Science topic

Systems Theory - Science topic

Principles, models, and laws that apply to complex interrelationships and interdependencies of sets of linked components which form a functioning whole, a system. Any system may be composed of components which are systems in their own right (sub-systems), such as several organs within an individual organism.
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I am researching the process that specific churches have gone through in deciding what they want to do regarding legalized same-gender weddings. Bowen Theory presents that those who resist change will be the more emotional due to lack of differentiation individually. They will be more anxious/scared and will probably express it as anger as they attempt to sabotage any plans to change from the old way - the literal interpretation of the Bible (seven isolated passages) that seems to say that homosexuality is a sin in those days.
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Attached is an excerpt from my dissertation, Comparison of Four Midwest Congregations in Transition of Decision-Making on Same-Gender Marriage Using Bowen Family Systems Theory (Shawnee, KS: Central Theological Seminary, 2020)
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The basic idea behind Systems Theory is, “The whole is greater than the sum of its parts.". This is a narrow idea and in our complex world with climate change, environmental degradation, and global inequalities. The pragmatic and positivist trend in the world was to oriented research towards explanations and causes, i.e. in-between of input and output, causes and effects. For no-system theoreticians, the idea is to observe systems as forms with enough inner complexity to reduce the external complexities by the means of selections that stabilized meaning. In this context, it is the self-observation of the form that has been investigated as a system. Once again why system theory is developed into a theory of self-organizing systems.
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Yes and No. It depends on which kind of the system you are dealing with. Some systems are just too huge to model them sufficiently accurately.
I will give you just one simple example. Human cell. Just one living cell has the number of functional parts approxiamtely equal to the number of living people on the Earth. Are we capable to predict the evolution of the humanity in the span of just a few years? Nope. Nada. Zilch.
It is same with a single cell! Not to speak about bodies!
With other systems, it gets even worse: human body, society, state, humanity, ecosystems, the whole Earth's nature, the Umiverse. Is there any escape from this trap made by our inability to evaluate all processes undergoing in the complex system simultaneously? Yes. There is.
By searching for emergent structures in complex systems, we can describe them at different levels. Seems to be easy, right. But it isn't. We have a Russian doll like structure of hard sciences each encompasing just one part of the complexity of the Universe: quantum fields, particles, atoms, molecules, materials, biomolecules, cells, tissues, bodies, ecosystems, the Earth, the Solar system, galaxies, and the Universe.
Scientific disciplines are here for a good reason. We are unable to go from the first principles and derive behavior of galaxies from them! We take as the baseline whole stars, gravity, and electromagnetism. We cannot go from quantum field theory to prove behavior of the galaxies!
Stars themselves are emergent structures originating in the lower level physics: electromagnetism, atomic interactions, fusion, etc. This physical ladder goes even lower.
Many scientists working in their field of research do not realize that they are working with emergents that exist only due to vast number of interactions of parts operating at the lover level of the physics ladder. Those who understand this can easily cross the borders of disciplines as they are putting ends correctly together.
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The question arises from complex systems theory, in which I faced a contradiction, as earlier I thought the equilibrium state of a system means maximum order. The obstacle in my way is thermodynamics. Please help me to better understand and potentially solve this contradiction.
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Your question is fundamental in the proper understanding of a complex system. It is in detail answers in the paper
A brief explanation follows. The entropy of the constant system where everything achieves the same state is equal to zero following the equation
S = p * ln (p) where p = 1 .
In the other hand, the maximum entropy is achieved by the white noise where each state has the same probability to occur.
S = Sum_i (p_i * ln(p_i)) for p_i = const .
For N bins in the distribution you get p_i = 1/N.
S = N * (1/N * ln(1/N)) for 1/N = const .
It gives S = ln(1/N) .
The maximum entropy for given number N of bins is equal to the logarithm of 1/N.
The operational complex system is having entropy S lower that the maximum one. White noise is useless.
More details, examples, and citations are given in the shared paper. This aspect of complex systems is really fascinating.
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If you build a parameter learning algorithm based on the Lyapunov stability theorem for updating the parameters of an adaptive fuzzy controller, how to determine the cost function and Lyapunov function? Is there a physical connection between them?
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Lyapunov function is a point-wise measure of energy, whereas, cost-functional is an interval-based measure of energy. In this sense, you may connect them by assuming Lyapunov function as an explicit function in time which could get a negative decay-rate assuming V=x^2, and then a closed-form dissipation as; V_dot=-K*V(t) for stabilizing a system, see my pre-print at the URL:
Meanwhile, optimal quadratic cost functional, minimizes energy as a sum of the squared state and control signal during a time-interval as; J=int(x^2+u^2).dt, from zero to T. Please see the paper:
Nonlinear Optimal Control: A Control Lyapunov Function and Receding Horizon Perspective (1999)
The control performance could be different through the two scopes, and the energy consumption could be also different.
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I call a digraph G= (V,E) essentially interconnected if whenever any vertex $a$ is removed from $G$ there is always at least one pair of distinct vertices $v$ and $w$ which can no longer be joined by an oriented path in $G$.
Are there essentially interconnected graphs ?
Example: The cycle: (a,b), (b,c),(c,a)
If I remove $b$ then I cannot connect $a$ to $c$ (although I can connected $c$ to $a$) and analogusly for $a$ and $c$.
Can we characterise such digraphs in general ?
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Hello, thank you for your reply.
The general idea is that all vertices are "essential" in the sense that removing a vertex will effect the semiconnectivity structure of the rest of the digraph. So I would say condition (1) captures this notion the best.
Thank you for the observation that there can be no source vertices.
There also can be no sinks (all indegrees).
An essentially interconnected graph need not be weakly connected (just take the disjoint union of cycles). Such examples are trivially also not strongly connected.
I think I just found an example of a weakly connected essentially interconnected graph which is not strongly connected:
Let the vertices of G be a,b,c,d,e,f and the directed edges be
(a,b),(b,c),(c,a) , (d,e),(e,f),(f,d) , (b,d)
It seems that G does satisfy condition (1) but is is not strongly connected as there is no oriented path from d to b.
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In fact, it is the fundamental defects in the work of “quantitative cognition to infinite things” that have been troubling people for thousands of years. But I am going on a different way from many people.
1, I analysis and study the defects in existing classical infinite theory system disclosed by the suspended "infinite paradox symptom clusters" in analysis and set theory from different perspectives with different conclusion: to abandon the unscientific (mistaken) "potential infinite and actual infinite" concepts in existing classical infinite theory system and discover the new concepts of "abstract infinite and the carriers of abstract infinite", especially to replace the unscientific (mistaken) "actual infinite" concept in existing classical infinite theory by the new concept of “carriers of abstract infinite" and develop a new infinite theory system with “mathematical carriers of abstract infinite and their related quantitative cognizing operation theory system ". From now on, human beings are no longer entangled in "potential infinite -- actual infinite", but can spare no effort to develop "infinite carrier theory", and develop comprehensive and scientific cognition of various contents related to "mathematical carrier of abstract infinite concept".
2, Abstract concept - abstract concept carrier theory, new infinite theory system, carrier theory, infinite mathematical carrier gene, infinite mathematical carrier scale,...The development of basic theory determines the construction of "quantum mathematics" based on the new infinite theory system.
3, I have up loaded 《On the Quantitative Cognitions to “Infinite Things” (IX) ------- "The Infinite Carrier Gene”, "The Infinite Carrier Measure" And "Quantum Mathematics”》2 days ago onto RG introducing " Quantum Mathematics". My work is not fixing here and there for those tiny defects (such as the CH theory above) but carrying out quantitative cognitions to all kinds of infinite mathematical things with "quantum mathematics" basing on new infinite theory system.
According to my studies (have been presented in some of my papers), Harmonic Series is a vivid modern example of Zeno's Paradox. It is really an important case in the researches of infinite related paradoxes syndrome in present set theory and analysis basing on unscientific classical infinite theory system.
All the existing (suspending) infinite related paradoxes in present set theory and analysis are typical logical contradictions.
The revolution in the foundation of infinite theory system determines the construction of "Quantum Mathematics" based on the new contents discovered in new infinite theory system: infinite mathematical carrier, infinite mathematical carrier gene, infinite mathematical carrier measure,... in new infinite carrier theory. So, the "Quantum Mathematics" mentioned in my paper is different from Quantum Logic and Quantum Algebras;
According to my studies (have been presented in some of my papers), “Non-Standard Analysis and Transfinite numbers” is all the infinite related things in unscientific classical infinite theory system based on the trouble making "potential infinite and actual infinite" --------- Non-Standard Analysis is equivalence with Standard Analysis while Transfinite is an odd idea of “more infinite, more more infinite, more more more infinite, more more more more infinite,…”).
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Search RG for Ed Gerck. I'm sure he'd be glad to discuss this topic.
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I am using technology adoption as a dependent variable and need a reliable survey instrument. My literature review includes Socio-Technical Systems Theory, TAM, TAM2, Theory of Planned Behavior, Unified Theory of Acceptance and Use of Technology.
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In addition to the answer above,
I advise that you adequately study the UTAUT2 model and see how it fits into your study. I am not sure of the constructs you are using. However, In addition to the construct relationships proposed in the original UTAUT, hedonic motivation and price value can determine behavioral intention. Habit can influence both behavioral intention and usage behavior. Again, facilitating conditions can affect behavioral intention.
For example, the model can be used to determine the intention of use (for mobile banking), by making these hypothesis:
Performance expectancy positively influences people’s behavioral intention to adopt mobile banking.
Effort expectancy positively influences people’s behavioral intention to adopt mobile banking.
Social influence positively influences people’s behavioral intention to adopt mobile banking.
Facilitating conditions positively influence people’s behavioral intention to adopt mobile banking.
Facilitating conditions influence people’s adoption of mobile banking.
Hedonic motivation positively influences people’s behavioral intention to adopt mobile banking.
Price value positively influences people’s behavioral intention to adopt mobile banking.
Read this article and adopt:
Regards
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Our studies have proved that there have been two fundamental defects in present classical infinite theory system: (1) theoretically, confusion on the concepts of “potential infinite and actual infinite”; (2) operationally, confusion on the contents of “potential infinite and actual infinite”. And, these two very defects decide the unavoidable generation of all kinds of infinite relating paradoxes in present mathematical analysis and set theory--------the 2500 years old un-dispersed cloud of “infinite paradoxes syndrome” hanging over the sky of our science. As it turns out, the concepts of “potential infinite” and “actual infinite”, which are un-scientifically defined and mutually contradictory, must be abandoned, and the new infinite theory system basing on ““abstract things—the carriers of abstract things” as well as the systematic theory of “infinite carriers” must be constructed.
We call present classical infinite theory system basing on "potential infinite and actual infinite" concepts "the first generation of infinite theory system" and the new infinite theory system basing on "abstract things and the carriers of abstract things" concepts "the second generation of infinite theory system".
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Interesting work, shall visit often, very much interested in infinite theory system
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The emergence of the new infinite theory system determines the emergence of the second generation of infinite set theory and the fourth generation of mathematical analysis------- we call present classical infinite set theory basing on present classical infinite theory system “the first generation of infinite set theory (the old infinite set theory)" and the new infinite set theory basing on the new infinite theory system the second generation of infinite set theory"; we call "the first, second and third generations of mathematical analysis (before standard analysis, standard analysis and non-standard analysis) " basing on present classical infinite theory system “the present classical mathematical analysis (the old mathematical analysis) " and the new mathematical analysis basing on the new infinite theory system the fourth generation of mathematical analysis".
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The advantage of the potentially infinite, to achieve the infinite by some limit of the finite, is that there would not be this abrupt break with properties of finite sets.
So finally it seems to me there can be two radically different approaches to infinite sets.
This is consistent with the view of many analysts, who say infinity as a number does not exist, potential infinity is just as large as needed in each step. This is the view of intuitionists also. Somehow this sets a limit to methods of induction.
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We have understood from the studies of infinite related mathematics’ history that present classical infinite theory system is based on the concepts of "potential infinite and actual infinite", which cannot be defined scientifically and contradict each other. This fatal flaw in the basic theory deeply affects the scientific nature of mathematical behavior of mathematical workers in the field related to the concept of "infinite". So, one cannot escape the constraint of the two false concepts of "potential infinite and actual infinite", and one cannot stop the emergence of various infinite related paradoxes. In addition, these paradoxes must exist in the form of "family (infinite paradox syndrome)". In different historical periods, the constantly emerging paradox family members repeatedly reveal the fundamental defects in the classical infinite theory system from different perspectives and call on people to solve these very defects. The fatal fundamental defects in present classical infinite theory system are the source of the second and the third mathematical crisis: more than 2500 years, no one can get rid of a kind of disease in the infinite related fields of mathematics --------- a diseases produced by the confusion of "potential infinite and actual infinite" concepts in set theory diagnosed clearly by Poincare, Frege, and Weyl more than 100 years ago. Studies have proved that this is the common "disease" existing in many infinite related mathematical disciplines with the foundation of present classical infinite theory system: the various "number and non--number mathematical things” -------- “variables of not only potential infinite but also actual infinite (the ‘ghost’ disappearing and reappearing at any time?)" for all the family members of Zeno's Paradox and Berkeley's Paradox in mathematical analysis [1-6]; the mathematical things with the property of "elements belonging and not belonging to a set ---------- T = {x|x📷x} (variable elements of not only potential infinite but also actual infinite: the ‘ghost’ disappearing and reappearing at any time?) " for all the family members of Russell paradox in set theory;…
This is why we are so sure to say that the Third Mathematical Crisis in present scientific theory system is unsolvable and the Third Mathematical Crisis is another manifestation of the Second Mathematical Crisis in set theory. They are "twins".
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Answer see parallel-topic. (Why two at the same time?). Please no answer here.
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How do we best classify ethical issues in AI and robotics? Which disciplines provide possible classification frameworks i.e. philosophy of ethics, psychology of moral reasoning, the law and human rights, the study of etiquette, sociology of norms, control systems theory, neuroscience of impulse regulation, science fiction, etc. etc.
Many possibilities - can you point me in the direction of any possible frameworks?
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As strange as it may seem, automaton has innate rights according to the physical constructal law.
“Ethical issues” will surface during the evolution of automaton replacing humans in the work place. Society may develop a concept of redistributing automaton's generated wealth, by the state, as a guaranteed minimum income. This satisfies most of UN’s Article 25 human rights objectives at a “minimum” standard of living. If one desires a higher standard of living, get a job.
On the subject of evolution, perhaps, one day educational institutions may include the following discovery in their curriculum, enhancing reason and ethics in the evolution of the sciences, technology, economics, governance, philosophy, automaton, etc. embracing a civil society relative to the physical constructal law:
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By reading a paper by F.Baldini "Freud's Line of Reasoning", ( ) I found the application of a black box model to test the analyst construction with reference to the symptom. The application is the following: the analyst does not know anything about the causes of a specific symptom and then he needs to treat the system that provoked the symptom as a black box. The methodology used to solve this situation is simply to apply some inputs to the system that are the so-called "constructions" that could either be true or false. After the construction is communicated to the patient, the symptom could either stay the same or ameliorate/worsen. Assuming that the modifications are indicators of a true construction (in the paper the methodology is explained), then it is possible to retrieve the cause of the symptom and so the box becomes white.
I guess this is possible because the input is the attempt to find the cause, i.e. transforming the blackbox in a white one!
I would like to know if there are similar examples in science.
Please advise.
Many thanks.
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Okay, it is now clear to me... Actually I was missing the fact that if the observer also controls input, the investigation turns into an experiment, and hypotheses about cause and effect can be tested directly.
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For example; can the dynamical systems theory help us find underlying general structures of the systems to make more accurate models?. Perhaps some data reflect these structures that are not evident by analyzing them from a purely statistical point of view. Having in mind that the data usually comes from dynamic systems.
Are there any works that relate to these areas? Or is it just a naive question?
Thanks,
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There is quite some work on the intersection of dynamical systems (ODEs and PDEs) and data science. A bunch of paper are co-authored by Igor Mezic:
dealing with the so-called Koopman operator. There are other researches looking at this, but I mention this one because he is a bit more math oriented than the rest.
Google on google scholar "Koopman operator dynamical systems" and you'll get many papers on the subject.
Hope this helps.
Best regards,
Cristina
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I am preparing to write an article about the development of the basic assumptions or way of thinking toward organisations and people that underpin Strategic Management.
About the development of Strategic Management, I read some articles and books relating to system theory, and complexity theory. Can anybody recommend some book or article that includes systematic descriptions about the development of Strategic Management and the characteristics of each phase. Thank you very much.
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A more general book summarising underlying management concepts and paradigms may be a good starter, too:
Morgen Witzel: A History of Management Thought, 2nd ed. 2016.
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Many autorities of complex systems theory claim that where the chaos theory begins, classical science ends.The theory of the chaos provides a different approach to solving problems, first of all, in natural sciences.It shows that centuries interpretations of physical phenomena(mechanic paradigm) still do not apply to a significant extent. Will the chaos theory overcomes the centuries mechanic paradigm in economics, leadership and management?
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Nonlinear dynamics can open the path to enclosure-overcoming mathematics that allow science to become explicative, thus can help to overcome the traditional, mere descriptive since enclosure-confined rank of science: cf. Number form theory linked to Structure wave theory.
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I have been working on a research project where i am constructing a complex system theory - that has race, gender, class, age and most importantly language as a system components - that lead to the emergence of social identities which in turn impede the peace building efforts taking place around the world. Therefore, I am currently looking for a suitable methodology. I also need a GPS conflict site tracking website for my case selection. This is my first time working for such a complicated framework as an undergrat and would really appreciate if you could help! 
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I would recommend you the concept of the complex network developed by A-L. Barabasi. It is a very useful approach to the description of networked system expressing complexity.
On top of it, it might be interesting to study clustering algorithms known from machine learning.
Both concepts can help you a lot to define and quantify the subject if your study.
There is one related subject called agent-based modeling. You might find it interesting too.
PS Sone references can be found in my review paper on complex systems applications in medicine. The general ideas covered there can help you to penetrate into the complex system quickly.
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The fatal defects in the foundations of present science system inevitably lead to the existence of “self-refutation mechanism”. Our 2500 years unsuccessful “infinite relating paradoxes” fighting history (the most typical example is Zeno's “Achilles--Tortoise Paradox”) has proved clearly that in present science theory system, it is impossible to solve those self-refutation mechanism relating paradox family members produced by the fundamental defect of theory system itself (unsolvable). The underlying origin of self-refutation mechanism should be studied and the theory of “abstract concept and the carriers of abstract concept” should be studied and developed. This is the only way to eradicate thoroughly those paradox families produced by “self-refutation mechanism” in different fields of human science (including philosophy and mathematics).
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I am afraid that science, as we know it today, will always lead to paradoxes and unprovable statements. It will always hit its impenetrable logical bottom.
We must remind a whole range of discoveries undermining the very foundations of perfect and consistent science.
- Bertrand Russell's paradoxes
- Kurt Gödels Incompleteness theorem
- Alan Turing's Halting problem (Russel's paradox used in the proof)
Explanation of Russell's paradox:
'The barber is the "one who shaves all those, and those only, who do not shave themselves." The question is, does the barber shave himself?'
Do not fry your brain while trying to solve this problem. To write down a table of logical outcomes is helpful.
It is a paradox that explains well all similar paradoxes. Untill science will be used on logic as we know it. We will always run into such paradoxes.
Those observations undermined attempts of mathematicians in the early 20th century led by David Hilbert to develop a unified and consistent mathematics going from the first principles. Instead we know that there will be patched of different disciplines that will cover just a part of mathematics and never one consistent theory of all mathematics.
This is my personal understanding: We will eventually find better explanations of quantum mechanics and that might lead to new mathematics that will be more suitable to describe the world from bottom-up.
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The unavoidable fatal defect of “’potential infinite--actual infinite’ confusion” in present classical infinite idea inevitably leads to the unceasingly production of “paradox events” (different in forms but same in nature) from many infinite relating fields in present science theory system and, the self-contradictory (Self-refutation Mechanism) “self and non-self” contents in present set theory (such as T={x|x📷x}) and mathematical analysis (such as the number-of-non-number variable) is a typical example. It is true that people have been trying very hard to solve those infinite relating paradoxes, but the mistaken working idea brought very little effect-------since antiquity, people have been unaware of that these suspended “infinite paradox events” are in fact an “infinite paradox syndrome” disclosing from different angles exactly the same fundamental defects in present classical infinite theory system, have not been studying seriously the consanguineous ties among the paradoxes in the syndrome, have not been studying seriously the consanguineous relations among these paradoxes and the foundations of their related theory systems (such as number system) , have not been studying seriously and deeply the fundamental defects in present classical infinite theory system disclosed jointly by different infinite paradox families; but merely studied, made up and developed very hard all kinds of formal languages, formal operations and formal logics specially for solving surface problems. So, not only these “infinite paradox families” have never been solved but developing and expanding unceasingly.
v
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Thank you dear Mr. Dennis Hamilton!
According to my studies, Zeno's great creation of “Achilles--Tortoise paradox” is not only a simple mistake but is a huge paradox family and its typical modern family member is the newly discovered Harmonic Series Paradox.
Let’s see following divergent proof of Harmonic Series which can still be found in many current higher mathematical books written in all kinds of languages:
1+1/2 +1/3+1/4+...+1/n +... (1)
=1+1/2 +(1/3+1/4 )+(1/5+1/6+1/7+1/8)+... (2) >1+ 1/2 +( 1/4+1/4 )+(1/8+1/8+1/8+1/8)+... (3) =1+ 1/2 + 1/2 + 1/2 + 1/2 + ...------>infinity (4)
Because of not knowing what infinitesimals are, the unavoidable practical problem has been troubling us ever since is how many items (including infinitesimals of cause) in infinite decreasing Harmonic Series can be added up by “brackets-placing rule" to produce infinite numbers each bigger than 1/2?
This kind of “infinite-infinitesimals paradox” tells us:
1, in Harmonic Series, we can produce infinite numbers each bigger than 1/2 or 1 or 100 or 100000 or 10000000000 or… from infinite infinitesimals in Harmonic Series by “brackets-placing rule" to change an infinitely decreasing Harmonic Series with the property of Un--->0 into any infinite constant series with the property of Un--->constant or any infinitely increasing series with the property of Un--->infinity;
2, the “brackets-placing rule" to get 1/2 or 1 or 100 or 100000 or 10000000000 or… from infinite items in Harmonic Series corresponds to different runners with different speed in Zeno’s Paradox while the items in Harmonic Series corresponds to those steps of the tortoise in Zeno’s Paradox. So, not matter what kind of runner (even a runner with the speed of modern jet plane) held the race with the tortoise he will never catch up with it.
By the way, Robinson's non-standard analysis can do nothing to solve any of those suspended “infinite-infinitesimals paradoxes” either.
Sincerely yours,
Geng
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I am interested to know, why is control set in control systems theory, usually assumed convex, more specifically, a convex cone, a convex hull or a convex set? Please let me know if you've gotten the answer.
Thank you.
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This because if the control set is convex, it is possible to use convex optimization techniques in order to get the global minimum or maximum. Engineering problems that can be casted in this framework are very often solvable with efficient numerical solutions. An example is the least-squares solution in systems identification. If the linear system is convex, then the coefficient matrix is positive semidefinite and the global minima (only a point in the case of a strictly positive definite matrix) can be found in a reliable way, using the pseudoinverse. Convexity is important also in robust control techiques and H2 optimal control theory.
For example, if the control set isn't convex in the robust identification and control framework, could be not possible to get the controller that minimizes the desired cost function (for example the Hinf norm for the robust stability) but another one (corresponding to a local minimum) would result from the optimization problem. That obviously would be a problem in controller synthesis.
In conclusion, it's important to know if the control set has this nice property called convexity, because this naturally lead to efficient and reliable numerical solution, that can be solved easily. If that isn't the case, other techniques can be applied but in general getting the global minimum isn't easy neither fast
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All,
I am considering looking into the relationship of SME Family Firm performance,internationalization, and sustainability through the prism of SEW and Bowen's Family Systems Theory.
I have seen a lot of literature on SEW. Has someone recently considered the relationship between SEW and Bowen's Family Systems Theory and the impact upon performance,internationalization, and sustainability?
Thanks.
Gerald
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As you have noted, the notion of socio-economic wealth underpins much of the family business literature. It is often articulated as the relative 'familiness' of the business. This however points to an important point, the extent and use of SEW varies within family businesses. A dichotomy or spectrum of the 'family in business' contrasts the 'family for business' captures the different engagements with SEW.
I am not persuaded that 'performance' is that important or useful. The concept of SEW deals with a quite different sort of performance; the relationships within the family. So key issues, if you want to retain a conceptually coherent framework, might be aspects such as satisfaction, enjoyment whilst working in the family firm. I am proposing psychic rewards and internal rather than extrinsic measures of say financial performance are more relevant and logical for this framework.
I am not familiar with Bowen's theory, so cannot comment on that. However, it is worth keeping in mind that family is the basic unit of social organisation. Moreover, it used to be the basic unit of economic organisation.
Finally, I think Leonadis' comment is wrong. In the family business and entrepreneurship literature emotions are an important part of what we study. Probably he has been looking in the wrong literature.
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We all know for a control system, the quality of information (e.g. state info, context info) could have significant impacts on control performance like stability and convergence rate, etc. To theoretically explore such impacts, it is important to adopt suitable system model and corresponding theory. for example, multi-agent system and theory to model coordination control problems and analyze the impact of information flow. In context of cloud computing and IoT more information could be available for a typical control system like traffic control, I just wonder what popular theory framework can apply to such applications? Is there any related surveys to read? thanks a lot.
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I believe that good starting point is
@ARTICLE{Sar:85,
author = {G.N. Saridis},
title = {An integrated theory of
intelligent machines by expressing the control performance as entropy},
journal = {Control Th.\ \& Advanced Technology},
year = {1985},
pages = {125-138},
number = {2},
}
and I hope that this paper is cited by its successors ... MK
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Does anyone know any criticism of systems theory and approaches, and point me to supporting references? I have a draft paper on an assessment of road safety strategies, based on systems criteria. But one of the reviewers raised an interesting question; “The conclusions, while good, could be expanded by describing the limitations and complexities of systems work.”
Could you let me know if you can suggest any literature that could inform this question.
Thanks for any help.
Regards, Brett
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wow, interesting question. My first suggestion would be to look at Hari Tsoukas' critique of critical systems thinking. He refers to a paper of Mike Jackson in systems practice (now called systemic practice and action research). As far as I remember people criticise a so called lack of rigour leading to fall into theoretical and methodological incommensurability. Perhaps because of this, John Mingers has developed a view of systems thinking based on critical realism. Gerald Midgley has criticised the work of Jackson by arguing that methodological pluralism in frameworks like Total Systems Intervention or TSI needs to be more dynamic and flexible, following the complexities of a situation. He also raised the issue of how ethical issues related to seeking improvements are to be dealt with, suggesting that improvement needs to be locally rather than normatively defined by stakeholders. Complexity theorists would follow this apparent lack of flexibility to argue that it is complexity, not systems thinking, which could then provide for such flexibility. However they could also be criticised by establishing some 'normative' principles as to how complex social systems or situations are to 'behave'. I guess this would be my answer. Good luck with your paper!
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What are the metrics for assessing the tipping points for a hydrological systems? I know they look appearances and disappearances of species for ecological systems but just wondering if there are any (certain) thresholds for hydrological systems!
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One approach for examining whether hydrologic systems have reached a threshold or tipping point is to apply the non-parametric Pettit test to any time series of data you are examining such as discharge, sediment loads, nutrient concentrations, etc. This will help identify whether there has been a shift in the mean and may indicate that the system is rapidly shifting towards a new state. Examining the geographic coherence of these tipping points can point towards regional drivers such as climate change, land use change, and other factors. These references are helpful if you want to perform a statistical exploration of tipping points:
Pettitt, A. (1979). A Non-Parametric Approach to the Change-Point Problem Published by : Wiley for the Royal Statistical Society Stable URL : http://www.jstor.org/stable/2346729 A Non-parametric Approach to the Change-point Problem, Applied Statistics, 28(2), 126–135.
Sagarika, S., Kalra, A., & Ahmad, S. (2014). Evaluating the effect of persistence on long-term trends and analyzing step changes in streamflows of the continental United States. Journal of Hydrology, 517, 36–53. http://doi.org/10.1016/j.jhydrol.2014.05.002.
McCabe, G. J., & Wolock, D. M. (2002). A step increase in streamflow in the conterminous United States. Geophysical Research Letters, 29(24), 38-1-38–4. http://doi.org/10.1029/2002GL015999.
Demaria, E. M. C., Palmer, R. N., & Roundy, J. K. (2016). Regional climate change projections of streamflow characteristics in the Northeast and Midwest U.S. Journal of Hydrology: Regional Studies, 5, 309–323. http://doi.org/10.1016/j.ejrh.2015.11.007.
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I have studied systems theory in the more complex mathematical version and have a handout in Dutch describing an organisation as a system with the primary process and two kinds of feedback loops. But that contsins no reference to official literature and none in English. Who can point out a useful source?
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Thanx all, my question has been answered! This is no longer a question. LH
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One of the critiques for systems theory of aeston is its limitations in non western systems? Do you agree with this ? Is it applicable in authoriterians context or it needs supportive theories?
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From the perspective of system theory a system is always contextual and locally embedded. I am gratitude for the dialogue in this forum. System theory helps us to understand sytemic-dynamic processes of selforganized systems. Human beings are selforganized systems. System theory is based on natural sciences and applied in social sciences. System theory is a form of epistemology. What do you want to explore? On micro or macro level? The process of synlogisation between the subsystems? or.... ?
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My theoretical framework for my dissertation is based on System Theory.
However, since I will be looking at Information System adoption, I want to use the Technology-Organisation-Environment (TOE) theory as a framework to develop my conceptual framework that will thus include the concepts that will be measured with the appropriate scales (e.g. under Organisation, top management support will be measured with an appropriate scale).
So, I will be saying something (broadly) like "adoption can only happen if there is a holistic view of the aspects (T-O-E) that influence this adoption)".
Can this work?
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Dear Colleagues, Thanks for the questions. Attached please find two figures. Figure 1 identifies the relationships assumed to exist between theories, and Figure 2 presents the workflow according to which we complete axiomatic theory fusion. Best regards, I.H.
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How do you know that from the almost infinite action (toolbox), which action you need to choose (which is A , B etc..) to get the next step within the progress toward the target. (Starting point (like sitting in the armchair) -> A -> B -> C -> Cooked a Pizza or Went out of the room through the door )
What algorith/method the most effective when the task is NEW, so you need planning, don't just solve this with previous experience.
And this method should be universally applicable because the animals can solve problems with a very high diversity interval.
I hope you get is what the question is.
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Hi Axel,
the answer might easily fill some books, but in short:
1. You have to know the contents of your toolbox. On the lowest level, it might contain less than 50 tools (like in robotics programming: speed, accel, move, moves, appro, appros, depart, departs, break, wait, delay etc.) On the physical level, you get to know your toolbox as a child; on the cognitive level, during your education (which is a livelong process if you don't lead a boring life).
2. If you have done a similar task in the past: If the result was satisfactory then do it in the same way. If not then introduce some promising change.
3. If the task is new to you then search your memory for analogous tasks you have done successfully. (Cooking a soup might not be very different from cooking a pizza.)
4. If the task is completely new: Use your planning ability, i. e. simulate (in your mind) yourself and your environment based on your general experience. If you hit a solution then try to implement the solution in reality.
5. If the task is complex then apply "divide and conquer": Generate a hierarchy with the task as root and subtasks on lower levels. Stop when all subtasks forming leaves look feasible to you. It's the same as writing a program. If you don't know how to solve certain subtasks then you have to gain knowledge in this domain first before continuing the planning (or programming).
6. If the task is not only new (to you or anyone else) and solving the problem involves obviously some creative processes then your picture with the virtually infinite toolbox is correct: The solving process might include a lot of dead ends, it might take weeks, years, or decades, and you might not succeed at all.
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I am working on a research and recently after a review a colleague asked me to consider combining dynamical complex systems theory and grounded theory. the study is on the relationship between social protection and sustainable peace.
Thanks
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Fine question. Yes, GT meets DS on case study. Both depart from hypothetico-deductive approach:
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Re: cognitive-developmental psychology: Is it a bad sign if one has only done ONE thing in her/his entire lifetime?
This is basically, in part, a confession. If you knew how true the "one thing" was in my life, you would likely consider me lazy and privileged. I can accept both labels and can clearly see it that way (at least from the standpoint of some very good people). Moreover, I have had the ability to have anything and everything I thought I needed -- essentially at all times.
But, perhaps as is the only interpretation imaginable, you suspect I am making such admissions just to further the exposure of my perspective and approach. That is completely true. And, I do contend that (with having all resources), I lived virtually all the years of my life looking for a complete and the best thoroughly empirical perspective. Even in my decades of college teaching (more like 1.5 decades), my courses and presentations had coherence most certainly as a function of my views. THUS, indeed, in fact: I have never done anything else in my life other than that needed to produce the papers, book, essays, etc. that I present here on RG (or make readily available through RG). To have a picture of my life, one should imagine about 30 years of it operating much as a hermit (for all that can be good for -- and I do believe it can be good for something).
I started with a core and moved carefully in adopting any aspect of my perspective (basically starting from the position of just what is possibly at-the-very-least needed, and maintaining extreme parsimony). And, again, I am a most thorough-going empiricist, believing that EVERYTHING has a core foundation of some behavior which, at least at some key point, is both overt (though maybe quite subtle) AND directly observable (and now practically so, via eye-tracking). My entire perspective and approach relies pivotally and mainly on such foundations and otherwise only on the best findings and extremely widely-affirmed processes IN ALL OF PSYCHOLOGY (things showing the very best inter-observer agreement). All this is not any kind of abstract or wide set of things. The other prime objective ("directive") has been to NOT [just] link but PUT behavior (behavior patterns) clearly IN a biological framework -- showing as much as possible the "biology of behavior"; this had the rewarding result of eliminating critical and serious dualisms, esp. nature/nurture.
Assumptions or presumptions (pseudo-asssumptions) in Psychology had to be exposed as both unproven and not well-founded. A half dozen central "assumptions" have been replaced in my system BY BASICALLY THE OPPOSITES -- these assumptions being fully consistent with biological principles and more likely true. I also show in my work how to use all the terms of classical ethology, this also allowing or furthering the "biology of behavior".
In short, though this should be to some degree a shameful confession (and many would have to believe that is part of it), my work is MINE (compromising nothing; adhering to principles) -- and it is good **. Please take some time to explore it, starting at: https://www.researchgate.net/profile/Brad_Jesness2 Thank you.
** FOOTNOTE: The perspective and approach is explicit and clear enough for artificial intelligence also -- a good test. BUT: For the great advancements needed in Psychology and major practical utility in AI, we need DISCOVERIES, the nature of which are indicated in testable (verifiable) hypotheses, clear in my writings -- MUCH awaits those discoveries. The same discoveries are involved for either field.
P.S. For 20 years of my hermitage I did have the strong "hobby" (avocation) of JavaScript programming; I never made any money from this. I tell you this just to make sure the portrayal is accurate -- and to in no way mislead. (See http://mynichecomputing.org , if you are curious.)
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Dear Vladimir A. Kulchitsky
I must thank you for your kind words and encouragement.
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Good day,
I am doing my PhD in operation research in logistics. I want to create an urban logistics simulation, during which I would show how autonomous vehicles can adapt to disruptions and resilience would emerge. The theoretical approach is based on complex-adaptive systems theory.
As I understand, the routing should be made by using “reinforcement learning for combinatorial optimization”, however, I do not have experience related to RL application for route scheduling. Could anyone recommend courses or literature related to this topic?
If anyone has developed such a model, maybe could provide some insights in to the data architecture? As I understand this would be similar to supervised learning, however sequence of categories must also be taken into consideration. Should the implementation be based on graphs? Or should I have features categorizing a trip with evaluation of the cost function?
In my case, I am having a e-commerce industry with product delivery to end-consumer, during the day I am generating traffic jams, which would block the routs. The algorithm should learn from the environment and select better routes automatically by considering the goal function.
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Dear Valentas,
It should be pointed out that the data structure technique belongs to the large domain of mathematical optimization, and combinatorial optimization is an element of this set. In addition, heuristics and metaheuristic techniques are part of this domain and are an extension for the resolution of multiobjective optimization. It is clear that these techniques can be used in a complementary manner or in hybridization.
For more information about this sbject, i suggest you to see links and attached file in topic.
How Autonomous Vehicles are Driving a Shift in Supply Chains
Solving Combinatorial Optimization Tasks by Reinforcement Learning ...
Logistics 2050 A Scenario Study - DHL
big data in logistics - DHL
Best regards
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Hello,
This project aims are to address the theory of dynamic systems from the pedagogy point of view or these intend to study the possibilities for the reformulations, for the re-conceptualizations ... of pedagogy from the perspective of the theory of complex systems?
In any cases, I thing that this project is very interesting and useful too for the knowledge society.
If I misunderstood, please give me some details about the objectives of your proposed project.
Sincerely,
Bogdan Nicolescu
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Thank you, Bogdan!
I am very happy when I have found even one person from the world who understand symstems theory and systems thinking and even the fact that for understanding pedagogy and education - so many intensions and extensions at the same time - sustemic views are needed. Otherwise only a small details ase seen - and it means narrow way of thinking.
sincerely yours,
professor Ulla Härkönen
Finland
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I'm interested to know about good Sci-Fi books that deal with e.g., species extinction and/or recovery, habitat destruction and/or restoration, climate change, ocean acidification, land-use change, and so on. If you read interesting Sci-Fi books on this type of topics, please let me know. I'd be very grateful :)
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I would also recommend the Atwood books and the Dune cycle (F. Herbert - 6 books). The Dune books are known for their exploration of religion and politics, but ecology is very important to the global story, dealing with resource dependance, ecosystem balance, ecological engineering (...) at a planetary scale. In particular, the first book includes a « planetologist » and an appendix explaining the ecology of Dune/Arrakis : '... the highest function of ecology is the understanding of consequences’.
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Have you considered any family - relationship factors as a source of chronic stress beyond the "usual suspects"? For example being the preferred child or parental expectations.
Bowen Family Systems Theory can give you ideas of family relationship patterns that put pressure on individuals and which are not often overlooked.
Mariana
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and parental gender role conservatism may be the important issue
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I work on my master thesis with the working title "system competence for people in leadership". So I assume that system theories, like synergetics, chaos theory as well as system thinking and system practice could create a solid theoretical framework and some practical implications when it comes to empower, coach or educate leaders.
So do you know of (empirical) research about "agility", "vuca", "system thinking", "system practice" or "system competence" in the context of leadership?
Any ideas are welcomed! Thanks in advance .... Marcus
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Hi Marcus, The sources below may be of interest
Lichtenstein, B. B., & Plowman, D. A. (2009). The leadership of emergence: A complex systems leadership theory of emergence at successive organizational levels. The Leadership Quarterly, 20(4), 617-630.
Marchildon, G. P., & Fletcher, A. J. (2016). Systems thinking and the leadership conundrum in health care. Evidence & Policy: A Journal of Research, Debate and Practice, 12(4), 559-573.
Hazy, J. K. (2008). Toward a theory of leadership in complex systems: Computational modeling explorations. Nonlinear Dynamics, Psychology, and Life Sciences, 12(3), 281.
Schneider, M., & Somers, M. (2006). Organizations as complex adaptive systems: Implications of complexity theory for leadership research. The Leadership Quarterly, 17(4), 351-365.
Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The leadership quarterly, 18(4), 298-318.
Regards,
Hamish
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Hello All,
I am preparing to write a paper on the application of contemporary management theories with focus on social/systems theory. I have not been able to access enough articles on the subject. Can someone please direct me links where I can source required articles from?
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Thank you, I am grateful.
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Processes, information feedback, policy and time delays are the important elements of System Dynamics modeling. Boundary setting is equally important component in SD modeling given the fact that endogeneous and exogeneous variables are determined based on boundary only. 
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Probably too late for this answer... but this manuscript was quite useful when I was trying to define the boundaries of a system dynamics model I was working on. 
Cheers. 
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Consider the discrete system
x' = A(t)x + B(t)u
y = C(t)x' + D(t)u
The matrices A, B, C, D contain time-varying parameters (calculated by a second model) which are given in the initial state, but will develop randomly.
How can I check the observability of the system above?
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Thank you all for your contributions!
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How can I construct a multi-attribute utility function for attributes that I cannot prove utility independence for? 
Thanks. 
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Thanks, David. Yes, that seems like a good option. 
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I have a preliminary observation: are you referring to miroscopic scale (i.e. at the scale of the division of a single tumor cells) or at mesoor macro scales (i.e. at the scale of a population of tumor cells) ?
If you are referring at the tumor scale, my answer is: ** no **, for a series of reasons of various nature. First, seldom a tumor growth model is adequately described by a discete dynamical system (one exception is my paper: d'Onofrio and Tomlinson, J Theor Biol ,2007); Second, the chaotic bifurcation diagram of the logistic map is often the result of the discretization of a continuous model by adopting an excessively large time-step; Third (and main) reason: the tumor growth is (unfortunately) progressive and (apart some cases of highly immunogenic tumors) very seldom characterized by the wild oscillations that are a landmark of the vast majority of chaotic phenomena. 
There are some chaotic models of tumor growth, where, however, chaos stems from other biological processes (e.g. in some cases: the interplay with the immune system) mirrored by other mathematical propserties.
Kind regards,
Alberto d'Onofrio
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I am interested in how these two theories interrelate and complete one another, both as an explanation of two-couple relationship dynamics, and also in workplace dynamics/leadership issues.
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Attachment or differentiation-of-self: Competing or complementary theoretical orientations in contemporary relational therapies. By Gingrich, Fred
Marriage & Family: A Christian Journal, Vol 7(1), 2004, 33-49.
Two popular theoretical concepts, attachment (Bowlby, 1969) and differentiation-of-self (Bowen, 1978), appear to be competitors in the arena of marital and family therapy. Attachment theory is the foundation of Emotionally Focused Couples Therapy (Johnson, 2004b), and differentiation is the core concept of Family Systems Therapy, represented by Schnarch (1991) and others. A review of these concepts and therapeutic models, along with reflections on how they are supported in Scripture, opens up the possibility that they may not be mutually exclusive. Both can be valuable resources for Christian counseling ministry to couples and families. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
What Predicts Marital Satisfaction? The Role of Attachment and Differentiation doi: http://dx.doi.org/10.1037/e559492014-001
By Moini, Sara; Regas, Susan
2014 [American Psychological Association (APA)].
Attachment and differentiation are effective frameworks for helping couples achieve marital satisfaction. The application of Bowlby's (1969) attachment theory to adult relationships is the foundation of the empirically supported treatment, Emotionally-Focused Therapy (EFT; Greenberg & Johnson, 1988), which is widely used with couples. Johnson (2007) discusses secure attachment as the foundation for couples having satisfying marriages. She explains that when partners can listen to each other's emotions, offer and accept comfort from each other and turn to each other to feel safe, a secure bond is developed. Differentiation of self has been theorized as fundamental to long-term intimacy and mutuality in marriages (Bowen, 1978). Bowen (1978) explains that when partners are highly differentiated, spouses are able to maintain clear autonomy and at the same time they are able to maintain an emotional closeness that is both comfortable and non-threatening to them. This allows them to enjoy a full range of intimacy. Although there is debate over whether attachment or differentiation is the most effective framework for helping couples achieve marital satisfaction, there is also evidence suggesting that attachment and differentiation may be related to each other. Secure attachment involves the ability to access support from attachment figures, allowing the development of self-reliant behavior. Differentiation involves the ability to achieve an autonomous self in emotional connection to others. Therefore, although attachment security and differentiation tap into specific elements of the relational experience, they share two underlying components: the need for intimacy and autonomy (Skowron & Dendy, 2004). Research has primarily focused separately on attachment and differentiation as predictors of marital satisfaction. Fewer studies have also examined the relationship between attachment and differentiation. The purpose of this study is to examine attachment and differentiation as predictors of marital satisfaction and to investigate the relationship between the two variables. One hundred and fifty two married men and women (56% female; M years married = 10; M age = 40) completed the following measures online: The Experiences in Close Relationships Revised (ECR-R; Fraley, Waller, & Brennan, 2000), Crucible Differentiation Scale (CDS; Schnarch & Regas, 2012), and the Marital Adjustment Test (MAT; Locke & Wallace, 1959). Participants were eligible to participate if they were a heterosexual, married man or woman, living in the United States and at least 22 years of age. A hierarchical regression was conducted and as hypothesized, attachment and differentiation explained significant variance in marital satisfaction. After correlation coefficients were computed between attachment and differentiation there was a significant negative correlation between attachment avoidance and differentiation r(148) = -.450, p < .01 (one-tail) and a significant negative correlation between attachment anxiety and differentiation r(148) = -.555, p < .01 (one-tail). That is, the lower one's level of attachment anxiety and avoidance, the higher one's level of differentiation. Results suggest that attachment and differentiation are both effective frameworks for helping couples achieve marital satisfaction and that secure attachment and differentiation share underlying components. (PsycEXTRA Database Record (c) 2015 APA, all rights reserved)
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Could anybody point out trusty and high rank journal discuss that Multiple Model Control with hard switching is applicable to system with fast dynamics ?
Thanks.
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When you combine hard switching and speed, you are unlikely to obtain reliable performance. This is because real systems have noise which can cause plenty of mistakes in switching. However, if you have high confidence/integrity detectors, and transitioned between hybrid modes smoothly, you could guarantee good performance.  Perhaps you could even analyze the overall system in an LMI framework, or SOSTOOLS framework (for nonlinear systems) as LPV controllers, gain scheduling controllers, etc are analyzed.
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I am working on qualitative, collective case study research with Total Quality Management as the conceptual framework. I'm looking for other frameworks that support or contrast against TQM. For example, Systems Theory is documented as a supporting theory of TQM. Peer-reviewed articles from 2012 or newer would be great.
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Also, Management by Objectives is contrasting as it focuses on the individual and short-term goals while TQM focuses on long-term gain.
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Dear all
Given a dynamical system x\dot=f(x,u) defined on a state space X with initial condition xand a control law u.
my question is that : is it possible that the invariant set in Lasalle's invariance principle is nowhere dense? under which conditions it could be (nowhere dese)? i would like also to know if there is any related works about this topic
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I found the following paper quite interesting and may help:
"Dense sets,nowhere dense sets and an ideal in generalized closure spaces". Chandan Chattopadhyay.
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It is claimed that human’s decision making is not logical necessarily [1].
Here is an example from [2].
Task 1: choose one of the following options:
a)     80% chance to win 4000$.
b)     3000$ for sure.
Task 2: choose one of the following options:
c) 20% chance to win 4000$.
d) 25% chance to win 3000$
In the first task, most people choose option (b) and in the second task most people prefer option (c). However the only difference between two tasks, is the multiplication of probabilities to 0.25, which shouldn’t change the decision.
Kahneman and Tvresky proposed two statistical curves for weighting “probability” and “value” in human mind (figure 1) [2]. However we want to model the dynamic of this behavior. A very rough idea is to consider a set of differential/difference equations and collecting some data for determining the structure and parameters.
Any suggestion and comment?
Thank you in advance,
Sajad
References:
[1] Ariely, Dan. "Predictably Irrational: The Hidden Forces That Shape Our Decisions.”
[2] Kahneman, Daniel, and Amos Tversky. "Prospect theory: An analysis of decision under risk." Econometrica: Journal of the Econometric Society (1979): 263-291.
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Sorry, but I don't see the two cases as being exactly the same and, therefore, the decision is not necessarily without logic.
While Task 2 is clearly based upon statistics, Task 1 is not exactly so.
If we talk about statistics, Task 1 should say that, based upon, say, 2000 cases, 100% of the 1000 who chose 3000$ got it, while only 80% of the 1000 who chose 4000$ got it. This way, the better chance still leaves room for some risk.
Instead, when you say "for sure," I think we all understand that, if we choose 3000$, we just get without any risk, so (unless we are addicted gamblers), we decide to just get it.
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I have been exploring Mario Bunge's Ontology and System Theory for a couple of years now. I started with Transport Research and now I am considering expanding to urban systems. It's a remarkably fecund framework to work with. 
I would really like to find other researchers to exchange ideas on Mario Bunge's Ontology and its applications. 
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Dear Rolf,
Thank you for your answer. I have been studying and applying Bunge's ideas to Transportation and Urban studies. I have exchanged some emails with Bunge back in 2009-2010 about his ontology. Even before, I studied volumes 3 and 4 of his Treatise. Now, I am trying to articulate different research fields in Architecture and Urbanism Graduate Program.
I am quite convinced of the applicability of his perspective to a consistent interdisciplinar approach. 
That would be wonderful to exchange some experiences and thoughts, if you are available.
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  • properties of phase transition of 2D ferroelectric system
  • theory of ferroelectric system
  • theory of phase transition of 2D Ferroelectric
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Phase transitions of many 2D systems are similar due to the universality behavior. You may start with a ferromagnetic system such as the Ising model. 
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I need to identify which resources (goods, materials, instruments, persons) can become a physical constraint or bottleneck in the logistic system of an enterprise / Necesito identificar qué recursos (activos, materiales, instrumentos, personas) pueden convertirse en una restricción física o cuello de botella en el sistema logístico de una empresa.
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Dear Rupert,
I appreciate to a lot your suggestion, have a nice day
Regards
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Are there educators and or researchers who know of situations where systems theory and or ecological models are being used in postsecondary education classrooms?
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I want to know if general systems theory can be applied using the following?
Input: organizational/individual skill, experience, training
Object: IT network
Output: security risk rating
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Dear Florence,
My view is that the answer is YES, but you should careful in performing your analysis. IT network is a system. It has a certain design and structure according to the initial requirements and the intelligence of the engineers who conceived the system. Now, you should make the difference between the concepts of "security" and "risk". Risks are associated with the uncertainties of the external environment while security is associated with the certainty of the internal environment. In other words, engineers conceive security systems for any IT network in order to withstand to potential risks coming from the external environment, or due to the poor functioning of some components of the IT network. The administrator's knowledge is related to the management of the given system, meaning that the administrator should be knowledgeable about the potential risks and the capacity of the security system built in to withstand them. Of course, an experienced administrator should be able to improve the capacity of the system to react to the possible risks. The administrator's knowledge should also be related to the complexity of the IT network.
The topic is very interesting but you should be careful in relating the variables you want to evaluate. I would suggest to investigate first the different classes of possible risks and the existing security systems to see how engineers already made correlations between them.
Wishing you good luck!
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how is system theory a synthesis to other management theories
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Management is known to be the art, or science, of achieving goals and maintaining continuous improvement through people, by making sure an optimal exploitation of resources and people do what they are supposed to do. Management is also the process of designing and maintaining an environment in which people, working with resources and together in groups, efficiently accomplish selected aims. The environment (including all hardware, software, cyberware, and brainware resources) is a system that is purposefully created and dynamically maintained under varying conditions and contexts. The fundamental management functions,  planning, organizing, staffing, leading, and controlling, can be seen in the context of the organization of the embedding system. Contemporary management theories tend to explain the rapidly changing nature of today’s organizational environments. Contemporary systems sciences intend to explain systems on a cybernetical basis, considering the holism of systems and how they accomplish overall goals. Systems are interpreted as wholeness having (i) inputs (euipment, materials, money, technologies, people), (ii) processes (e.g. design, planning, organizing, motivating, and controlling), (iii) outputs (products, services, wastes ) and (iv) outcomes (e.g. productivity, revenue, well-being, sustainability). On the one hand, management theories have become more important in the perspective of systems as the complicatedness and complexity of real life systems increased. On the other hand, systems theories play a crucial role  in practical management since they help managers to look at the organization holistically and more broadly, and recognize the interdependencies among the parts and actors of systems. Based on this perhaps it is better to say that there is an interplay between management theories and systems theories, rather than that systems theory is a synthesis of management theories.
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What are the necessary books for understanding, Perceiving and then execution of system thinking in people’s attitude and improvement of their lives by better Decision Making Process, And also for increase quality of policies and decisions in organizations?
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Here is (somebody else's) list of favourites:
I've used Peter Senge's 'The Fifth Discipline' (https://en.wikipedia.org/wiki/The_Fifth_Discipline) quite a bit
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Control system concepts.... using Input output data we could model a system... and using physical laws also...
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Physical laws(or knowledge model) give you an accurate model of the system but this model is generally complexe so we can simplify this model by reduction technics allowing to have an equivalent model more suitable to control (generally a 2nd order is satisfactory) . It's important to notice that one of the objectives of control is to accelerate slow dynamics (dominant poles) so we don't need to know with precision fast dynamics.
The control model can also be obtained by identification of an input output model (generally a second order). so both approaches can be used for control.
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In the dynamical systems theory, "edge of chaos" is a metaphor describing the transition point between order and chaos. For example, in the context of the logistic map the edge of chaos corresponds to a = 5.569945.., with a the bifurcation parameter. But inside the large chaotic region there are a lot of islands of periodicity characterized by a period-doubling cascade to chaos. Do we have more edges of chaos? What happens for Tinkerbell map, where there is no obvious road from period-doubling bifurcation to chaos? Where is the edge of chaos?
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Hi Dumitru,
If you define the logistic map as x_n+1 = a x_n (1-x_n), then from 3  <  a <  3.5699 , we have periodic orbits of period 2^n and for values of 3.5699  <  a  <= 4, we find chaotic orbits and periodic orbits. This point a =  3.5699 is called the Feigenbaum point (do not confuse with the Feigenbaum constant 4.669). I do not know any definition of what you call "edge of chaos". Thus, if what you call "edge of chaos" is the Feigenbaum point, I would say it is unique. If you refer to transitions between a period region into a chaotic region, I guess there are infinitely many in the chaotic region 3.5699  <  a  <=  4.
Regards,
Miguel A. F. Sanjuán
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What theory contradicts the assertions of General Systems Theory?
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Dear Chadwick, smack to your question: the rivals of GST are: Cartesian and Newtonian scince, i.e. determinism and reductionism. In other words, classical modern science - whether in the natural or in the social sciences.
Besides, the very distinction between the natural and social sciences is questioned by GST. From this standpoint GST stands out against the division of sciences into disciplines.
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I'm working in my doctoral thesis and I will use a neurophenomenological approach in order to shed light about how dual systems theory of decision making (i.e Kahneman and Tversy) are interrelated and controlled.
My background is on engineer but I am very interested in take a mixed complementary approach that include cognitive tasks and measurement, neurological data gathering (by EEG use), and phenomenological interviews in order to deal with the issue from  multiple and concurrent approaches. I lack of any experience using phenomenological research but I understand that is not an easy task, then I am wondering if this great research community could provide some help to me
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Manuel, I support many of the suggestions made already in this thread in relation to phenomenological interviewing  (Smith, Flowers and Larkin is good) and the hermeneutic processes.  
However, I am a little unclear about how phenomenological interviewing will help you.  Perhaps you could explain what you are trying to do there? You seem to want to explore brain activation patterns during cognitive tasks, presumably engaging both implicit thinking and explicit thinking (Kahneman infers all cognition has implicit elements).  That sounds like a very exciting topic and I can see synergies with theoretical phenomenology particularly with Schutz’s adoption of the concept of schemata as organising structures.
As an aside, I hope to publish something on schema and dual cognitive processes shortly. The strength of the schema concept is that it provides a link between System 1 thinking and System 2 thinking and explains some of the interrelationships.  It can also be used to explain phenomena such as the “mental shotgun” described by Kahneman. It also explains which schemata come to dominate at any one moment in time. In reference to your comment about control, I should say that I prefer the more organic models which don’t imply a need for ‘control’ but see conscious thought emerging from dynamic interplay of implicit processes.  For example
·       Norman, DA & Shallice, T 1986, 'Attention to Action: Willed and Automatic Control of Behavior ', in Richard Davidson, J., Gary E.  Schwartz and David Shapiro (eds), Consciousness and Self-Regulation: Advances in Research and Theory, Vol. 4, Plenum Press, New York, pp. 1-18.
·       Huesmann, LR 1998, 'The role of social information processing and cognitive schema in the acquisition and maintenance of habitual aggressive behavior', in Russell G. Geen and Edward Donnerstein (eds), Human Aggression: Theories, research and implications for social policy, Academic Press, San Diego, pp. 73-109.
Part of my question about your proposed use of phenomenological interviewing lies in what I believe it can tell you. My reading of the literature on phenomenological interviewing suggests the interviews may have different shapes. Some focus solely on non-directive, open-ended questions asking for descriptions (Smith et al) others encourage expressive methods of interviewing, eliciting art, poetry etc. that reflect lived experience (e.g. Janet Waters https://www.capilanou.ca/psychology/student-resources/research-guidelines/Phenomenological-Research-Guidelines/).
If you are trying to tease out some of the differences between System 1 and System 2 then using question-based interview may be a viable strategy. However, if you wish to explore underling cognitive processes using phenomenological interviewing there is an issue you might wish to consider.
I see a contradiction in the literature on phenomenological interviewing (one that goes back to Husserl himself) between the focus on lived experience and the idea that reflection is the means of obtaining data on lived experience.  If you accept there is a qualitative difference between System 1 and System 2 thinking you will understand my concern. Reflection is inherently System 2 thinking but experience is largely System 1 thinking.
Madelaine’s suggestion about ‘Think Aloud’ approaches will provide some useful data.  They are particularly useful in testing questionnaires but in my experience they largely capture only System 2 thinking and there is much System 1 thinking that is not revealed (see also)
·       Wilson, TdC & Nisbett, RE 1978, 'The Accuracy of Verbal Reports About the Effects of Stimuli on Evaluations and Behavior', Social Psychology, vol. 41, no. 2, pp. 118-31.
·       Nisbett, RE & Wilson, TD 1977, 'Telling more than we can know: Verbal reports on mental processes', Psychol Rev, vol. 84, no. 3, pp. 231-59.
Some writers (below) provide defences for talk aloud methods but I am not sure either defence works for a project that attempts to elicit implicit understandings, especially if you are working with people who are not trained in meditation.
·       Sudman, Bradburn and Schwarz (1996) Thinking about Answers
·       Petitmengin, C (2006), 'Describing one’s subjective experience in the second person: An interview method for the science of consciousness', Phenomenology and the Cognitive Sciences, vol. 5, pp. 229-69.
I prefer expressive methods because they are more closely linked to System 1 thinking. See for example
  • Jenkins, N, Bloor, M, Fischer, JAN, Berney, LEE & Neale, J 2010, 'Putting it in context: the use of vignettes in qualitative interviewing', Qualitative Research, vol. 10, no. 2, pp. 175-98.
I suggest they are much more likely to elicit cognitive processes that share some of the characteristics of the lived experience (see attached).  However, we do need to recognise that any interview situation is removed from the situation of interest and carries its own freight of context and demands on the participant. 
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I'm building a framework to analyse and evaluate the level of peacefulness of theoretical political economic systems.
I'm concerned about which methodology to use in order to come up with the criteria of reference I will use to evaluate the different systems.
I've been researching system methodologies and design methodologies extensively but couldn't satisfy my specific need.
So far I'm using a design methodology (use case): goal, functions, requirements (= criteria). I could use an evaluation methodology: variables, dimensions, indicators.
Any other idea?
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Hi Numa
I designed a scientific tool to help answer questions such as these in a systems manner. Please refer to this white paper I'm attaching here. It is not for reproduction, but for your personal use only. Contact me if you have any, further questions. 
Regards,
Robert
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I have been utilising in-vivo codes on various established definitions in two fields of study in order to determine if theories derived from the code analysis can be grouped into the two fields of studies. What has emerged is 141 codes that have been grouped into 11 logical categories. 
These categories can be linked to some prominent theories such as System Theory and Institution Theory but others cannot. 
I need assistance with:
  1. Are there any principles in linking coding outputs to established theories?
  2. Are there any principles in handling code categories that do not logically link to established theories?
Thanks. 
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I think your general goal is quite coherent: first inductively coding your material as closely too the participants' own words as possible, and then comparing that coding system to a deductive framework based on existing theory.
As reasonable as this might be, I'm not aware of examples of anyone else following the same path. In terms of reporting your findings, you could create a table with 11 rows and 2 columns, where the cells that match existing theory have small amounts of text to explain the linkage, and then blank cells when your code categories do not match existing theory. The core of your Results section would then be to describe the innovative content that you have found.
As far as Ground Theory goes, you have certainly followed the recommendation of going from open (initial) coding into categorization. The strict use of in vivo codes is a bit unusual, but certainly understandable for your purposes. Beyond that, goal of comparing a set of categories (which is less than a theory) to preexisting theories is not a very good fit to GT. So I personally would say that you used GT methods in ways that would ultimately serve a different purpose.
Of course, you did not mention GT in your original post, and I'm not sure why you want to claim it. The problem being that many GT proponents have a tendency to argue over boundaries -- what is and is not acceptable as GT. Since your work is also compatible with Braun & Clarke's (2006) thematic analysis, I would recommend aligning yourself with that widely used approach to qualitative analysis.
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Given a matrix k(z)=k_1 z^{-1}+k_2 z^{-2}+... of dimension (s x s) whose elements are rational function, one can obtain a matrix fraction description (MFD) (a(z),b(z)), where a(z) and b(z) are polynomials in z, such that they satisfy the conditions in, e.g. "Hannan, Deistler 1988 - The statistical theory of linear systems" page 58 or "Guidorzi 75 - Canonical Structures in the Identification of Multivariable Systems". Is there an algorithm in Maple/Mathematica/some other language available to get (a(z),b(z)) for a given k(z)?
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sorry I do not have the expertise to answer this question.
Regards
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Systems thinking have been quite appealing to academia and industry folks for quite some time now. Many people believe System thinking has not lived up to the expectations. What are the possible causes of its failure and what can be done to make systems thinking an effective problem solving tool? Is it time to propose a new paradigm to understand and solve new age problems? 
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Your question is excellent, and should periodically be discussed. You seem to be assuming that the problem lies with Systems Thinking which is not the case. The problem is in an unwillingness to change. This can be due to any number of reasons. I hope the attached article will be of some help. 
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Say we have a complex network made of n sub-networks and m nodes. Some of the sub-networks share some of the m nodes. Say that such complex network (aka Interdependent Network) is under attack, and say that this attack is not targeted (e.g., does not look for high degree nodes only) nor random, but spatial (both low degree and high degree nodes are being removed). Now, say that the failure cause is external, in addition to being spatial, and that it can feature many levels of spatial extent. Hence, the higher the level, the higher the number of nodes involved, the higher the disruption (theoretically). My problem relates to the failure threshold qc (the minimum size of the disrupting event that is capable of producing 0 active nodes after the attack).
My question: does the failure threshold qc depend on how nodes are connected only (e.g., the qc is an intrinsic feature of the network)? Or is it a function of how vast the spatial attack is? Or does it depend on both?
Thank you very much to all of you.
Francesco
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Yes it's likely to depend on the structure of the network, as it does for a simple network. The situation you describe is quite specific, so I'm not sure the answer is known. The best way is to try to find out!
You might find this review helpful, for some basic ideas http://arxiv.org/abs/0705.0010
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From a design and operational systems perspective: Is complexity always a "bad thing"? and, should simplicity be always preferred over complexity? To what extent the complexity vs simplicity debate influences systems design? Support your answer/comments with examples.
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Dear Francisco et Al:
I see other answers to the issue posed above, that in my view relate more to the system than to the model for assessing the system. So let me provide another alternative/complementary explanation to the one suggested above, which focus more on the complexity of the system, and not the complexity of the model.
From a physical POV, complexity is many times understood as the quality that enables building systems away from thermal equilibrium. Since thermal equilibrium is the state of maximum entropy [or disorder], complexity is many times considered to be equivalent to neguentropy [Bertalanffy, Foerster,...].
Neguentropy is a concept that relates mainly to organization. Any organization implies an expenditure in energy to be built [Lovelock] and creates a difference in information [which allows to understand why Shannon uses Entropy formula for measuring information].
But structures can be stable or instable; can tend to steady states or to critical points. In fact some authors question whether there are any steady states or all real systems tend to Self Organized Critical States [SOC, Bak], where collapse happens as an endogenous feature [i.e., collapse is generated by the usual dynamics that explain the system].
SOC theory is interesting and the economic system has been put as an example of a SOC system.
And relating to this issues, I am finishing a review of the economy of UE-28 countries that may shed some light to the above question from an empirical basis, which we can relate to two issues:
When we review countries’ evolution from classical economic indicators like GDP, employment,… SOC dynamics are clearly present. It seems like the economic cycle tends always to critical states and from time to time a collapse [crisis] is necessary [i.e, cannot be avoided] to adjust the system state [an easy eplanation is understanding that when too fragile structures are built too large, they necessarily collapse]. But…
When we use different variables, SOC dynamics do not appear, and the countries that best perform under classical economic indicators show steady equilibrium states using this other variables…
This is highly interesting. It relates to something many times discussed: the importance of the oberver as whom choses the variables to be reviewed. It also allows us to understand that a sustainability indicator shall be that which value can be stationary in an economic crisis, not which show SOC behaviour.
Of course, those two issues are very important, but they are not related to the issue discussed here, So.. which is the interest? Ok, let me explain it now... 
Any economic activity implies creating structures [i.e., departure from thermal equilibrium], or in other words, implies neguentropy or Entropy reduction. 
And any collapse [as SOC critical episode] implies a neguentropy destruction; a reduction in activity [hence approach to thermal equilibrium].
From a physical point of view, the first is equivalent to what the majority of scientists would consider an increase of the complexity of the system and the second to a reduction in the complexity of the system.
So, if we assess countries using classical economic indicators, we are indirectly measuring sort of their complexity [of course, not all their complexity]. But some of such complexity may be essentially fragile; the next economic crisis it will collapse with high probability [this could be consider as an example of what many people dessignates as 'bad complexity'].
Yet, if we assess countries using sustainability indicators, we are indirectly measuring ‘the part of their complexity’ that can be sustained over time; i.e., the part that can stand a crisis without collapsing [it somehow would be equivalent to what many people considers 'good complexity']
Hope this example provides some ‘empirical content’ to the issue asked above and I am sure that Francisco [a Spaniard as me] is convinced of the important of the above nowadays that Spain is struggling to overcome a devastating economic crisis, largely due to building too unstable structures [sort of 'bad complexity'...]
Regards.
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can anyone help me out and have some information about that
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Hi Ms Nabhani,
you might try very interesting research of James A. Reggia. Check the following links.
Try to observe and rething the video. The subject is very interesting and important. It has a lot of prospective applications. james is a very nice person. If you need ask me for more info but the best way is to study Jamese's papers first.
Good luck at your research,
Jiri Kroc
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We are looking for people in control theory working on the problem of regulation output for non-autonomous linear systems on infinite dimensional state spaces.
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Additionally one can put a static charge on a spacecraft and this will create a force that is the result of a cross product between the spacecraft velocity vector and the magnetic field direction.  However this force is very small and the charge is hard to maintain, so it is generally considered useful only for very specialized applications.
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Grey theory is an extension of fuzzy set theory and rough set theory where two memberships function a lower one and an upper one are used with interval. Grey system theory is a unique concept which deals with continuous systems including uncertain. Grey theory classifies sets into three groups: White sets, Black sets and Grey sets. White set contains objects that have complete knowledge behavior, while black set contains objects which have unknown behavior.
What are the limitation of Grey set as uncertainty model?
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As models of uncertainty, grey sets are very close (one could even argue formally identical) to interval-value fuzzy sets, and therefore share most of their limitations. I guess some good starting references to grasp thir advantages and limitations are
and
and references within them or references citing them.
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Both  TISm and ISm are interpretive in nature; and TISM has been extension of ISM proposed by Honorable Professor Sushil (IIT, Delhi, India).
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ISM interprets only the nodes, whereas TISM interprets both nodes and links in the diagraph. Moreover, in ISM all transitive links are eliminated, whereas TISM can have sme important transitive links giving better explanatory framework. It answers all the three key questions of theory building, i.e. what, how, and why.
Sushil
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Dear Prof.
I think by transitivity we may find the answer.
Best regards,
Risong Li
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Hi everyone,
I want to identify linear model for a pneumatic proportional valve that has hysteresis behavior. I split region of system to 9 sub-regions and apply a PRBS as input of system for every sub-region. Input-output data shows that because of hysteresis, upper bound of sub-region does not match on lower bound of next sub-region. for example, for the first sub-region, input PRBS with bounds of [3350 , 4200] is applied that leads to output flow of [7 , 13] as fig. 1.
for second sub-region, to reaching of output flow in range of  [13 , 20], input PRBS with bounds of [3850 , 4280] is applied as fig. 2.
As can be seen, these sub-regions have overlap and cause problem for identification. how can i solve this problem ?
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Hi Davood,
your main difficulty comes from the fact that you are trying to obtain linear models. This will generally NOT work for systems with hysteresis because such systems are NOT linearizable about an operating point, which is the underlying assumption of trying linear models for nonlinear systems. Other nonlinearizable (in the sense of truncating a Taylor series) examples include bilinear systems, that is, systems that have a dominant time constant in one direction (i.e. heating) and a very different one in the other direction (i.e. cooling). As a matter of fact thermal systems fall into this category.
You either ignore hysteresis or you go for nonlinear models.
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It is often said in the field of complex systems that such systems achieve self-organisation through simple order-generating rules. Under what conditions is such self-organisation achieved?
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This is a good question.    In addition to what @Kamal and @Nizar have incisively observed, there are a few more things to consider.
An overview of different types self-organizing systems is given in
J.A.C. Gomez, Self-organization in biology: From quasispecies to ecosystems, Ph.D. thesis, Unversidad Carlos III de Madrid, 2010:
See Section 1.3 (Self-organization, universality and scaling), starting on page 6.  The challenge is for any entity to survive (and flourish) when it finds itself in situations in between order and disorder.  A very detailed introduction to self-organization in biological systems is given in Section 1.5, starting on page 8.
A very detailed introduction to conditions (and rules) required for self-organizating is given in
C. Gershenson, Design and control of self-organizing systems, Ph.D. thesis, Vrije Universiteit Brussel, 2007:
For example, in typical swarming rules, agents start to move with varying speeds  towards the centre of a swarm, while mutually adjusting their velocities to avoid collisions (see Section 3.2, starting on page 24, especially page 27).    This view of swarming behaviour carries over to artificial self-organizing systems such as a swarm of robots (see Section 3.5.1, starting on page 33) and self-organizing traffic lights (see Section 5.1, starting on page 62).
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Why delays exist in system dynamics given the fact that nothing is standstill in the system dynamics world? When there is a delay between training and its impact on productivity it is not the case that nothing is happening in the duration of 'delay'; nothing is standstill during that period. Delay is only for the purpose of modeling.
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For instance, there is an element of delay between end of training and increase in productivitity to measure training effectiveness. It is not always clear what happens during this interim period we call 'delay'. In case of a long pipe bringing water to the tank dynamics of water in the pipe before reaching the tank can be modeled and what happens during the interim period is visible.
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HR system is a pattern(unique) of the alignment of different HR practices.