Please Look Up Everything I Say About History, Plants, etc. I Always Give Names That Can Be Found Online.

Sunday, March 19, 2017

Bazillion Beings, the Cloud and the Internet of Things #IoT

Everyone should follow this twitter account:
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 (They said they are launching in July), 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.

Wednesday, March 8, 2017

The Prince



http://www.constitution.org/mac/prince.pdf

Kim Jung Un has a brother Brother, Kim Jung Nam (who was just killed by the Assassin with the "LOL" shirt), it is thought that Kim Jung Un killed his brother because he was living in China, and could have been installed by the Chinese Government if they ever decided to assassinate Kim Jung Un. So it is thought that he killed his own brother to remove that possibility.



But Kim Jung Nam has a son named Kim Han Sol. Kim Han Sol just released a video saying that he and his mom and the rest of his family are staying with a group that is protecting them, and that they are safe from Kim Jung Un.

And it can be assumed that North Korean leaders are seeing this video, meaning that they know there is a group out there that is willing to take them in if they defect from the North Korean regime. So someone could assassinate Kim Jung Un and then defect and be protected by this group.

Saturday, March 4, 2017

The New Whig Party Platform

New Whig Party Platform

• Corruption Regulation: Gang injunctions for executives of companies involved in corruption cases.

• Congress > President: Encourage Congress to write laws to expand rights mentioned in the Constitution and the Amendments, rather than focusing primarily on regulations.

• Modernization: Expert Systems, Cloud Technology, Ubiquitous Computing; 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.'. A restructured educational system which provides a student power to determine his/her course of study, student participation in over-all policy planning; an educational system which breaks down its barriers between school and community; a system which uses the surrounding community as a classroom so that students may learn directly the problems of the people. A political system which is more streamlined and responsive to the needs of all the people regardless of age. sex, or race; perhaps a national referendum system conducted via television, telephone or Crypto-Asset based voting system.

• Community Control: Adoption of the community control concept in our ghetto areas; an end to the cultural and economic domination of minority groups.

• Crypto-Banking: Crypto-Currency shall be treated like any other line of code or literature.

• Gold, Silver, Water, Oil, or Hash Standard: The Currency of the United States shall be backed by an actual commodity, which it can be exchanged for at any banking institution.

• Anti-Indian Removal: NDAPL, etc.

• Taxing Imports, but Increasing Visa Opportunities: Higher taxes on imports, but a more streamlined and simplified Visa program.

• Farm Subsidies: A program of ecological development that would provide incentives for the decentralization of crowded cities so as to expand them out, and intertwine industry and ecology. Not forced, simply incentivized.

• War on Poverty: The abolition of pay housing, pay media, pay transportation, pay food, pay education, pay clothing and pay medical health.

• Anti-War: An immediate end to the war in the Middle East/North Africa/Arabian Peninsula and a restructuring of our foreign policy which eliminates aspects of military, economic and cultural imperialism; the withdrawal of all foreign based troops and the expansion of Refugee Programs. A program that encourages and promotes the preservation of art and architecture in war zones. American troops should be respected by the communities they encounter.

• Ending the Drug War: The overturning of the Controlled Substances Act, to be replaced by tax regulations in order to promote domestic manufacturing; the freeing of all prisoners currently imprisoned on narcotics charges.

• Judicial Reform: A judicial system which works towards the abolition of all laws related to crimes without victims; that is, retention only of laws relating to crimes in which there is an unwilling injured party: i.e. murder, rape, or assault.

• Weapons Education Programs: Living in a country in which we have the right to bear arms, no one should be confused about what to do when someone pulls out a gun in public.

Friday, March 3, 2017

Expert Systems are the Future of Education


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 <condition> THEN <action>
IF the ‘traffic light’ is ‘green’ THEN the action is go
IF the ‘traffic light’ is ‘red’ THEN the action is stop

IF <antecedent 1>           IF <antecedent 1>
AND  <antecedent 2>     OR  <antecedent 2>
.                                          .
.                                          .
AND <antecedent n>      OR  <antecedent n>
THEN <consequent>       THEN <consequent>
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 <attribute> of <object> is <value> with certainty <CD

The basic EMYCIN syntax for a rule is:

PREMISE: ($AND (<clause1>…<clause-n>))
ACTION: (CONCLUDE <new-fact> <CF>)

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.




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)

Tuesday, February 21, 2017

Trump's DHS "Border Security Memo"

Everyone should begin protesting at County lines in order to bring Venue and Jurisdiction to the forefront of all local courts' attentions.



Baltimore


Ferguson

El Gasolinazo



MEMORANDUM FOR:
Kevin McAleenan Acting Commissioner Secretary U.S. Department of Homeland Security

Thomas D. Homan Acting Director U.S. Immigration and Customs Enforcement

Lori Scialabba Acting Director U.S. Citizenship and Immigration Services

Joseph B. Maher Acting General Counsel

Dimple Shah Acting Assistant Secretary for International Affairs

Chip Fulghum Acting Undersecretary for Management

John Kelly Secretary

February 17, 2017
SUBJECT:
Implementing the President's Border Security and Immigration Enforcement Improvements Policies
This memorandum implements the Executive Order entitled "Border Security and Immigration Enforcement Improvements," issued by the President on January 25, 2017, which establishes the President's policy regarding effective border security and immigration enforcement through faithful execution of the laws of the United States. It implements new policies designed to stem illegal immigration and facilitate the detection, apprehension, detention, and removal of aliens who have no lawful basis to enter or remain in the United States. It constitutes guidance to all Department personnel, and supersedes all existing conflicting policy, directives, memoranda, and other guidance regarding this subject matter, except as otherwise expressly stated in this memorandum.

A. Policies Regarding the Apprehension and Detention of Aliens Described in Section 235 of the Immigration and Nationality Act.
The President has determined that the lawful detention of aliens arriving in the United States or otherwise described in section 235(b) of the Immigration and Nationality Act (INA) pending a final determination of whether to order them removed, including determining eligibility for immigration relief, is the most efficient means by which to enforce the immigration laws at our borders. Detention also prevents such aliens from committing crimes while at large in the United States, ensures that aliens will appear for their removal proceedings, and substantially increases the likelihood that aliens lawfully ordered removed will be removed.
These policies are consistent with INA provisions that mandate detention of such aliens and allow me or my designee to exercise discretionary parole authority pursuant to section 212(d)(5) of the INA only on a case-by-case basis, and only for urgent humanitarian reasons or significant public benefit. Policies that facilitate the release of removable aliens apprehended at and between the ports of entry, which allow them to abscond and fail to appear at their removal hearings, undermine the border security mission. Such policies, collectively referred to as "catchand-release," shall end.
Accordingly, effective upon my determination of: (1) the establishment and deployment of a joint plan with the Department of Justice to surge the deployment of immigration judges and asylum officers to interview and adjudicate claims asserted by recent border entrants; and, (2) the establishment of appropriate processing and detention facilities, U.S. Customs and Border Protection (CBP) and U.S. Immigration and Customs Enforcement (ICE) personnel should only release from detention an alien detained pursuant to section 235(b) of the INA, who was apprehended or encountered after illegally entering or attempting to illegally enter the United States, in the following situations on a case-by-case basis, to the extent consistent with applicable statutes and regulations:

1. When removing the alien from the United States pursuant to statute or regulation;

2. When the alien obtains an order granting relief or protection from removal or the Department of Homeland Security (DHS) determines that the individual is a U.S. citizen, national of the United States, or an alien who is a lawful permanent resident, refugee, asylee, holds temporary protected status, or holds a valid immigration status in the United States;

3. When an ICE Field Office Director, ICE Special Agent-in-Charge, U.S. Border Patrol Sector Chief, CBP Director of Field Operations, or CBP Air & Marine Operations Director consents to the alien's withdrawal of an application for admission, and the alien contemporaneously departs from the United States;

4. When required to do so by statute, or to comply with a binding settlement agreement or order issued by a competent judicial or administrative authority;

5. When an ICE Field Office Director, ICE Special Agent-in-Charge, U.S. Border Patrol Sector Chief, CBP Director of Field Operations, or CBP Air & Marine Operations Director authorizes the alien's parole pursuant to section 212(d)(5) of the INA with the written concurrence of the Deputy Director ofICE or the Deputy Commissioner of CBP, except in exigent circumstances such as medical emergencies where seeking prior approval is not practicable. In those exceptional instances, any such parole will be reported to the Deputy Director or Deputy Commissioner as expeditiously as possible; or

6. When an arriving alien processed under the expedited removal provisions of section 235(b) has been found to have established a "credible fear" of persecution or torture by an asylum officer or an immigration judge, provided that such an alien affirmatively establishes to the satisfaction of an ICE immigration officer his or her identity, that he or she presents neither a security risk nor a risk of absconding, and provided that he or she agrees to comply with any additional conditions of release imposed by ICE to ensure public safety and appearance at any removal hearings.

To the extent current regulations are inconsistent with this guidance, components will develop or revise regulations as appropriate.
As the Department works to expand detention capabilities, detention of all such individuals may not be immediately possible, and detention resources should be prioritized based upon potential danger and risk of flight if an individual alien is not detained, and parole determinations will be made in accordance with current regulations and guidance. See 8 C.F.R. §§ 212.5, 235.3. This guidance does not prohibit the return of an alien who is arriving on land to the foreign territory contiguous to the United States from which the alien is arriving pending a removal proceeding under section 240 of the INA consistent with the direction of an ICE Field Office Director, ICE Special Agent-in-Charge, CBP Chief Patrol Agent, or CBP Director of Field Operations.

B. Hiring More CBP Agents/Officers
CBP has insufficient agents/officers to effectively detect, track, and apprehend all aliens illegally entering the United States. The United States needs additional agents and officers to ensure complete operational control of the border. Accordingly, the Commissioner of CBP shall-while ensuring consistency in training and standards- immediately begin the process of hiring 5,000 additional Border Patrol agents, as well as 500 Air & Marine Agents/Officers, and take all actions necessary to ensure that such agents/officers enter on duty and are assigned to appropriate duty stations, including providing for the attendant resources and additional personnel necessary to support such agents, as soon as practicable.
Human Capital leadership in CBP and ICE, in coordination with the Under Secretary for Management, Chief Financial Officer, and Chief Human Capital Officer, shall develop hiring plans that balance growth and interagency attrition by integrating workforce shaping and career paths for incumbents and new hires.

C. Identifying and Quantifying Sources of Aid to Mexico
The President has directed the heads of all executive departments to identify and quantify all sources of direct and indirect Federal aid or assistance to the Government of Mexico. Accordingly, the Under Secretary for Management shall identify all sources of direct or indirect aid and assistance, excluding intelligence activities, from every departmental component to the Government of Mexico on an annual basis, for the last five fiscal years, and quantify such aid or assistance. The Under Secretary for Management shall submit a report to me reflecting historic levels of such aid or assistance provided annually within 30 days of the date of this memorandum.

D. Expansion of the 287(g) Program in the Border Region
Section 287(g) of the INA authorizes me to enter into a written agreement with a state or political subdivision thereof, for the purpose of authorizing qualified officers or employees of the state or subdivision to perform the functions of an immigration officer in relation to the investigation, apprehension, or detention of aliens in the United States. This grant of authority, known as the 287(g) Program, has been a highly successful force multiplier that authorizes state or local law enforcement personnel to perform all law enforcement functions specified in section 287(a) of the INA, including the authority to investigate, identify, apprehend, arrest, detain, transport and conduct searches of an alien for the purposes of enforcing the immigration laws. From January 2006 through September 2015, the 287(g) Program led to the identification of more than 402,000 removable aliens, primarily through encounters at local jails.
Empowering state and local law enforcement agencies to assist in the enforcement of federal immigration law is critical to an effective enforcement strategy. Aliens who engage in criminal conduct are priorities for arrest and removal and will often be encountered by state and local law enforcement officers during the course of their routine duties. It is in the interest of the Department to partner with those state and local jurisdictions through 287(g) agreements to assist in the arrest and removal of criminal aliens.
To maximize participation by state and local jurisdictions in the enforcement of federal immigration law near the southern border, I am directing the Director of ICE and the Commissioner of CBP to engage immediately with all willing and qualified law enforcement jurisdictions that meet all program requirements for the purpose of entering into agreements under 287(g) of the INA.
The Commissioner of CBP and the Director of ICE should consider the operational functions and capabilities of the jurisdictions willing to enter into 287(g) agreements and structure such agreements in a manner that employs the most effective enforcement model for that jurisdiction, including the jail enforcement model, task force officer model, or joint jail enforcement-task force officer model. In furtherance of my direction herein, the Commissioner of CBP is authorized, in addition to the Director of ICE, to accept state services and take other actions as appropriate to carry out immigration enforcement pursuant to 287(g).

E. Commissioning a Comprehensive Study of Border Security
The Under Secretary for Management, in consultation with the Commissioner of CBP, Joint Task Force (Border), and Commandant of the Coast Guard, is directed to commission an immediate, comprehensive study of the security of the southern border (air, land and maritime) to identify vulnerabilities and provide recommendations to enhance border security. The study should include all aspects of the current border security environment, including the availability of federal and state resources to develop and implement an effective border security strategy that will achieve complete operational control of the border.

F. Border Wall Construction and Funding
A wall along the southern border is necessary to deter and prevent the illegal entry of aliens and is a critical component of the President's overall border security strategy. Congress has authorized the construction of physical barriers and roads at the border to prevent illegal immigration in several statutory provisions, including section 102 of the Illegal Immigration Reform and Immigrant Responsibility Act of 1996, as amended, 8 U.S.C. § 1103 note.
Consistent with the President's Executive Order, the will of Congress and the need to secure the border in the national interest, CBP, in consultation with the appropriate executive departments and agencies, and nongovernmental entities having relevant expertise- and using materials originating in the United States to the maximum extent permitted by law- shall immediately begin planning, design, construction and maintenance of a wall, including the attendant lighting, technology (including sensors), as well as patrol and access roads, along the land border with Mexico in accordance with existing law, in the most appropriate locations and utilizing appropriate materials and technology to most effectively achieve operational control of the border.
The Under Secretary for Management, in consultation with the Commissioner of CBP shall immediately identify and allocate all sources of available funding for the planning, design, construction and maintenance of a wall, including the attendant lighting, technology (including sensors), as well as patrol and access roads, and develop requirements for total ownership cost of this project, including preparing Congressional budget requests for the current fiscal year ( e.g., supplemental budget requests) and subsequent fiscal years.

G. Expanding Expedited Removal Pursuant to Section 235(b)(l)(A)(iii)(I) of the INA
It is in the national interest to detain and expeditiously remove from the United States aliens apprehended at the border, who have been ordered removed after consideration and denial of their claims for relief or protection. Pursuant to section 235(b )(I )(A)(i) of the INA, if an immigration officer determines that an arriving alien is inadmissible to the United States under section 2I2(a)(6)(C) or section 212(a)(7) of the INA, the officer shall, consistent with all applicable laws, order the alien removed from the United States without further hearing or review, unless the alien is an unaccompanied alien child as defined in 6 U.S.C. § 279(g)(2), indicates an intention to apply for asylum or a fear of persecution or torture or a fear of return to his or her country, or claims to have a valid immigration status within the United States or to be a citizen or national of the United States.
Pursuant to section 235(b)(l)(A)(iii)(I) of the INA and other provisions of law, I have been granted the authority to apply, by designation in my sole and umeviewable discretion, the expedited removal provisions in section 235(b)(l)(A)(i) and (ii) of the INA to aliens who have not been admitted or paroled into the United States, who are inadmissible to the United States under section 212(a)(6)(C) or section 212(a)(7) of the INA, and who have not affirmatively shown, to the satisfaction of an immigration officer, that they have been continuously physically present in the United States for the two-year period immediately prior to the determination of their inadmissibility. To date, this authority has only been exercised to designate for application of expedited removal, aliens encountered within 100 air miles of the border and 14 days of entry, and aliens who arrived in the United States by sea other than at a port of entry.
The surge of illegal immigration at the southern border has overwhelmed federal agencies and resources and has created a significant national security vulnerability to the United States. Thousands of aliens apprehended at the border, placed in removal proceedings, and released from custody have absconded and failed to appear at their removal hearings. Immigration courts are experiencing a historic backlog ofremoval cases, primarily proceedings under section 240 of the INA for individuals who are not currently detained.
During October 20 I 6 and November 20 I 6, there were 46,184 and 47,215 apprehensions, respectively, between ports of entry on our southern border. In comparison, during October 2015 and November 2015 there were 32,724 and 32,838 apprehensions, respectively, between ports of entry on our southern border. This increase of 10,000- 15,000 apprehensions per month has significantly strained OHS resources.
Furthermore, according to EOIR information provided to OHS, there are more than 534,000 cases currently pending on immigration court dockets nationwide-a record high. By contrast, according to some reports, there were nearly 168,000 cases pending at the end of fiscal year (FY) 2004 when section 235(b)(l)(A)(i) was last expanded.2 This represents an increase of more than 200% in the number of cases pending completion. The average removal case for an alien who is not detained has been pending for more than two years before an immigration judge. 3 In some immigration courts, aliens who are not detained will not have their cases heard by an immigration judge for as long as five years. This unacceptable delay affords removable aliens with no plausible claim for relief to remain unlawfully in the United States for many years.
To ensure the prompt removal of aliens apprehended at or near the border, the Department will publish in the Federal Register a new Notice Designating Aliens Subject to Expedited Removal Under Section 235(b)(l)(a)(iii) of the Immigration and Nationality Act. I direct the Commissioner of CBP and the Director of ICE to conform the use of expedited removal procedures to the designations made in this notice upon its publication.

H. Implementing the Provisions of Section 235(b)(2)(C) of the INA to Return Aliens to Contiguous Countries
Section 235(b)(2)(C) of the INA authorizes the Department to return aliens arriving on land from a foreign territory contiguous to the United States, to the territory from which they arrived, pending a formal removal proceeding under section 240 of the INA. When aliens so apprehended do not pose a risk of a subsequent illegal entry or attempted illegal entry, returning them to the foreign contiguous territory from which they arrived, pending the outcome of removal proceedings saves the Department's detention and adjudication resources for other priority aliens.
Accordingly, subject to the requirements of section 1232, Title 8, United States Code, related to unaccompanied alien children and to the extent otherwise consistent with the law and U.S. international treaty obligations, CBP and ICE personnel shall, to the extent appropriate and reasonably practicable, return aliens described in section 235(b)(2)(A) of the INA, who are placed in removal proceedings under section 240 of the INA- and who, consistent with the guidance of an ICE Field Office Director, CBP Chief Patrol Agent, or CBP Director of Field Operations, pose no risk of recidivism- to the territory of the foreign contiguous country from which they arrived pending such removal proceedings.
To facilitate the completion of removal proceedings for aliens so returned to the contiguous country, ICE Field Office Directors, ICE Special Agents-in-Charge, CBP Chief Patrol Agent, and CBP Directors of Field Operations shall make available facilities for such aliens to appear via video teleconference. The Director of ICE and the Commissioner of CBP shall consult with the Director of EOIR to establish a functional, interoperable video teleconference system to ensure maximum capability to conduct video teleconference removal hearings for those aliens so returned to the contiguous country.

I. Enhancing Asylum Referrals and Credible Fear Determinations Pursuant to Section 235(b)(l) of the INA

With certain exceptions, any alien who is physically present in the United States or who arrives in the United States (whether or not at a designated port of arrival and including an alien who is brought to the United States after having been interdicted in international or United States waters), irrespective of such alien's status, may apply for asylum. For those aliens who are subject to expedited removal under section 235(b) of the INA, aliens who claim a fear of return must be referred to an asylum officer to determine whether they have established a credible fear of persecution or torture.4 To establish a credible fear of persecution, an alien must demonstrate that there is a "significant possibility" that the alien could establish eligibility for asylum, taking into account the credibility of the statements made by the alien in support of the claim and such other facts as are known to the officer.
The Director of USCIS shall ensure that asylum officers conduct credible fear interviews in a manner that allows the interviewing officer to elicit all relevant information from the alien as is necessary to make a legally sufficient determination. In determining whether the alien has demonstrated a significant possibility that the alien could establish eligibility for asylum, or for withholding or deferral of removal under the Convention Against Torture, the asylum officer shall consider the statements of the alien and determine the credibility of the alien's statements made in support of his or her claim and shall consider other facts known to the officer, as required by statute.
The asylum officer shall make a positive credible fear finding only after the officer has considered all relevant evidence and determined, based on credible evidence, that the alien has a significant possibility of establishing eligibility for asylum, or for withholding or deferral of removal under the Convention Against Torture, based on established legal authority. 7
The Director of USCIS shall also increase the operational capacity of the Fraud Detection and National Security (FDNS) Directorate and continue to strengthen the integration of its operations to support the Field Operations, Refugee, Asylum, and International Operations, and Service Center Operations Directorate, to detect and prevent fraud in the asylum and benefits adjudication processes, and in consultation with the USC IS Office of Policy and Strategy as operationally appropriate.
The Director ofUSCIS, the Commissioner of CBP, and the Director of ICE shall review fraud detection, deterrence, and prevention measures throughout their respective agencies and provide me with a consolidated report within 90 days of the date of this memorandum regarding fraud vulnerabilities in the asylum and benefits adjudication processes, and propose measures to enhance fraud detection, deterrence, and prevention in these processes.

J. Allocation of Resources and Personnel to the Southern Border for Detention of Aliens and Adjudication of Claims
The detention of aliens apprehended at the border is critical to the effective enforcement of the immigration laws. Aliens who are released from custody pending a determination of their removability are highly likely to abscond and fail to attend their removal hearings. Moreover, the screening of credible fear claims by USC IS and adjudication of asylum claims by EOIR at detention facilities located at or near the point of apprehension will facilitate an expedited resolution of those claims and result in lower detention and transportation costs.
Accordingly, the Director of ICE and the Commissioner of CBP should take all necessary action and allocate all available resources to expand their detention capabilities and capacities at or near the border with Mexico to the greatest extent practicable. CBP shall focus these actions on expansion of "short-term detention" (defined as 72 hours or less under 6 U.S.C. § 21 l(m)) capability, and ICE will focus these actions on expansion of all other detention capabilities. CBP and ICE should also explore options for joint temporary structures that meet appropriate standards for detention given the length of stay in those facilities.
In addition, to the greatest extent practicable, the Director of USC IS is directed to increase the number of asylum officers and FDNS officers assigned to detention facilities located at or near the border with Mexico to properly and efficiently adjudicate credible fear and reasonable fear claims and to counter asylum-related fraud.

K. Proper Use of Parole Authority Pursuant to Section 212(d)(S) of the INA
The authority to parole aliens into the United States is set forth in section 212(d)(5) of the INA, which provides that the Secretary may, in his discretion and on a case-by-case basis, temporarily parole into the United States any alien who is an applicant for admission for urgent humanitarian reasons or significant public benefit. Upon careful scrutiny, the statutory language appears to strongly counsel in favor of using the parole authority sparingly and only in individual cases where, after careful consideration of the circumstances, parole is necessary because of demonstrated urgent humanitarian reasons or significant public benefit.
The practice of granting parole to certain aliens in pre-designated categories in order to create immigration programs not established by Congress, has contributed to a border security crisis, undermined the integrity of the immigration laws and the parole process, and created an incentive for additional illegal immigration.
Therefore, the Director of USC IS, the Commissioner of CBP, and the Director of ICE shall ensure that, pending the issuance of final regulations clarifying the appropriate use of the parole power, appropriate written policy guidance and training is provided to employees within those agencies exercising parole authority, including advance parole, so that such employees are familiar with the proper exercise of parole under section 212( d)( 5) of the INA and exercise such parole authority only on a case-by-case basis, consistent with the law and written policy guidance.
Notwithstanding any other provision of this memorandum, pending my further review and evaluation of the impact of operational changes to implement the Executive Order, and additional guidance on the issue by the Director of ICE, the ICE policy directive establishing standards and procedures for the parole of certain arriving aliens found to have a credible fear of persecution or torture shall remain in full force and effect.8 The ICE policy directive shall be implemented in a manner consistent with its plain language. In every case, the burden to establish that his or her release would neither pose a danger to the community, nor a risk of flight remains on the individual alien, and ICE retains ultimate discretion whether it grants parole in a particular case.

L. Proper Processing and Treatment of Unaccompanied Alien Minors Encountered at the Border
In accordance with section 235 of the William Wilberforce Trafficking Victims Protection Reauthorization Act of 2008 (codified in part at 8 U.S.C. § 1232) and section 462 of the Homeland Security Act of 2002 (6 U.S.C. § 279), unaccompanied alien children are provided special protections to ensure that they are properly processed and receive the appropriate care and placement when they are encountered by an immigration officer. An unaccompanied alien child, as defined in section 279(g)(2), Title 6, United States Code, is an alien who has no lawful immigration status in the United States, has not attained 18 years of age; and with respect to whom, (1) there is no parent or legal guardian in the United States, or (2) no parent of legal guardian in the United States is available to provide care and physical custody.
Approximately 155,000 unaccompanied alien children have been apprehended at the southern border in the last three years. Most of these minors are from El Salvador, Honduras, and Guatemala, many of whom travel overland to the southern border with the assistance of a smuggler who is paid several thousand dollars by one or both parents, who reside illegally in the United States.
With limited exceptions, upon apprehension, CBP or ICE must promptly determine if a child meets the definition of an "unaccompanied alien child" and, if so, the child must be transferred to the custody of the Office of Refugee Resettlement within the Department of Health and Human Services (HHS) within 72 hours, absent exceptional circumstances.9 The determination that the child is an "unaccompanied alien child" entitles the child to special protections, including placement in a suitable care facility, access to social services, removal proceedings before an immigration judge under section 240 of the INA, rather than expedited removal proceedings under section 235(b) of the INA, and initial adjudication of any asylum claim by USCIS. 10
Approximately 60% of minors initially determined to be "unaccompanied alien children" are placed in the care of one or more parents illegally residing in the United States. However, by Department policy and practice, such minors maintained their status as "unaccompanied alien children," notwithstanding that they may no longer meet the statutory definition once they have been placed by HHS in the custody of a parent in the United States who can care for the minor. Exploitation of that policy led to abuses by many of the parents and legal guardians of those minors and has contributed to significant administrative delays in adjudications by immigration courts and users.
To ensure identification of abuses and the processing of unaccompanied alien children consistent with the statutory framework and any applicable court order, the Director of USCIS, the Commissioner of CBP, and the Director of ICE are directed to develop uniform written guidance and training for all employees and contractors of those agencies regarding the proper processing of unaccompanied alien children, the timely and fair adjudication of their claims for relief from removal, and, if appropriate, their safe repatriation at the conclusion of removal proceedings. In developing such guidance and training, they shall establish standardized review procedures to confirm that alien children who are initially determined to be "unaccompanied alien child[ren]," as defined in section 279(g)(2), Title 6, United States Code, continue to fall within the statutory definition when being considered for the legal protections afforded to such children as they go through the removal process.

M. Accountability Measures to Protect Alien Children from Exploitation and Prevent Abuses of Our Immigration Laws
Although the Department's personnel must process unaccompanied alien children pursuant to the requirements described above, we have an obligation to ensure that those who conspire to violate our immigration laws do not do so with impunity- particularly in light of the unique vulnerabilities of alien children who are smuggled or trafficked into the United States.
The parents and family members of these children, who are often illegally present in the United States, often pay smugglers several thousand dollars to bring their children into this country. Tragically, many of these children fall victim to robbery, extortion, kidnapping, sexual assault, and other crimes of violence by the smugglers and other criminal elements along the dangerous journey through Mexico to the United States. Regardless of the desires for family reunification, or conditions in other countries, the smuggling or trafficking of alien children is intolerable.
Accordingly, the Director of ICE and the Commissioner of CBP shall ensure the proper enforcement of our immigration laws against those who facilitate the smuggling or trafficking of alien children into the United States. Proper enforcement includes, but is not limited to, placing such individuals who are removable aliens into removal proceedings, or referring such individuals for criminal prosecution, as appropriate.

N. Prioritizing Criminal Prosecutions for Immigration Offenses Committed at the Border
The surge of illegal immigration at the southern border has produced a significant increase in organized criminal activity in the border region. Mexican drug cartels, Central American gangs, and other violent transnational criminal organizations have established sophisticated criminal enterprises on both sides of the border. The large-scale movement of Central Americans, Mexicans, and other foreign nationals into the border area has significantly strained federal agencies and resources dedicated to border security. These criminal organizations have monopolized the human trafficking, human smuggling, and drug trafficking trades in the border region.
It is in the national interest of the United States to prevent criminals and criminal organizations from destabilizing border security through the proliferation of illicit transactions and violence perpetrated by criminal organizations.
To counter this substantial and ongoing threat to the security of the southern borderincluding threats to our maritime border and the approaches- the Directors of the Joint Task Forces-West, -East, and -Investigations, as well as the ICE-led Border Enforcement Security Task Forces (BESTs), are directed to plan and implement enhanced counternetwork operations directed at disrupting transnational criminal organizations, focused on those involved in human smuggling. The Department will support this work through the Office oflntelligence and Analysis, CBP's National Targeting Center, and the DHS Human Smuggling Cell.
In addition, the task forces should include participants from other federal, state, and local agencies, and should target individuals and organizations whose criminal conduct undermines border security or the integrity of the immigration system, including offenses related to alien smuggling or trafficking, drug trafficking, illegal entry and reentry, visa fraud, identity theft, unlawful possession or use of official documents, and acts of violence committed against persons or property at or near the border.
In order to support the efforts of the BES Ts and counter network operations of the Joint Task Forces, the Director oflCE shall increase of the number of special agents and analysts in the Northern Triangle ICE Attache Offices and increase the number of vetted  Transnational Criminal Investigative Unit international partners. This expansion of lCE's international footprint will focus both domestic and international efforts to dismantle transnational criminal organizations that are facilitating and profiting from the smuggling routes to the United States.

O. Public Reporting of Border Apprehensions Data
The Department has an obligation to perform its mission in a transparent and forthright manner. The public is entitled to know, with a reasonable degree of detail, information pertaining to the aliens unlawfully entering at our borders.
Therefore, consistent with law, in an effort to promote transparency and renew confidence in the Department's border security mission, the Commissioner of CBP and the Director oflCE shall develop a standardized method for public reporting of statistical data regarding aliens apprehended at or near the border for violating the immigration law. The reporting method shall include uniform terminology and shall utilize a format that is easily understandable by the public in a medium that can be readily accessed.
At a minimum, in addition to statistical information currently being publicly reported regarding apprehended aliens, the following information must be included: the number of convicted criminals and the nature of their offenses; the prevalence of gang members and prior immigration violators; the custody status of aliens and, if released, the reason for release and location of that release; and the number of aliens ordered removed and those aliens physically removed.

P. No Private Right of Action
This document provides only internal DHS policy guidance, which may be modified, rescinded, or superseded at any time without notice. This guidance is not intended to, does not, and may not be relied upon to create any right or benefit, substantive or procedural, enforceable at law by any party in any administrative, civil, or criminal matter. Likewise, no limitations are placed by this guidance on the otherwise lawful enforcement or litigation prerogatives of DHS.
In implementing this guidance, I direct DHS Components to consult with legal counsel to ensure compliance with all applicable laws, including the Administrative Procedure Act.