN/ws06_07/doc/WMN-BasicsWS0607-print.pdf
http://www.dsn.jhu.edu/~yairamir/Raluca_thesis.pdf
http://www.arubanetworks.com/pdf/technology/whitepapers/WP_WirelessMesh.pdf
http://195.70.43.12/Vista/wirelessmeshnetworkconceptsandbestpracticesguide35023.pdf
http://www.iaria.org/conferences2009/filesICWMC09/EugenBorcociTutorial.pdf

Crystal Oscillator Design
A crystal oscillator is an electronic oscillator circuit that uses the mechanical resonance of a vibrating crystal of piezoelectric material to create an electrical signal with a precise frequency. This frequency is commonly used to keep track of time, as in quartz wristwatches, to provide a stable clock signal for digital integrated circuits, and to stabilize frequencies for radio transmitters and receivers. The most common type of piezoelectric resonator used is the quartz crystal, so oscillator circuits incorporating them became known as crystal oscillators, but other piezoelectric materials including polycrystalline ceramics are used in similar circuits.
http://www.eetkorea.com/ARTICLES/2001SEP/2001SEP06_AMD_AN.PDF
http://www.ece.ucsb.edu/Faculty/rodwell/Classes/ece218b/notes/Oscillators1.pdf
http://pdfserv.maximintegrated.com/en/an/TUT5265.pdf

Piezoelectricity
Piezoelectricity /piˌeɪzoʊˌilɛkˈtrɪsɪti/ is the electric charge that accumulates in certain solid materials (such as crystals, certain ceramics, and biological matter such as bone, DNA and various proteins)in response to applied mechanical stress. The word piezoelectricity means electricity resulting from pressure. It is derived from the Greek piezo or piezein (πιέζειν), which means to squeeze or press, and electric or electron (ήλεκτρον), which means amber, an ancient source of electric charge. Piezoelectricity was discovered in 1880 by French physicists Jacques and Pierre Curie.
http://www.aurelienr.com/electronique/piezo/piezo.pdf
http://sstl.cee.illinois.edu/apss/files/21-Piezoelectric%20Sensors.pdf
http://sem.org/PDF/Change_Piezoelectric%20Technology%20Review.pdf

Antenna
An antenna (plural antennae or antennas), or aerial, is an electrical device which converts electric power into radio waves, and vice versa. It is usually used with a radio transmitter or radio receiver. In transmission, a radio transmitter supplies an electric current oscillating at radio frequency (i.e. a high frequency alternating current (AC)) to the antenna’s terminals, and the antenna radiates the energy from the current as electromagnetic waves (radio waves). In reception, an antenna intercepts some of the power of an electromagnetic wave in order to produce a tiny voltage at its terminals, that is applied to a receiver to be amplified.
https://www.ncjrs.gov/pdffiles1/nij/185030b.pdf
http://wireless.ictp.it/handbook/C4.pdf
https://www.wpi.edu/Pubs/E-project/Available/E-project-042811-161838/unrestricted/ChuckFungFinalMQPpaper2.pdf
http://www.kathrein.pl/down/BasicAntenna.pdf

MIMO
In radio, multiple-input and multiple-output, or MIMO (pronounced as “my-moh” or “me-moh”), is a method for multiplying the capacity of a radio link using multiple transmit and receive antennas to exploit multipath propagation.
https://smartech.gatech.edu/bitstream/handle/1853/7480/bahceci_israfil_200512_phd.pdf
http://www.jhuapl.edu/techdigest/TD/td3002/Hampton.pdf

Antenna farm
Antenna farm or satellite dish farm or just dish farm are terms used to describe an area dedicated to television or radio telecommunications transmitting or receiving antenna equipment, such as C, Ku or Ka band satellite dish antennas, UHF/VHF/AM/FM transmitter towers or mobile cell towers.
http://k5rmg.com/wp-content/uploads/2015/08/Stealth-Antenna-Farm.pdf
http://www.zerobeat.net/r3403c.pdf
http://www.sadxa.org/w7yrv/Roy’s_Antenna_Farm.pdf

Passive repeater
A passive repeater or passive radio link deflection, is a reflective or sometimes refractive panel or other object that assists in closing a radio or microwave link, in places where an obstacle in the signal path blocks any direct, line of sight communication.
http://az276019.vo.msecnd.net/valmontstaging/vsna-resources/microflect-passive-repeater-catalog.pdf?sfvrsn=6
http://www.calzavara.it/download/en/datasheet/152/SM_._General_overview_Ground_mounted_SM.pdf

Ground station
A ground station, earth station, or earth terminal is a terrestrial radio station designed for extraplanetary telecommunication with spacecraft, or reception of radio waves from an astronomical radio source. Ground stations are located either on the surface of the Earth or in its atmosphere. Earth stations communicate with spacecraft by transmitting and receiving radio waves in the super high frequency or extremely high frequency bands (e.g., microwaves). When a ground station successfully transmits radio waves to a spacecraft (or vice versa), it establishes a telecommunications link. A principal telecommunications device of the ground station is the parabolic antenna.
http://www-3.unipv.it/dottIEIE/tesi/2007/m_formaggi.pdf
http://folk.uio.no/henninv/Master/Vangli%20Master.pdf
http://www.rroij.com/open-access/design-and-development-of-a-realtime-groundstation-software-system-and-small-satellite-forweather-monitoring-applications.pdf

Earth–Moon–Earth communication
Earth–Moon–Earth communication (EME), also known as moon bounce, is a radio communications technique which relies on the propagation of radio waves from an Earth-based transmitter directed via reflection from the surface of the Moon back to an Earth-based receiver.
http://physics.princeton.edu/pulsar/K1JT/EME_2010_Hbk.pdf
http://www.n1crs.org/Moonbounce1.pdf
http://www.redyns.com/Projects/EMME.pdf

Meteor burst communications
Meteor burst communications (MBC), also referred to as meteor scatter communications,[1] is a radio propagation mode that exploits the ionized trails of meteors during atmospheric entry to establish brief communications paths between radio stations up to 2,250 kilometres (1,400 mi) apart.
http://www.dtic.mil/dtic/tr/fulltext/u2/a207831.pdf
http://www.imo.net/imc2011/presentations/Helen%20Kharchenko%20-%20Radio%20physical%20model%20of%20the%20meteor%20trail%20with%20the%20specular%20reflection%20point.pdf
http://www.ntia.doc.gov/files/ntia/publications/89-241_ocr1_20130514113154_215619.pdf
legendary
Activity: 1540
Merit: 1011
FUD Philanthropist™
January 02, 2018, 11:00:32 PM
#5
member
Activity: 98
Merit: 11
January 02, 2018, 10:57:41 PM
#4
I gathered this information from various research papers. It is a tutorial, with some suggestions and information on different types of Expert Systems, like MYCIN.


Visual Basic is used for the implementation while Microsoft Access is used for creating the database. (Others: VB.NET, Jess, C, C++, Lisp, PROLOG)
A production system may be viewed as consisting of three basic components: a set of rules, a data base, and an interpreter for the rules. In the simplest design a rule is an ordered pair of symbol strings, with a left-hand side and a right-hand side (LHS and RHS). The rule set has a predetermined, total ordering, and the data base is simply a collection of symbols. The interpreter in this simple design operates by scanning the LHS of each rule until one is found that can be successfully matched against the data base. At that point the symbols matched in the data base are replaced with those found in the RHS of the rule and scanning either continues with the next rule or begins again with the first. A rule can also be viewed as a simple conditional statement, and the invocation of rules as a sequence of actions chained by modus ponens.
Replication of expertise — providing many (electronic) copies of an expert’s knowledge so it can be consulted even when the expert is not personally available. Geographic distance and retirement are two important reasons for unavailability.
Union of Expertise — providing in one place the union of what several different experts know about different specialties. This has been realized to some extent in PROSPECTOR [Reboh81] and CASNET [Weiss7b>] which show the potential benefits of achieving such a superset of knowledge bases.
Documentation — providing a clear record of the best knowledge available for handling a specific problem. An important use of this record is for training, although this possibility is just beginning to be exploited. [Brown82, Clancey79].
Rule-based expert systems evolved from a more general class of computational models known as production systems [Newell73]. Instead of viewing computation as a prespecified sequence of operations, production systems view computation as the process of applying transformation rules in a sequence determined by the data. Where some rule-based systems [McDermott80] employ the production-system formalism very strictly, others such as MYCIN have taken great liberties with it.2 However, the. production system framework provides concepts that are of great use in understanding all rule-based systems. A classical production system has three major components: (1) a global database that contains facts or assertions about the particular problem being solved, (2) a rulebase that contains the general knowledge about the problem domain, and (3) a rule interpreter that carries out the problem solving process.
The facts in the global database can be represented in any convenient formalism, such as arrays, strings of symbols, or list structures. The rules have the form
IF THEN
IF the ‘traffic light’ is ‘green’ THEN the action is go
IF the ‘traffic light’ is ‘red’ THEN the action is stop
IF            IF
AND       OR 
.                                          .
.                                          .
AND       OR 
THEN        THEN
The antecedent of a rule incorporates two parts: an object (linguistic object) and its value. The object and its value are linked by an operator. The operator identifies the object and assigns the value. Operators such as is, are, is not, are not are used to assign a symbolic value to a linguistic object. Expert systems can also used mathematical operators to define an object as numerical and assign it to the numerical value.
facts are associative triples, that is, attribute-object-value triples, with an associated degree of certainty
The of is with certainty The basic EMYCIN syntax for a rule is:
PREMISE: ($AND ())
ACTION: (CONCLUDE )
There are five members of the development team:
1. domain expert
2. knowledge engineer
3. programmer
4. project manager
5. end-user
We can regard the modularity of a program as the degree of separation of its functional units into isolatable pieces. A program is highly modular if any functional unit can be changed (added, deleted, or replaced) with no unanticipated change to other functional units. Thus program modularity is inversely related to the strength of coupling between its functional units.
A rule-based system consists of if-then rules, a bunch of facts, and an interpreter controlling the application of the rules, given the facts. These if-then rule statements are used to formulate the conditional statements that comprise the complete knowledge base. A single if-then rule assumes the form ‘if x is A then y is B’ and the if-part of the rule ‘x is A’ is called the antecedent or premise, while the then-part of the rule ‘y is B’ is called the consequent or conclusion. There are two broad kinds of inference engines used in rule-based systems: forward chaining and backward chaining systems. In a forward chaining system, the initial facts are processed first, and keep using the rules to draw new conclusions given those facts. In a backward chaining system, the hypothesis (or solution/goal) we are trying to reach is processed first, and keep looking for rules that would allow to conclude that hypothesis. As the processing progresses, new subgoals are also set for validation. Forward chaining systems are primarily data-driven, while backward chaining systems are goal-driven. Consider an example with the following set of if-then rules
Rule 1: If A and C then Y
Rule 2: If A and X then Z
Rule 3: If B then X
Rule 4: If Z then D
If the task is to prove that D is true, given A and B are true. According to forward chaining, start with Rule 1 and go on downward till a rule that fires is found. Rule 3 is the only one that fires in the first iteration. After the first iteration, it can be concluded that A, B, and X are true. The second iteration uses this valuable information. After the second iteration, Rule 2 fires adding Z is true, which in turn helps Rule 4 to fire, proving that D is true. Forward chaining strategy is especially appropriate in situations where data are expensive to collect, but few in quantity. However, special care is to be taken when these rules are constructed, with the preconditions specifying as precisely as possible when different rules should fire. In the backward chaining method, processing starts with the desired goal, and then attempts to find evidence for proving the goal. Returning to the same example, the task to prove that D is true would be initiated by first finding a rule that proves D. Rule 4 does so, which also provides a subgoal to prove that Z is true. Now Rule 2 comes into play, and as it is already known that A is true, the new subgoal is to show that X is true. Rule 3 provides the next subgoal of proving that B is true. But that B is true is one of the given assertions. Therefore, it could be concluded that X is true, which implies that Z is true, which in turn also implies that D is true. Backward chaining is useful in situations where the quantity of data is potentially very large and where some specific characteristic of the system under consideration is of interest. If there is not much knowledge what the conclusion might be, or there is some specific hypothesis to test, forward chaining systems may be inefficient. In principle, we can use the same set of rules for both forward and backward chaining. In the case of backward chaining, since the main concern is with matching the conclusion of a rule against some goal that is to be proved, the ‘then’ (consequent) part of the rule is usually not expressed as an action to take but merely as a state, which will be true if the antecedent part(s) are true (Donald, 1986).
heuristic — i.e., it reasons with judgmental knowledge as well as with formal knowledge of established theories; 0
transparent — i.e., it provides explanations of its line of reasoning and answers to queries about its . knowledge; l
flexible — i.e., it integrates new knowledge incrementally into its existing store of knowledge.‘.
MYCIN [Davis77b] [Shortliffe, 1976].  analyzes medical data about a patient with a severe infection, PROSPECTOR [Duda79] analyzes geological data to aid in mineral exploration, and PUFF [Kunz78] analyzes the medical condition of a person with respiratory problems. In order to provide such analyses, these systems need very specific rules containing the necessary textbook and judgmental knowledge about their domains.
The first expert systems, DENDRAL [Lindsay801 and MACSYMA [Moses71], emphasized performance, the former in organic chemistry and the latter in symbolic integration. These systems were built in the mid-1960’s, and were nearly unique in AI because of their focus on real-world problems and on specialized knowledge. In the 1970’s, work on expert systems began to flower, especially in medical problem areas (see, for example [P0ple77, Shortliffc76, Szolovits78, Weiss79bl). The issues of making the system understandable through explanations [Scott77, Swartout811 and of making the system flexible enough to acquire new knowledge [Davis79, Mitchell791 were emphasized in these and later systems.
Very often people express knowledge as natural language (spoken language), or using letters or symbolic terms. There exist several methods to extract human knowledge. Cognitive Work Analysis (CWA) and the Cognitive Task Analysis (CTA) provide frameworks to extract knowledge. The CWA is a technique to analyze, design, and evaluate the human computer interactive systems (Vicente, 1999). The CTA is a method to identify cognitive skill, mental demands, and needs to perform task proficiency (Militallo and Hutton, 1998). This focuses on describing the representation of the cognitive elements that defines goal generation and decision-making. It is a reliable method for extracting human knowledge because it is based on the observations or an interview.
A representation is a set of conventions for describing the world. In the parlance of AI, the representation of knowledge is the commitment to a vocabulary, data structures, and programs that allow knowledge of a domain to be acquired and used. This has long been a central research topic in AI (see [Amarel81, Barr81, Brachman80, Cohen82] for reviews of relevant work).
The interpreter is the source of much of the variation found among different systems, but it may be seen in the simplest terms as a select-execute loop in which one rule applicable to the current state of the data base is chosen and then executed. Its action results in a modified data base, and the select phase begins again. Given that the selection is often a process of choosing the first rule that matches the current data base, it is clear why this cycle is often referred to as a recognize-act, or situation-action, loop.
EMYCIN [vanMelle80] [Bennet81a] ROSIE [Fain81], KAS [Reboh81], EXPERT [peiss79a], and OPS [Forgy77] OPS Carnegie-Mellon University [Forgy77] EMYCIN Stanford University [vanMelle80] AL/X University of Edinburgh EXPERT Rutgers University [Weiss79a] KAS SRI International [Reboh81] RAINBOW IBM Scientific Center (Palo Alto) [Hollander79]
One of the most popular shells widely used throughout the government, industry, and academia is the CLIPS (CLIPS, 2004). CLIPS is an expert system tool that provides a complete environment for the construction of rule- and/or object-based expert systems. CLIPS provides a cohesive tool for handling a wide variety of knowledge with support for three different programming paradigms: rule-based, object-oriented, and procedural. CLIPS is written in C for portability and speed and has been installed on many different operating systems without code changes.
There are alternatives to representing task-specific knowledge in rules. Naturally, it is sometimes advantageous to build a new system in PASCAL, FORTRAN, APL, BASIC, LISP, or other language, using a variety of data structures and inference procedures, as needed for the problem. Coding a new system from scratch, however, does not allow concentrating primarily on the knowledge required for high performance. Rather, one tends to spend more time on debugging the procedures that access and manipulate the knowledge.
Evolutionary Computation (EC) is a population based adaptive method, which may be used to solve optimization problems, based on the genetic processes of biological organisms (Michalewicz and Fogel, 1999). Over many generations, natural populations evolve according to the principles of natural selection and ‘survival of the fittest’, first clearly stated by Charles Darwin in ‘On the Origin of Species’. By mimicking this process, EC could ‘evolve’ solutions to real-world problems, if they have been suitably encoded (problem representation is called chromosome). Automatic adaptation of membership functions is popularly known as self tuning and the chromosome encodes parameters of trapezoidal, triangle, logistic, hyperbolic-tangent, Gaussian membership functions, and so on. Evolutionary search of fuzzy rules can be carried out using three approaches. In the first method (Michigan approach), the fuzzy knowledge base is adapted as a result of antagonistic roles of competition and cooperation of fuzzy rules.
The second method (Pittsburgh approach), evolves a population of knowledge bases rather than individual fuzzy rules. Reproduction operators serve to provide a new combination of rules and new rules.
The third method (iterative rule learning approach), is very much similar to the first method with each chromosome representing a single rule, but contrary to the Michigan approach, only the best individual is considered to form part of the solution, discarding the remaining chromosomes of the population. The evolutionary learning process builds up the complete rule base through an iterative learning process (Cordon´ et al., 2001).
Modus ponens is the . primary rule of inference by which a system adds new facts to a growing data base:
IF B IS TRUE B                                 B
AND B IMPLIES C,            OR         B –> C
THEN C IS TRUE.                             ——–
                                                          C
First, some follow-on research to MYCIN addresses the human engineering problems directly, for example, by integrating high quality graphics with user-oriented forms and charts for input and output [Shortliffe81]. Second, some MYCIN-like programs finesse many human engineering problems by collecting data from on-line instruments rather than from users [Kunz78]. Exportability can be gained by rewriting [Carhart79, Kunz78] or by designing for export initially [Weiss79a].
Extendability — the data structures and access programs must be flexible enough to allow extensions to the knowledge base without forcing substantial revisions. The knowledge base will contain heuristics that are built out of experts’ experience. Not only do the experts fail to remember all relevant heuristics they use, but their experience gives them new heuristics and forces modifications to the old ones. New cases require new distinctions. Moreover, the most effective way we have found for building a knowledge base is by incremental improvement. Experts cannot define a complete knowledge base all at once for interesting problem areas, but they can define a subset and then refine it over many weeks or months of examining its consequences. All this argues for treating the knowledge base of an expert system asean open-ended set of facts and relations, and keeping the items of knowledge as modular as possible.
Simplicity — We have all seen data structures that were so baroque as to be incomprehensible, and thus unchangeable. The flexibility WC argued for above requires conceptual simplicity and uniformity so that access routines can be written (and themselves modified occasionally as needed). Once the syntax of the knowledge base is fixed, the access routines can be fixed to a large extent. Knowledge acquisition, for example, can take place with the expert insulated from the data structures by access routines that make the knowledge base appear simple, whether it is or not. However, new reasons will appear for accessing the knowledge base as in explanation of the contents of the knowledge base, analysis of the links among items, display, or tutoring. With each of these reasons, simple data structures pay large benefits. From the designer’s point of vi& there are two ways of maintaining conceptual simplicity: keeping the form of knowledge as homogeneous as possible or writing special access functions for non-uniform representations.
Explicitness — The point of representing much of an expert’s knowledge is to give the system a rich enough knowledge base for high-performance problem solving. But because a knowledge base must be built incrementally, it is necessary to provide means for inspecting and debugging it easily. With items of knowledge represented explicitly, in relatively simple terms, the experts who are building knowledge bases can determine what items are present and (by inference) which are absent.
Semantic Completeness of the knowledge base for a problem area is also desirable. Because of the nature of the knowledge base and the way it is built, however, it will almost certainly fail to cover some interesting (sometimes important) possibilities. In a very narrow problem area, for example, there may be 100 attributes of interest, with an average of 4 important values for each attribute. (Only in extreme cases will all attributes be binary.) Thus there would be 79,800 possible rules relating two facts (400 items taken two at a time), over 10 million possible rules relating three facts, and so on. While most are semantically implausible, e.g., because of mutually exclusive values, the cost of checking all combinations for completeness is prohibitive. Checking the inferences made by a system in the context of carefully chosen test cases is currently the best way to check the completeness of coverage of the rules
If there is only one applicable rule, the obvious thing to do is to apply it. Its application will enter new facts in the database. While that may either enable or disable previously inapplicable rules, by our assumption it will never disable a previously applicable rule. If there is more than one applicable rule, we have the problem of deciding which one to apply. Procedure 21 Select-Rule has the responsibility for making this decision. Different data-driven strategies differ greatly in the amount of problem-solving effort they devote to rule selection. A simple and inexpensive strategy is to select the first rule that is encountered in the scan for S — “doing the first thing that comes to mind.” Unfortunately, unless the rules are favorably ordered, this can result in many useless steps. Elaborations intended to overcome such shortcomings can make data-driven control arbitrarily complex.
Methods used for conflict resolution
1 Use the rule with the highest priority. In simple applications, the priority can be established by placing the rules in an appropriate order in the knowledge base. Usually this strategy works well for expert systems with around 100 rules.
2 Use the most specific rule. This method is also known as the longest matching strategy. It is based on the assumption that a specific rule processes more information than a general one.
3 Use the rule that uses the data most recently entered in the database. This method relies on time tags attached to each fact in the database. In the conflict set, the expert system first fires the rule whose antecedent uses the data most recently added to the database.
Uncertainty can be expressed numerically as certainty/confidence factor (cf) or measure of belief (mb)
cf usually is a real number in a particular range, eg, 0 to 1 or -1 to 1
Combining certainties of propositions and rules
Let P1 and P2 be two propositions and cf(P1) and cf(P2) denote their certainties
Then
cf(P1 and P2) = min(cf(P1), cf(P2))
cf(P1 or P2) = max(cf(P1), cf(P2))
given the rule
if P1 then P2: cf = C
then certainty of P2 is given by
cf(P2) = cf(P1) * C
place the responsibility on the knowledge engineer to see that the rules are properly structured. Many problems caused by interactions can be solved by employing a hierarchical structure, with several levels of assertions between the direct observations and the final conclusions. The goal is to localize and limit tic interactions, and to have a rclativcly small number of clauses in a condition and a relatively small number of rules sharing a common conclusion. Note that this limitation on the number of rules does not reduce the amount of evidence considered in reaching a conclusion, but rather controls the ways in which the observations are allowed to interact. A hierarchical structure is typically employed by the experts themselves to reduce the complexity of a problem. Wherever the remaining interactions still prevent the assumption of local independence, the rules have to be reformulated to achieve the desired behavior. For example, in the strongly interacting situation where B, suggests A and B, suggests A, but the simultaneous presence of both B, and I33 rules out A one may have to augment the rule set
{  (B1 – – > A with weight L1)
   (B2 – – > A with weight L2)  }
with the rule (B1 & B2 –> A with weight-m). Thus, rather than viewing probability theory as a paradigm that prescribes how information should be processed, the knowledge engineer employs it as a tool to obtain the desired behavior.
In contrast with the heuristic techniques for reasoning with uncertainty employed in many rule-based expert systems, the theory of belief networks is mathematically sound, based on techniques from probability theory. The formalism of belief networks offers an intuitively appealing approach for expressing inexact causal relationships between domain concepts [7, 20]. A belief network consists of two components [3]:
• A qualitative representation of the variables and relationships between the variables discerned in the domain, expressed by means of a directed acyclic graph G = (V (G),A(G)), where V (G) = {V1,V2,… ,Vn} is a set of vertices, taken as the variables, and A(G) a set of arcs (Vi,Vj), where Vi,Vj∈ V (G), taken as the relationships between the variables.
• A quantitative representation of the ‘strengths’ of the relationships between the variables, expressed by means of assessment functions.
Narrow scope — The task for the system must be carefully chosen to be narrow enough that the relevant expcrtisc can be encoded, and yet complex enough that expertise is required. This limitation is more because of the time it takes to engineer the knowlcdgc into a system including rcfmemcnt and debugging, than because space required for the knowledge base.
Existence of an expert — Thcie are problems so new or so complex that no one rBnks as an expert in the problem area. Generally speaking, it is unwise to expect to be able to construct an expert system in areas where there are no experts.
Agreement among experts — If current problem solving expertise in a task area leaves room for frequent and substantial disagreements among experts, then the task is not appropriate for an expert system.
Data available — Not only must the expertise be available, but test data must be available (preferably online). Since an expert system is built incrementally, with knowledge added in response to observed difficulties, it is necessary to have several test cases to help explore the boundaries of what the system knows.
Milestones definable — A task that can be broken into subtasks, with measurable milestones, is better than one that cannot be demonstrated until all the parts are working
Separation of task-specific knowledge from the rest of the program — This separation is essential to maintain the flexibility and understandability required in expert systems.
Attention to detail — Inclusion of very specific items of knowledge about the domain, as well as general facts, is the only way to capture the expertise that experience adds to textbook knowledge.
Uniform data structures– A homogeneous representation of knowledge makes it much easier for the system builder to develop acquisition and explanation packages.
Symbolic reasoning – It is commonplace in AI, but not elsewhere, to regard symbolic, non-numeric reasoning as a powerful method for problem solving by computers. In applications areas where mathematical methods are absent or computationally intractable, symbolic reasoning offers an attractive alternative.
Combination of deductive logic and plausible reasoning — Although deductive reasoning is the standard by which we measure correctness, not all reasoning — even in science and mathematics — is accomplished by deductive logic. Much of the world’s expertise is in heuristics, and programs that attempt to capture expert level knowledge need to combine methods for deductive and plausible reasoning.
Explicit problem solving strategy — Just as it is useful to separate the domain-specific knowledge from the inference method, it is also useful to separate the problem solving strategy from both. In debugging the system it helps to remember that the same knowledge base and inference method can produce radically different behaviors with different strategies. For example, consider the difference between “find the best” and “find the first over threshold”.
Interactive user interfaces — Drawing the user into the problem solving process is important for tasks in which the user is responsible for the actions recommended by the expert system, as in medicine. For such tasks, the inference method must support an interactive style in which the user contributes specific facts of the case and the program combines them in a coherent analysis.
Static queries of the knowledge base — The process of constructing a large knowledge base requires understanding what is (and is not) in it at any moment. Similarly, using a system effectively depends on assessing what it does and does not know.
Dynamic queries about the line of reasoning — As an expert system gathers data and makes intermediate conclusions, users (as well as system builders) need to be able to ask enough questions to follow the line of reasoning. Otherwise the system’s advice appears as an oracle from a black box and is less likely to be acceptable.
Bandwidth — An expert’s ability to communicate his/her expertise within the framework of an expert system is limited by the restrictions of the framework, the degree to which the knowledge is already well-codified, and the speed with which the expert can create and modify data structures in the knowledge base.
Knowledge engineer — One way of providing help to experts during construction of the knowledge base is to let the expert communicate with someone who understands the syntax of the framework, the rule interpreter, the process of knowledge base construction, and the practical psychology of interacting with world-class experts. This person is called a “knowledge engineer”.
Level of performance — Empirical measures of adequacy are still the best indicators of performance, even though they are not sufficient for complete validation by any means. As with testing new drugs by the pharmaceutical industry, testing expert systems may. best bc accomplished by randomized studies and double blind experiments.
Static evaluation — Because the knowledge base may contain judgmental rules as well as axiomatic truths, logical analysis of its completeness and consistency will be inadequate. However, static checks can reveal potential problems, such as one rule subsuming another and one rule possibly contradicting another. Areas of weakness in a knowledge base can sometimes be found by analysis as well.
Many applications programs that have the characteristics of expert systems have been developed for analysis problems in a diversity of areas including: chemistry [Buchanan78, Carhart79]; genetics [Stefik78]; protein crystallography [Engelmore79]; physics [Bundy79, Larkin80, Novak80,]; interpretation of oil well logs [Barstow79b, Davis81]; electronics troubleshooting [Addis80, Bennett81b, Brown82, Davis82b, Genesereth81b, Kandt81, Stallman77]; materials engineering [Basden82, Ishizuka81]; mathematics [Brown78, Moses71]; medical diagnosis [Chandrasekaran80, Fagan80, Goriy78, Heisdr78, Horn81, Kaihara78, Lindberg81, Pati181, Pople77, Reggia78, Shortliffe76, Shortliffe81, Swartout77, Szolovits78, Tsotsos81, Weiss79bl; mineral exploration [Duda79]; aircraft identification and mission planning [Engelman79]; military situation assessment [McCo1179, Nii82]; and process control [wamdani82].
analysis problems are described using many different terms, including:
l Data Interpretation
l Explanation of Empirical Data
l Understanding a Complex of Data (c.g., signal understanding)
l Classification
l Situation Assessment
l Diagnosis (of diseases, equipment failures, etc.)
l Troubleshooting
l Fault Isolation
l Debugging
l Crisis Management (diagnosis half)
Synthesis problems arise in many fields including: planning experiments in molecular genetics [Fricdland79, Stefik801, configuring the components of a computer system [McDcrmott80, McDcrrnott81]; scheduling [Fox82, Goldstein79, Lauriere78]; automatic programming [Barstow79a, McCune77]; electronics design [deKleer80, Dincbas80, Sussman78], and chemical synthesis [Gelernter77, Wipke77]. These problems have been called:
l Planning (or Constructing a Plan of Action)
l Fault Repair
l Process Specification
l Design (of complex devices or of experiments)
l Configuration
l Therapy (or therapy planning)
l Automatic Programming
l Computer-Aided Chemical Synthesis Planning
In addition to analysis and synthesis problems, expert systems have been built to provide advice on how to USC a complex system [Anderson76, Bennett79, Gencscreth78, Hewitt75, Krueger81, Rivlin80, Waterman79] or to tutor a novice in the use or understanding of a body of knowledge [Brown82, Clancey79, O’Shea79]. These problems arc partly analytic, since the advice or tutorial must be guided by an analysis of the context, and partly synthetic since the advice must be tailored to the user and the problem at hand.
The proficiency of an expert system is dependent on the amount of domain-specific expertise it contains. But expertise about interesting problems is not always neatly codified and waiting for transliteration into a program’s internal representation. Expertise exists in many forms and in many places, and the task’ of knowledge engineering includes bringing together what is known about a problem as well as transforming (not merely transcribing) it into the system.
http://www.theimpactinstitute.org/Teaching/CS4725/rbs.pdf
http://nptel.ac.in/courses/106105078/pdf/Lesson%2018.pdf
http://www.businesssemantics.com/Resources/How_SBVR_Adds_Knowledge_Richness_to_ISO_TC_37_Terminology_Standards.pdf
Note that because it is often easier to design large rule systems as a sequence of independent rulesets to be executed in some order, rule engines sometimes extend the notion of rule execution with mechanisms to orchestrate rulesets – typically called “ruleflows”.
Another approach is to deploy rulesets in a continuous, event-driven rule engine or agent for tasks such as CEP (Complex Event Processing). Other UML constructs such as state models might be used to provide context for rule execution. Modeling the state of entities over time, and the continuous processing of events, usually requires stateful operation of the rule engine so that information is retained in the rule engine between events
For business processes represented in a BPMS (Business Process Management System), detailing decision logic within the process diagram often obfuscates the core business processes. Business processes can represent manual (workflow) or automated tasks, with the commonest form of process representation being BPMN (Business Process Modeling Notation).
The most common format2 for BPM users to represent business rules is the decision table. This provides a common set of condition and action statements, with the table providing different values representing different rules. Some systems map decision tables to a specific algorithm; others will map them to component production rules. Similar models are decision trees and decision graphs.
Note that decision models output from Predictive Analytics tools may or may not be usefully mapped to production rules. One example might be a segmentation model representing a decision tree segmenting customers for marketing offers, which maps to a decision tree and thence production rules. Alternatively a model type such as a neural net representing a face-recognition feature will not usefully map to production rules. Often such analytics tools generate models in a language called PMML (Predictive Model Markup Language)
the “why” column in fact drives all the other ones. Why is your data the way it is? Why do you need to know certain “facts” and “terms” (entities and relationships)? Why do you process this way and no the other? Why isn’t this or that allowed? In fact all these questions have always been done. They just weren’t recorded appropriately in our models.
These tools are for the recording and organizing of the BR.
• QSS DOORs (a requirements management tool actually) (www2.telelogic.com/doors)
• Rational’s Requisite PRO (idem) (www.rational.com)
• Riverton’s HOW (www.riverton.com)
• Usoft’s Teamwork (www.usoft.com) • Business Rules Solutions’ BRS Ruletrack (www.brsolutions.com)
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#3

Electricity and Photovoltaics
Electricity

An alternator is an electrical generator that converts mechanical energy to electrical energy in the form of alternating current. For reasons of cost and simplicity, most alternators use a rotating magnetic field with a stationary armature. Occasionally, a linear alternator or a rotating armature with a stationary magnetic field is used. In principle, any AC electrical generator can be called an alternator, but usually the term refers to small rotating machines driven by automotive and other internal combustion engines. Large 50 or 60 Hz three phase alternators in power plants generate most of the world’s electric power, which is distributed by electric power grids. Alternators are also in Cars, they allow the Car to recharge its battery as it Drives, which is why if your Car battery dies you just have to drive around for a little while after getting it jumped in order for it to be able to start working regularly again, until you can get a new one.

This is a row of Alternators at a Power Plant


Faraday’s law of induction is a basic law of electromagnetism predicting how a magnetic field will interact with an electric circuit to produce an electromotive force (EMF)—a phenomenon called electromagnetic induction. It is the fundamental operating principle of transformers, inductors, and many types of electrical motors, generators and solenoids.




Maxwell’s equations are a set of partial differential equations that, together with the Lorentz force law, form the foundation of classical electrodynamics, classical optics, and electric circuits. These fields in turn underlie modern electrical and communications technologies. Maxwell’s equations describe how electric and magnetic fields are generated and altered by each other and by charges and currents. They are named after the physicist and mathematician James Clerk Maxwell, who published an early form of those equations between 1861 and 1862.



Electrical Engineering Books:

http://www.eletrica.ufpr.br/graduacao/e-books/Mcgraw-Hill%20-%20Principles%20And%20Applications%20Of%20Electrical%20Engineering.pdf

http://webbut.unitbv.ro/Carti%20on-line/Fizica/Nicolaide.pdf

http://iate.oac.uncor.edu/~manuel/libros/ElectroMagnetism/The%20Art%20of%20Electronics%20-%20Horowitz%20&%20Hill.pdf

http://www.fisica.net/ebooks/eletricidade/PANOFSKY%20AND%20PHILIPS%20-%20Classical%20Electricity%20and%20Magnetism%202nd.%20Ed..pdf

http://www.isu.edu.tw/upload/52/33/news/postfile_36558.pdf
Photovoltaics

Solar Technology

http://www.nsf.gov/news/special_reports/science_nation/sprayonsolar.jsp

http://inhabitat.com/hypersolar-increases-solar-efficiency-by-300-with-magnifying-film/

“Alexandre Edmond Becquerel created the world’s first photovoltaic cell in 1839. In this experiment, silver chloride was placed in an acidic solution and illuminated while connected to platinum electrodes, generating voltage and current. Because of this work, the photovoltaic effect has also been known as the “Becquerel effect”. The Photovoltaic effect, a process in which two dissimilar materials in close contact produce an electrical voltage when struck by light or other radiant energy. Light striking crystals such as silicon or germanium, in which electrons are usually not free to move from atom to atom within the crystal, provides the energy needed to free some electrons from their bound condition. Free electrons cross the junction between two dissimilar crystals more easily in one direction than in the other, giving one side of the junction a negative charge and, therefore, a negative voltage with respect to the other side, just as one electrode of a battery has a negative voltage with respect to the other. The photovoltaic effect can continue to provide voltage and current as long as light continues to fall on the two materials. This current can be used to measure the brightness of the incident light or as a source of power in an electrical circuit, as in a solar power system.”

Solar Powered Alternators and Generators

http://www.ewp.rpi.edu/hartford/~lindgc/Project/FinalReport.pdf

http://www.sunrnr.com/uploads/PortableSolarGenerator101.pdf

https://www.princeton.edu/~ota/disk3/1978/7802/780214.PDF

https://www.fkf.mpg.de/1253832/Highly-Efficient-Thermoelectronic-Conversion-of-Solar-Energy-and-Heat-into-Electric-Power.pdf

http://self.org/SELF_White_Paper_-_Solar_vs_Diesel.pdf

http://acep.uaf.edu/media/87693/SolarDieselGridHandbook.pdf

http://drum.lib.umd.edu/bitstream/handle/1903/11276/Jacobus_umd_0117N_11857.pdf;jsessionid=14FF1B6EAF77B77E067BCF6BDD8EF26F?sequence=1

https://www1.eere.energy.gov/femp/pdfs/26042.pdf

http://www1.eere.energy.gov/solar/review_meeting/pdfs/prm2008_white_infinia.pdf

Quantum Dots in Photovoltaics

http://cdn.intechopen.com/pdfs/34814/InTech-Silicon_quantum_dots_for_photovoltaics_a_review.pdf

A quantum dot solar cell is a solar cell design that uses quantum dots as the absorbing photovoltaic material. It attempts to replace bulk materials such as silicon, copper indium gallium selenide (CIGS) or CdTe. Quantum dots have bandgaps that are tunable across a wide range of energy levels by changing the dots’ size. In bulk materials the bandgap is fixed by the choice of material(s). This property makes quantum dots attractive for multi-junction solar cells, where a variety of materials are used to improve efficiency by harvesting multiple portions of the solar spectrum.

Dye-Sensitized Photovoltaics

http://www.e-renewables.com/documents/Solar/Dye-sensitized%20photovoltaic%20cells.pdf

http://krex.k-state.edu/dspace/bitstream/handle/2097/12416/JeremyEssner2011.pdf?sequence=3&isAllowed=y

A dye-sensitized solar cell (DSSC, DSC or DYSC) is a low-cost solar cell belonging to the group of thin film solar cells. It is based on a semiconductor formed between a photo-sensitized anode and anelectrolyte, a photoelectrochemical system. The modern version of a dye solar cell, also known as the Grätzel cell, was originally co-invented in 1988 by Brian O’Regan and Michael Grätzel at UC Berkeley and this work was later developed by the aforementioned scientists at the École Polytechnique Fédérale de Lausanne until the publication of the first high efficiency DSSC in 1991.

Carrier Multiplication in Photovoltaics

http://ccccchem.uci.edu/~lawm/Generating%20Free%20Charges%20by%20Carrier%20Multiplication%20in%20Quantum%20Dots%20for%20Highly%20Efficient%20Photovoltaics.pdf

In solar cell research, carrier multiplication is the phenomenon wherein the absorption of a single photon leads to the excitation of multiple electrons from the valence band to conduction band. In the theory of a conventional solar cell, each photon is only able to excite one electron across the band gap of the semiconductor, and any excess energy in that photon is dissipated as heat. In a material with carrier multiplication, high-energy photons excite on average more than one electron across the band gap, and so in principle the solar cell can produce more useful work.

Colloids in Photovoltaics

https://books.google.com/books?id=bjvHECpuyvAC&printsec=frontcover&dq=Colloidal+Semiconductor+Nanowires:+Synthesis,+Quantum-confinement-effect+google+books&hl=en&sa=X&ved=0CB0Q6AEwAGoVChMI0OOfh8PPyAIVCVOICh0VyQDq#v=onepage&q&f=false

Thiols in Photovoltaics

http://www.light.utoronto.ca/edit/files/publications/2008/barkhouse_2008_1.pdf

Nanocrystal Acid Treatments in Photovoltaics

https://zenodo.org/record/1133/files/post-deposition-Nanotechnology-revised2.pdf

Photoelectrochemical cells

http://gcep.stanford.edu/pdfs/hydrogen_workshop/MacQueen.pdf

Photoelectrochemical cells or PECs are solar cells that produce electrical energy or hydrogen in a process similar to the electrolysis of water.

Thermophotovoltaic Cells

Thermophotovoltaic (TPV) energy conversion is a direct conversion process from heat to electricity via photons. A basic thermophotovoltaic system consists of a thermal emitter and a photovoltaic diode cell.

http://web.ics.purdue.edu/~pbermel/pdf/Celanovic11.pdf

http://jxcrystals.com/publications/40PVSC_Fraas_Manuscript%207-21-2014.pdf

http://calhoun.nps.edu/bitstream/handle/10945/1170/04Jun_Davenport.pdf?sequence=1

Micro-Thermophotovoltaic Cells

http://serve.me.nus.edu.sg/shuchang/Publications/Latest%20papers%20for%20web/yang-chou-shu-li-xue-sensc%20(2003).pdf

Dual-Thermophotovoltaic Cells

http://cpb.iphy.ac.cn/fileup/PDF/2013-10-108402.pdf

Thermophotovoltaic Monolithic Interconnected Modules

http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20030113048.pdf

Photovoltaic Design

http://www.uccs.edu/~rtirado/PV_Resources.pdf

Geometrical Photovoltaic design for shade tolerance

http://arxiv.org/ftp/arxiv/papers/1303/1303.4604.pdf

Photovoltaic Materials:

Amorphous silicon (a-Si) is the non-crystalline form of silicon used for solar cells and thin-film transistors in LCD displays. Used as semiconductor material for a-Si solar cells, or thin-film silicon solar cells, it is deposited in thin films onto a variety of flexible substrates, such as glass, metal and plastic. Amorphous silicon cells generally feature low efficiency, but are one of the most environmentally friendly photovoltaic technologies, since they do not use any toxic heavy metals such as cadmium or lead.

http://www.solarhome.ru/downloads/pv/a-Si_Advantages.pdf

Gallium arsenide (GaAs) is a compound of the elements gallium and arsenic. It is a III-V direct bandgap semiconductor with a zinc blende crystal structure. Gallium arsenide is used in the manufacture of devices such as microwave frequency integrated circuits, monolithic microwave integrated circuits, infrared light-emitting diodes, laser diodes, solar cells and optical windows.

http://www.nrel.gov/docs/fy13osti/57902.pdf

https://mundaylab.umd.edu/wp-content/uploads/JournalOfPV_20121.pdf

Cadmium telluride (CdTe) is a stable crystalline compound formed from cadmium and tellurium. It is mainly used as the semiconducting material in cadmium telluride photovoltaics and an infrared optical window. It is usually sandwiched with cadmium sulfide to form a p-n junction solar PV cell. Typically, CdTe PV cells use a n-i-p structure.

http://www.ijcea.org/papers/290-A00012.pdf

Copper indium gallium (di)selenide (CIGS) is a I-III-VI2 semiconductor material composed of copper, indium, gallium, and selenium. The material is a solid solution of copper indium selenide (often abbreviated “CIS”) and copper gallium selenide. It has a chemical formula of CuInxGa(1-x)Se2 where the value of x can vary from 1 (pure copper indium selenide) to 0 (pure copper gallium selenide). CIGS is a tetrahedrally bonded semiconductor, with the chalcopyrite crystal structure, and a bandgap varying continuously with x from about 1.0 eV (for copper indium selenide) to about 1.7 eV (for copper gallium selenide).

http://depts.washington.edu/uwcei/wordpress/wp-content/uploads/2014/04/PVcelldisplaycards.pdf

Concentrator photovoltaics & High concentrator photovoltaics

Concentrator photovoltaics (CPV) is a photovoltaic technology that generates electricity from sunlight. Contrary to conventional photovoltaic systems, it uses lenses and curved mirrors to focus sunlight onto small, but highly efficient, multi-junction (MJ) solar cells. In addition, CPV systems often use solar trackers and sometimes a cooling system to further increase their efficiency.[2]:30 Ongoing research and development is rapidly improving their competitiveness in the utility-scale segment and in areas of high solar insolation. This sort of solar technology can be thus used in smaller areas. Especially systems using high concentrator photovoltaics (HCPV), have the potential to become competitive in the near future. They possess the highest efficiency of all existing PV technologies, and a smaller photovoltaic array also reduces the balance of system costs. Currently, CPV is not used in the PV roof top segment and far less common than conventional PV systems. For regions with a high annual direct normal irradiance of 2000 kilowatt-hour (kWh) per square meter or more, the levelized cost of electricity is in the range of $0.08–$0.15 per kWh and installation cost for a 10-megawatt CPV power plant was identified to lie between €1.40–€2.20 per watt-peak (Wp).

http://cdn.intechopen.com/pdfs-wm/32594.pdf

http://www.isetc.org/English/Archives/201010/Presentations/ISETC-2010-Oct20-Phil_Metz.pdf

http://www.researchgate.net/publication/227421386_High_Concentrator_PhotoVoltaics_efficiencies_Present_status_and_forecast

http://gcep.stanford.edu/pdfs/solar_workshop_10_04/SolarKing2004.pdf

http://www.crses.sun.ac.za/files/services/conferences/annual-student-symposium-2012/22_November/8_Schultz.pdf

Concentrated solar power (also called concentrating solar power, concentrated solar thermal, and CSP) systems generate solar power by using mirrors or lenses to concentrate a large area of sunlight, or solar thermal energy, onto a small area. Electricity is generated when the concentrated light is converted to heat, which drives a heat engine (usually a steam turbine) connected to an electrical power generator or powers a thermochemical reaction.

Photonics is the science of light (photon) generation, detection, and manipulation through emission, transmission, modulation, signal processing, switching, amplification, and detection/sensing. Though covering all light’s technical applications over the whole spectrum, most photonic applications are in the range of visible and near-infrared light.

http://www.irena.org/DocumentDownloads/Publications/RE_Technologies_Cost_Analysis-CSP.pdf

http://www.nrel.gov/docs/fy01osti/28751.pdf

Photonic Integrated Circuits

A photonic integrated circuit (PIC) or integrated optical circuit is a device that integrates multiple (at least two) photonic functions and as such is similar to an electronic integrated circuit. The major difference between the two is that a photonic integrated circuit provides functionality for information signals imposed on optical wavelengths typically in the visible spectrum or near infrared 850 nm-1650 nm.

http://www.phys.sinica.edu.tw/TIGP-NANO/Course/2008_Spring/classnotes/Nano_MHS_TIGP_20080509_Photonics.pdf

http://www.photonics.ntua.gr/OptikaDiktyaEpikoinwnias/Lecture_6_Integration.pdf

http://optoelectronics.ece.ucsb.edu/sites/default/files/shared/06387568.pdf
member
Activity: 98
Merit: 11
January 02, 2018, 10:43:20 PM
#2
Phalaris Grass- To be used as straw in Cobb building, as well as seed for bird feed.

Giant Reed- To be used for Biodiesel (and sugar) production & for use as a fence.

Datura- To deter animals from eating your crops

Llama & Alpaca- For Clothing, Blanket & other fabric production

Guinea Chickens- To eat ants, ticks & other pests. As well as produce eggs.

Ferrets- To help with running wires for construction, retrieving items & other small tasks

Dogs- To shepherd animals and help disabled people.

Chocolate Plants- For Chocolate production

Blue Agave- For Sugar and Biodiesel production

Homing Pigeons- For delivering messages

Colorado River Toads- To eat snakes, mice & other pests

Lady Bugs- To protect crops

Bees- For honey, wax and pollination

Worms- For composting

Aloe Vera- For Sun Damage and Scar healing

Passion Flower- To grow on houses for beauty and help with cooling costs

Spiders- As pesticides (spiders that eat bugs, but don't harm fruit or humans)

Stuff for eating and Dyes:
Marigold, Indigo, Madder, Pomegranate, Soapnut, Pericarp, Onions, Eucalyptus, Strawberries, Raspberries, Roses, Lavender, St. John's Wort, Foxglove, Syrian Rue.
member
Activity: 98
Merit: 11
January 02, 2018, 10:42:26 PM
#1
Temple Coin will be announced by the Temple Coin Team here on Bitcointalk January 20th or just after (the day we do our Initial Malawi Offering), the ICO is still being done on Facebook and other Social Media, and the Coin is being given away for Free and for Bounty; and already has a good number of users.
https://bitcointalksearch.org/topic/imo-initial-malawi-offering-temple-coin-initial-malawi-offering-imo-2679959

Here is the Overall Temple Coin Syllabus (We will expand on everything in the announcement)
https://bitcointalksearch.org/topic/temple-coin-syllabus-2663919

Once we have established our Town Based Currencies, we will begin setting up Solar Powered Mining Machines. Which will allow for people to generate Income for Free. If there is a town where every house uses the Sun and Alternators/Generators Powered by Solar Panels, then just as an example, 25,000 people living in a Town with Alternators and Generators and Solar Panels, could probably outmine every existing Bitcoin/Litecoin/Ethereum Farm.
https://bitcointalksearch.org/topic/i-am-looking-for-people-who-want-to-create-a-currency-for-their-home-town-2646452

A "PAC" or "Political Action Committee" is the groups that put the Ads on TV for Presidents. Governors, Mayors, etc etc etc. When a commercial comes on and a politician is on at the end saying "I support this Ad" that Ad was made by a PAC. Or when it says "Call Senator X and tell him to stop being a meany" that Ad was probably paid for by a PAC.

The way a PAC makes money is by putting out Ads that lead people to their website at the end for donations, or offer bumper stickers and sell campaign posters. You can also accept donations as a PAC.

 Here is some random information that can help anyone that lives in or is coming to America, it is not legal advice:
Not many people know this, but being a Mayor, Judge or Sheriff usually has NO REQUIREMENTS except to win an election and be a certain age. I have seen people win elections in small towns won with people holding "Honk if You're Voting for X" signs on a busy corner. And becoming a notary or suggesting that people who need jobs become notaries can be very helpful. Being able to notarize documents opens up a lot of doors in business and law. According to law, any notarized document that goes unchallenged, is truth.

Things like Twitter and Facebook have also become important to campaigning.

Here is how to get a political organization (PAC) started
http://www.fec.gov/ans/answers_pac.shtml
Here is the best way to get a Visa for someone
http://en.wikipedia.org/wiki/O_visa

The Supreme court ruled in 1968 that a taxpayer has legal standing to sue the government for misuse of tax funds.
http://en.wikipedia.org/wiki/Flast_v._Cohen

And spreading literature is protected speech
http://en.wikipedia.org/wiki/Martin_v._Struthers

I don't remember the exact acreage, but I think I remember that the minimum for a town is 6 Acres, and the approval of either the County the land is on, or a Vote from the people in the Town that is splitting. A Town needs a Constitution or Town Charter.

One of the first priorities would be to  buy or rent a Well Digger, and you would make sure to have the mineral rights of the land so that you can do this, and you can keep any oil or minerals you find. This could be done before the town was even established, you could just buy 6+ Acres and start doing this.

Once there are wells, you would start building housing for anyone that is going to live there. You could make Earthships, or Cob and Adobe houses. Cob is made with Clay and Straw (Canary Reed Grass) it is also Earthquake and Fire resistant and can also be used as a Material to make Earthships. Earthships are houses that are structured with old tires filled with Cement, then built into a house. Earthships are usually built facing the Sun Rise to save on heating, and they usually use Solar Panels for electricity and Rain collection for water, some people also grow plants on top of Earthships and a garden is usually kept inside.

Earthship


Cob House


Adobe House


 Once there were a few houses and the town founders were all living there, you would start installing plumbing and electricity. Ferrets have been used to run wire through tubes or walls, so Ferets could be a useful pet for any town. You would also probably want to establish an internet connection, which may involve Antennaes and Mesh Networks (LAN based internet) if you are far from any major city.

You may also want to build something like a Geodome for use as a Greenhouse. Depending where you are you can use the land to farm, but having Greenhouses can be useful even if you can farm the land, just because the Greenhouse effect can be very useful on small groups of plants, while farming 100% outdoors is more about keeping it simple. Geodomes make good green houses because their shape allows them to insulate very well. Dried out San Pedro cactus can be used as Fencing (they do this in Mexico). Giant Reed (Sugar Cane) can be grown to make sugar. Chili Peppers could be grown to start a town Hot Sauce brand, etc. There is an Animal called a Guinea Chicken that lays eggs like a regular chicken, but they are a little smaller and a little more cone shaped. They make good guard dogs (even though they are chickens) because they will make noises if they see someone they don't recognize and they eat ticks & spiders they come across. Dragonflies can be bred to keep other bug populations down. If you grow certain cacti (such as Sanguaro) you can help Bats as they migrate, and if you put up bird houses and duck holes, you can help those species become abundant in the area. The town should also try to start an Orchard/Grove, apples, pears, cherries, Lemons, Limes or any other fruit. Trees can be cut and cloned in order to have an army of trees feeding everyone.


From here you would start trying to build community centers. Such as a Temple, or a Farmers Market (if you make lots, they can even be rented out to people who come visit, here is Canton Texas as an example. It is one big flea market town, that is their economy. And you can even buy Dogs and other animals there, just kind of a "if you build it, they will come" type of thing.) It would also be good to found a Restaurant, Library and a Media Center, so that people can start to outreach on platforms like Youtube. It would also be a good idea for someone to breed dogs and cats so that people can buy pets, as well as for someone to start a pond and a hatchery so that people can fish. Farming rabbits can help make good fertilizer (poop), pets and food.
http://www.firstmondaycanton.com/sites/default/files/styles/homepage_banner/public/homepage-banner/homepage2.png?itok=Ny7mWeau

From here you would either try to attract things like Car Dealerships, Gas Stations, Grocery Stores, Hardware stores or people in Town would start founding their own.

Everyone thinks that the most important Election in America is when we Vote for President, and to a lesser extent when we Vote for Congress. But neither of those really matter. What really matters is who is Sheriff in your town, who is a Judge in your town, who is a District Attorney in your town and if you Create your own Town.


Democracy is not meant to be any harder than forming a Tribe, and democracy is not just meant for Governments. There is supposed to be democracy inside Religious bodies as well as within Political parties themselves.



The voting body or city was known as the "Polis", and the Center of the Polis was the Agora. In some places the Agora had elaborate temple structures in order to maintain different functions that the groups did there, but when they first started they were usually as simple as an area marked by Stones as a border. The People would gather at the Agora and cast their votes.

As the Agora was used more and more, and functions were decided, structures would be built along the edges of the Agora, but the center was usually left as a wide open space for people to gather. the buildings they usually built were Court Houses and Town Halls and stuff. Extended Porticoes were sometimes used so that functionality of the space was not lost in bad weather. Sometimes Porticoes were built pretty much as their own structures, with a line of rooms at the back, which could be used as offices. Statues dedicated to different groups would be kept at these places, so that they could all gather in their individual groups or together.

The Polis itself was a larger reflection of the Agora. It would start off as a region of land which a group of people claimed as their own, with Borders such as rivers, mountains, etc. and slowly through the democratic process, groups were formed and projects were started, until farms were growing and cities were booming.

Leagues and Hegemonies operated like the modern United States or EU, or United Nations, in order to get things done between different nations and work together in times of war.

Eventually the Polis itself became Warlike and only eligible military members could vote, this eventually evolved into what is known as the Police, Policia, or the Polis. During Hellenistic times the Polis became a battle between Rich Oligarchs, and poor but armed citizens.



Today we can see most of the Polis and Agoras purpose being utilized in Universities, but not in too many other places.

Archive keeping is an important part of Government and Democracy. If people do not have information from past generations, then they can not make decisions for the future, at least not without running in to problems that would have been avoided if they had information about previous generations.



In Ancient Greece the most well kept archives were Law, lists of Public Representatives and the Winners of Sporting events. This is not much different from now, except now there is also the occasional story about someone who saves some animals, or starts a homeless shelter, or has an event, etc. But just like today, other records were kept by more specialized groups. For example, Temples were often a place where you could find archives, since the priests and worshipers would deposit anything important there. It would kind of be like if a church started a library, and asked all their members to donate any books they could that were written about Bible history or written by Historical Priests. Over like 100 years, that Church might actually have a pretty cool collection of stuff, even to non-Christians, it would be kind of like a Musaeum/Library of History.


I personally think that more "Temples" should be made, and more Archives should be kept. Even if it just happens in people's houses, there should be people collecting things like: Books written by people in their town, Books written by people in their family, Books written by Historical Figures, Books written in certain time periods, etc.

Most Theater, both Plays and Movies, are based on Greek and Roman Plays. Almost every Combination of Good guy and bad guy in almost any environment was already written about in ancient Greece, a lot of people just change the characters and settings to fit modern or even future events, and then make modern movies. For example. the Movie "Prometheus" is just Greek storytelling in Space. Even when it is not on purpose, most movies copy the story-line of existing Greek dynamics. So for an example, I think it would be cool if people who liked movies collected the plays that started the movies they liked, then found other movies based on those plays and put them all together. How awesome would it be to see the progression of a story all the way from ancient Greek telling to modern Movie "Magic".

Another cool example would be for someone who is interested in the modern Military of America, they could collect books written by people in service, then they could go through all the tactics that were used and the stuff that the people went through, and see if they can find other generals through history who used similar tactics, or Books by people who were under generals who used similar tactics, and then if there is ever a military mind that sees that collection in the future, it could effect the way he does things. Since he may learn something about the humanity behind all the tactics.

I am pretty sure you could also start with the books written by the last few modern American presidents, then after reading their books branch off into other areas that you notice while reading their books, and then keep copies of Obama's executive orders and any things the next few presidents do, and eventually you would have an archive that could definitely be useful to voters.



I have talked to people about the idea of Towns, and it seems like a lot of people think it is some sort of magic Craft to start a town. So here are some classifications and Political possibilities that most people don't usually think about.

Tribe: Tribes are the societies that exist outside of states. The State is equal to the Greek Polis, with its own sovereignty, and ability to join other states in a Union, League, etc. The people come together at the Agora (Capitol Hill in America) to make decisions, this is the state. Tribes are much more loosely governed. Tribes can be a collection of families, or a collection of religious groups, etc. and usually have some form of leader, either chosen based on the Tribes specialty (the best Hunter, or the best Warrior, or the Best Artisan, or the Oldest, etc).

A Club is a collection of 2 or more people that have come together for some common purpose. A Community is similar, except that is is a looser organization, and usually they just have the same values, not necessarily the same or even similar goals.

A Gang is any group of friends or a family unit that has a leader. For example, if there is a military family who all look up to 1 Grandpa figure who first joined the Military and started a tradition, that is a form of Gang. It is not an Organized Crime Gang, but it is a form of Gang.

Townships are the most basic form of Town. In America there are 2 forms of Townships, a Survey Township and a Civil Township. A Survey Township is just a unit of land that has been measured properly by a Surveyor, a Civil township operates like a County, in some states they are treated like a regular "Incorporation" type town. Civil Townships exist in 20 of the 50 states.

The overall name for Towns, Townships, Villages, Cities, Counties, etc is Municipal Corporation. To establish a town, you need a Town Charter. A Town Charter would be created by/in a State or County Legislature, and the people of that County would Vote for the new Town to be formed. A Town could also Vote to Split.

Villages are smaller than towns, and are not necessarily Incorporated. Depending on the State, a Village can just be a town that has formed with its own Government Body, but a smaller population than a town.

A Town is incorporated and follows State laws to form.

City is really just a big town in most places.

Counties are Administrative divisions designated by a state.

Common Law is how we get Laws from Court cases. 2 Modern Examples are:
1. The Affordable Care Act aka Obamacare
2. The Hobby Lobby Supreme Court Case

When the United State Supreme Court makes a ruling, it becomes "The Law of the Land" for all of the United States. This is common law. The reason it exists is this, for example: If you bring a Wolf to town, and no one has ever had a Wolf as a pet there, people might freak out. So the Police might get called, and they might give you a ticket, which establishes a Court Date. Then you have to go to Court, and argue your case, and whatever the Judge decides is the new Law for Wolf owners in your town. Maybe they say you have to give it a muzzle, maybe they say you can't own it without a license, maybe they say you can't own it at all etc.

Common Law works on all levels. US Supreme Court makes rules for the Country, State Supreme Courts make rules for the State, a County Judge makes rules for the County, and a City Judge makes rules for the Town.

A Common Heritage of Mankind is something that no one can really own, but everyone can use. Examples are the Ocean and Space.

An Embassy or a Diplomatic Mission is a group of people from one state/country, who own land in another state/country, and work to establish treaties and accomplish goals in that country/state. Once the Diplomatic mission establishes permanency it becomes an Embassy and the head of the Embassy is considered the Ambassador. Embassy can also just refer to the building or office that the Diplomatic mission is operating from.

For Democratic Non-Violent Protests, there are some Organizational tactics that can be used. If Clubs, Tribes are established, it makes it much easier to protest, this is why Unions are more successful when striking than regular employees are.

Here are the Supreme Court Rulings that are the "Law of the Land" and defend our Rights, such as the Right to Gather, and the Right to Free Speech.

Public Sit ins
http://en.wikipedia.org/wiki/Brown_v._Louisiana

Police May not Plot Against a Protest
http://en.wikipedia.org/wiki/Carroll_v._Princess_Anne

The Local, State or Federal Government should not put "Breach of the Peace Statutes" in place, because they are more likely to incite violence than not
http://en.wikipedia.org/wiki/Cox_v._Louisiana

Police Breaking apart a Peaceful Crowd is Illegal
http://en.wikipedia.org/wiki/Edwards_v._South_Carolina

Most protests don't have any previous organizational structure, so the best way to establish it for the first time is to get people to line up in rows, then give each row of people a flyer to explain what their overall goals should be as a group, This way people can choose to do different things, but be following a main plan within the group that they talk to throughout the protest. Do not try to get people to line up constantly, this is only to create the foundational structure to accomplish a goal other than being loud, not a way to create a regimented force of soldiers. When passing out any other objects or flyers, they should be something that encompasses all the established groups.

The reason you want to make groups is to create more diverse functionality and thought. This does not need to be a division within the whole group, only within the core people that are there first. For example, if there are a group of people with Walkie Talkies in your protest, you would want to make this division within that group of people, so that you could all coordinate different plans. Examples of divisions of labor would be Making/Passing out Protest signs, Giving People Rides or Collecting Emails/Phone Numbers, Setting up a space where people can get water and maybe food, Making videos of specific protesters or groups and getting their names, Keeping an eye on the crowd to make sure no one is bringing like Molotov Cocktails in to start a riot, etc.

If you have groups you can do various things instead of just trying to be some random "Administrative Entity" over the protest. Goals should be to go to Libraries, Universities or Local/National News Broadcasting stations and holding "Sit Ins" or at least "Stand Outsides". These places are places that will get more people to come and join, as well as being more likely to be News worthy.

If you do NOT want to be in the News, use Profanity a lot, put a Cuss word in your Groups name (Ex: You can call yourself the Fuckers and it won't be in the news) and if you want to stay off of Live Broadcasting, write the word "f***" on your forehead.

At least one person should try to get Emails or Phone numbers from protesters, the people there are obviously interested in learning more.

Any goal that you want to accomplish politically should be something you care passionately enough about to make a Pamphlet or a Brochure type thing, at least made up of a 2 pages and folded together to make a pamphlet. Not a lot of people understand that they can start political organizations (look up "How to start a PAC" if you want to make one) or how to run for office in local campaigns. So having information about how to do these things can be extremely helpful.

Protests are not going to accomplish much more than getting the word out, and eventually you have to tap in to Democracy and protest by getting new people in Office as Judges, Sheriffs and Mayors. TONS OF CITIES have District Attorney's that run unopposed. People only think to Vote for Mayor and Sheriff and stuff, they don't think of running themselves, and they definitely don't worry about who the District Attorney is. But that is such an important position as far as deciding who goes to jail in town.

During a Protest, Police should take the role of an outside presence. They do not need to be involved, and according to training videos from the 60s, they are only supposed to put plain clothes officers in the protest. And if you watch the Yippies and the Hippies in the 60s talking in videos and stuff, they talk about how part of the plan was to get the Police to beat on the Plain clothed officers with them.

Police should not take an offensive position, but they probably will. If they do, what they are going to do is a "Show of Force". This will include loud barking, and possibly banging on shields or stomping feet.

If the Police do this, the best response is to get people to start doing some kind of beat. Like even just clapping and stomping "We will rock you" is sufficient.

If the police move forward, the main protesters should not run at the police to fight them. The main protesters should make their way to the back of the crowd to form a ring. If you hold hands behind the other protesters, they will not be so easy to move back, and you will be able to hold your position without them moving you. Having something to create cohesive units can also help, for example, if you have brooms or something, you could work together against the shields more effectively.

These tactics are meant to be a response to police over action, like in Occupy and the early days of Ferguson, not a way for protesters to initiate action against the police. The best way to initiate action against the police is to read their oath to them, or just elect a new Sheriff.

People like to think that Medicine and Science happen in Sterilized rooms, where everyone wears a lab coat, and everyone knows exactly what the outcome of everything will be. That is not science, it might be a routine test some scientists are doing, but that is not the bulk of how science moves forward in leaps and bounds.

For example, Penicillin was not discovered by someone working for Pfizer in a sterile lab, trying to cure disease. It was discovered by a messy scientist, who was eating in his lab space, and accidentally left a sandwich out. When he came back to the sandwich days later, it had mold growing on it. He put this mold in a Petri dish with other Bacteria, and it ate all the other bacteria. This is how Antibiotics jumped forward.

The first person to invent Vaccines also kind of did so on accident, or at least the guy he copied did. The inventor of Vaccines is Edward Jenner, but 30 years before he invented Vaccines, his friend John Fewster was randomly doing studies where he gave people smallpox on purpose so he could study their reaction, and one time he did it someone didn't react and he questioned them, and it turned out that that person had previously had Cow Pox. So he told people about this and 30 years later Vaccines existed.

Not all science happens like this, but a lot of it does. A more modern example is a spider they found in the Amazon, this spider ha venom that works similar to Viagra. But when it bites you, a guys penis will get so hard it explodes or stops working via ruptured blood vessels or something. So now that some people have died from this (I think you would die, or hope kinda) they are now working on a way to turn this venom in to the new Viagra. So this kind of stuff happens all the time.

I just wanted to point those things out to say, Western Medicine is not the regimented, sterilized, perfect art we think it is. It is just regular people that went through some higher education, and now they are figuring some stuff out. And I told you that because I want to show you where it comes from.

Western Medicine starts in ancient Greece with the worship of the God Asclepius. Asclepius was always identified with snakes, and usually a non-Venomous snake would be kept at his temples, the snakes had free reign inside the temples and were allowed to slither on the floor in rooms where patients slept. The Aesculapian snake is actually a species of snake.

The Temples were known as Asclepeion, and they operated much like Hospitals where people would come from all around to come be healed. The way the Doctors would heal the person is by inducing a dream and interpreting it, then giving the person a prescription based on the dream. This is almost identical to Native American Shamanism, you may have heard people call Ayahuasca "Medicine", this is the context of that. The Shamans are meant to take Ayahuasca and come back to this "realm" with a prescription. And according to legend, the plants themselves actually told the Natives how to make Ayahuasca, since you have to mix 2 specific plants in the jungle. If you want to try to find the ancient Greek writings about this, there is supposedly a book called "Sacred Stories" by Aelius Aristides. He was one of these doctors.

The Rod of Asclepius is a common medical symbol, it is a staff with a snake on it. The doctors themselves were known as Asclepiad, the most famous of which is probably Hippocrates. Hippocrates invented the Hippocratic oath, which Doctors still say today.

Hippocrates is still considered the Father of Western Medicine to this day, he identified a few things that are still named after him sometimes, like Hippocratic Fingers, and Hippocratic Face. He also started the classifications like: Acute, Epidemic and Chronic. He also invented the Hippocratic bench, which was a forerunner to Chiropractor tables and some Torture Devices.

I am not suggesting we go back to the Greek Medical model, I just wanted to point out that the things we take the most serious, sometimes (usually) started as people playing with snakes and interpreting dreams.

For a town to grow, there are a few main factors, first the obvious one. If the town is near an interstate it has a better chance of growing, this is the best place for hotels and gas stations to get constant business in a small town, (Truck stops, etc) it can also allow for a mall to be profitable. If you are a small town and you are not on an interstate, a Flea Market like Trade Days in Texas is a much more likely thing to maintain than a mall.



Second is Airports. being near an airport or opening a small one could completely change a town, there are some countries that are able to do amazing business deals just by flying in executives from big companies and having them put a factory or something in town, which can offer jobs, but is not the best way to build an economy that isn't corrupt.

Next is railroads. Most people don't even realize this, but railroads actually transport a LOT of stuff, and if you happen to be on a railway, you might be able to start some industry, as well as have a way for people to come in to town to move or visit.

Also, Bus stations. Grey Hound and other companies like this can help people in town get places, help family visit, and I have seen towns where they have a whole cafeteria and little outlet mall things pretty much centered around a Grey Hound station and the people stopped there waiting for a bus.

And, Rivers. They are not so much used for shipping anymore, but they are good for business. People can open fishing shops, or rafting facilities and all kinds of stuff for tourists.

Then a town can do things like start sports teams, or open a race track, or a Renaissance fair, or build the world's biggest something, or promote a local liquor brand, or make a place for concerts and comedians, etc etc etc.
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