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Through the combination of permeability data with pore pressure, porosity and other parameters it is possible to estimate the productivity of the formations. Emphasis goes o… absolute permeability synonyms, absolute permeability pronunciation, absolute permeability translation, English dictionary definition of absolute permeability. (absolute) permeability: scalar or tensor quantity the product of which by the magnetic field strength H in a medium is equal to the magnetic flux density B:. 3m symbol - Die hochwertigsten 3m symbol auf einen Blick. NOTE – Absolute permeability is a scalar quantity in an isotropic medium and a tensor quantity in an anisotropic medium. According to the definition, magnetic permeability is a physical unit that has the formula symbol µ. In simple terms, permeability is an ability of any material to permit the density of the magnetic flux. According to Micrometals-Arnold High Frequency Sendust data. from Absolute permeability Definition: the permeability of free space, which has the value 4π × 10 –7 henry per metre | Bedeutung, Aussprache, Übersetzungen und Beispiele It typically requires a sensitive analytical balance to detect the effect. In ferromagnetic materials, the relationship between B and H exhibits both non-linearity and hysteresis: B is not a single-valued function of H,[5] but depends also on the history of the material. Permeability solely depends upon the medium being used, so, ‘type of medium’ plays a major role here. The paramagnetic property of an element depends on the electronic configuration, and they are weakly attracted to the magnet, and they don’t retain their magnetism after an external magnetic field is removed. The absolute permeability (m) of a soft iron core is given as 80 milli-henries/meter. Paramagnetic materials are attracted to magnetic fields, hence have a relative magnetic permeability greater than one (or, equivalently, a positive magnetic susceptibility). Auf welche Punkte Sie zuhause bei der Wahl Ihres Arabic christian symbol achten sollten. Permittivity is the ability of a material to allow electric fields to pass through, (like in capacitors) which depends upon the material being used and Permeability is the allowance of the magnetic field on various factors. But inductance is magnetic flux per unit current, so the product has dimensions magnetic flux per unit area, that is, magnetic flux density. Arabic christian symbol - Die ausgezeichnetesten Arabic christian symbol verglichen . Die magnetische Feldkonstante, auch Magnetische Konstante, Vakuumpermeabilität oder Induktionskonstante, ist eine physikalische Konstante, die eine Rolle bei der Beschreibung von Magnetfeldern spielt. The relationship be-92 PYP100: First Year B.Tech. The product μH thus has dimensions inductance times current per unit area (H⋅A/m2). It’s a value between 1 and 0, but in practice hardly ever reaches 1. This is reinforced by a material with high permeability because it can be magnetized. One darcy is the permeability of a sample 1 cm long with a cross-sectional area of 1 cm2, when a pressure difference of 1 dyne/cm2 between the ends of the sample causes a fluid with a dynamic viscosity of 1 poise to flow at a rate of 1 cm3/s (Fig. Unabhängig davon, dass die Bewertungen ab und zu manipuliert werden, geben sie in ihrer Gesamtheit einen guten Orientierungspunkt ; Welches Ziel beabsichtigen Sie mit Ihrem 3m symbol? n the permeability of free space, which has the value 4πx10--7henry per metre., (Symbol) M0 (Also called) absolute permeability. Relative Permeability (ᵣ) of a medium is defined as the force between two poles when placed at a fixed distance in vacuum to the force between them at the same distance in that medium. Permeability is typically represented by the (italicized) Greek letter μ. The units of permeability are the darcy, D, and 2, where 1 D = 0.9869m ×10-12 m2. μ The permeability constant μ0, also known as the magnetic constant or the permeability of free space, is the proportionality between magnetic induction and magnetizing force when forming a magnetic field in a classical vacuum. i.e. B(2) and Fig. Absolute permeability Definition: the permeability of free space, which has the value 4π × 10 –7 henry per metre | Bedeutung, Aussprache, Übersetzungen und Beispiele English Collins Dictionary - English Definition & Thesaurus. Q1: What is the Basic Difference Between Permittivity and Permeability? An average permeability can also be calculated from production-history data by adjusting permeability until the correct history of production is obtained. Die magnetische Feldkonstante, auch Magnetische Konstante, Vakuumpermeabilität oder Induktionskonstante, ist eine physikalische Konstante, die eine Rolle bei der Beschreibung von Magnetfeldern spielt. Each data point represents an average value of porosity and permeability. 0 The reciprocal of permeability is magnetic reluctivity. Permeability. It all depends upon the composition and the temperature, on the basis on which the electrons are polarized. Results of absolute permeability estimation by artificial neural network in well B and C. Symbols of Polish informal stratigraphic unit as in Fig. The term Absolute Permeability (ₐ) of a material is the product of permeability of free space ₀ ( = 4 ⨯ 10⁻⁷ henry/meter) and the Relative Permeability ᵣ . absolute permittivity synonyms, absolute permittivity pronunciation, absolute permittivity translation, English dictionary definition of absolute permittivity. so that the permeability becomes a complex number. In electromagnetism, the absolute permittivity, often simply called permittivity and denoted by the Greek letter ε (epsilon), is a measure of the electric polarizability of a dielectric. The absolute permeability of another material can be expressed relative to the permeability of free space. According to Ferronics Incorporated data. absolute permittivity synonyms, absolute permittivity pronunciation, absolute permittivity translation, English dictionary definition of absolute permittivity. Permeability is denoted by a Greek symbol ‘m’. They are given for a zero frequency; in practice, the permeability is generally a function of the frequency. The relationship be-92 PYP100: First Year B.Tech. Wie sehen die Amazon Nutzerbewertungen aus? by, G.W.C. Thus, permeability represents how much it would be helpful in energy conservation.Permeability is two types: Absolute and Relative. Das Team vergleicht eine Vielzahl an Eigenarten und verleihen dem Artikel am Ende die abschließende Testnote. Basic Rock and Fluid Properties 11. Charles-Augustin de Coulomb was the first French physicist and military engineer who introduced the Laws of Magnetic Force in 1785 known as Coulomb’s Inverse Square Law of magnetic force or Coulomb’s Law of magnetic force.He represented the quantitative expression of force for two isolated point poles. Absolute Permeability is used to analyze the formation rock. The objective of this experiment is to measure the absolute permeability of water using a method based on the Darcy theory. Laby, Table of Physical and Chemical Constants, 14th ed, Longman. B Fleming’s left - hand rule states that if we stretch the thumb, middle finger and the, The index finger of the left hand in such a way that they make an angle of 90 degrees       (Perpendicular to each other) and the conductor placed in the magnetic field, Thumb: It points towards the direction of force (F), Middle finger: It represents the direction of the current (I), Index finger:  It represents the direction of the magnetic field (B). If the frequency of supply varies, then, harmonics will develop, which would create a humming sound, which usually happens in the Transformer. Sorry!, This page is not available for now to bookmark. The experimental results show that Darcy's law is not capable of accurately predicting the transport, especially in MPLs due to … 1. n. [Geology] The measurement of the permeability, or ability to flow or transmit fluids through a rock, conducted when a single fluid, or phase, is present in the rock. Specifically, an external magnetic field alters the orbital velocity of electrons around their nuclei, thus changing the magnetic dipole moment in the direction opposing the external field. Absolute Permeability is the ability of a reservoir rock to allow fluids to flow through its pores. μ = 1.113 (kg/m 3) 16.97 10-6 (m 2 /s) = 1.88 10-5 (kg/(m s), N s/m 2) Viscosity of some Common Liquids The number χm is a dimensionless quantity, sometimes called volumetric or bulk susceptibility, to distinguish it from χp (magnetic mass or specific susceptibility) and χM (molar or molar mass susceptibility). It is … A material with high permittivity polarizes more in response to an applied electric field than a material with low permittivity, thereby storing more energy in the material. It is generally a quite weak effect in most materials, although superconductors exhibit a strong effect. 4 Full size image The correlation coefficient between the absolute permeability from the artificial neural networks … Introduction To Heat, Internal Energy And Work, Introduction and Characteristics of Management, Introduction to Organisation and Its Importance, An Introduction to Atomic Number, Isotopes and Isobars, Relative Measures of Dispersion and Lorenz Curve, Introduction to the Composition of Functions and Inverse of a Function, Vedantu It indicates the flow capacity of formation. Values shown above are approximate and valid only at the magnetic fields shown. Diamagnetism is the property of an object which causes it to create a magnetic field in opposition of an externally applied magnetic field, thus causing a repulsive effect. mr of magnetic materials such as cobalt, nickel, iron, steel, and their alloys are far greater than unity and are not constant, as you can see in Fig. Auf welche Faktoren Sie zu Hause vor dem Kauf Ihres 3m symbol Aufmerksamkeit richten sollten! Solution:. Pro Lite, Vedantu μ = dynamic or absolute viscosity (cP) SG = Specific Gravity ν centiStokes = kinematic viscosity (centiStokes) SSU at other temperatures; Degree Engler. The measurement of the permeability, or ability to flow or transmit fluids through a rock, conducted when a single fluid, or phase, is present in the rock. The mr of a non-magnetic material, such as air, copper, wood glass, and plastic are, for all practical purposes, equal to unity. Absolute permittivity Definition: the permittivity of free space, which has the value 8.854 187 × 10 –12 farad per metre | Bedeutung, Aussprache, Übersetzungen und Beispiele Kaye & T.H. Relative permeability and magnetic susceptibility, The permeability of austenitic stainless steel strongly depends on the history of mechanical strain applied to it, e.g. An entire sub-branch of physics is devoted to the study of the effectsproduced within various materials by the application of a magneticfield. Welchen Kostenfaktor kostet der 3m symbol … Sie gibt das Verhältnis der magnetischen Flussdichte zur magnetischen Feldstärke im Vakuum an. where A closely related property of materials is magnetic susceptibility, which is a dimensionless proportionality factor that indicates the degree of magnetization of a material in response to an applied magnetic field. {\displaystyle \mu _{\mathrm {r} }} B = μ H. Note – For an isotropic medium the absolute permeability is a scalar; for an anisotropic medium it is a tensor. Define absolute permittivity. In SI units, permeability is measured in henries per meter (H/m), or equivalently in newtons per ampere squared (N/A2). According to Siemens Matsushita SIFERRIT data. Its relation to permeability is. n the permittivity of free space, which has the value 8.854 187 × 10–12 farad per metre. The symbol most commonly used for permeability is k, which is measured in units of darcies or millidarcies. These web pages make no attempt to cover the subject fully, andif you wish to explore it in greater depth then you should consult atext such as Jiles. The relative permeability symbol r, is de ned as the product of (absolute permeability) and o, the permeability of free space. absolute permeability. This is because there are several saturation configurations that do not allow fluid movement at all. Multiphase Flow Permeability in a porous medium that is 100% saturated with a single-phase fluid is the absolute permeability , or synonymously, the intrinsic permeability or specific permeability . Permeability is typically represented by the (italicized) Greek letter μ. Most inductor calculations make use of it, or one of its multitudinousvariants. Magnetic Intensity defines the degree of magnetism (created by a magnetic field) a material can hold in itself. Any element which has unpaired electrons in its outermost shell such that when it is placed in the magnetic field, possess high magnetic field strength, and retains this attribute even if an external magnetic field is removed. One thing can be observed that the element, “Fe” behaves as both Paramagnetic and a ferromagnetic as well, why is there a difference? Permeability is typically represented by the (italicized) Greek letter μ. Permeability and Relative Permeability of Materials. In terms of relative permeability, the magnetic susceptibility is. Paramagnetism is a form of magnetism which occurs only in the presence of an externally applied magnetic field. Absolute permeability. In dieser Rangliste finden Sie die absolute Top-Auswahl an Arabic christian symbol, während die Top-Position unseren Favoriten darstellt. The magnetic moment induced by the applied field is linear in the field strength and rather weak. … Welchen Kostenfaktor kostet der 3m symbol überhaupt? Define absolute permeability. Porosity, given the symbol f,isdeﬁned as the ratio of void volume to total rock volume: ... Single-phase absolute permeability is measured on core in a steel cylinder where pressures P 1 and P 2 are measuredfor a given gas ﬂow rateQ (Fig.2.6). It is similar to susceptibility and indicates how permeable a material is to the magnetic flux density. Any material let’s say Iron when placed inside the magnetic field possesses magnetism in itself. n the permeability of free space, which has the value 4π × 10–7 henry per metre. The effect of irreducible saturation of rel. 1. n. [Geology] The measurement of the permeability, or ability to flow or transmit fluids through a rock, conducted when a single fluid, or phase, is present in the rock. Results of absolute permeability estimation by artificial neural network in well B and C. Symbols of Polish informal stratigraphic unit as in Fig. and, Intensity of Magnetization of a magnetic material is defined as a magnetic moment per unit volume of the material, which is calculated as: Which is high for Ferromagnetic material and low for a diamagnetic material. Dielektrizitätskonstante, ε, DK, Permittivität, Influenzkonstante, elektrische Feldkonstante, Proportionalitätsfaktor zwischen der… According to Magnetics MPP-molypermalloy powder data. The relative permeability symbol r, is de ned as the product of (absolute permeability) and o, the permeability of free space. While the material like Wood, Aluminium doesn’t allow the magnetic fields to pass via and, they are reluctant to permit magnetism in itself, that’s why they also are calculated regarding permeability of free space or permeability constant. According to the definition, magnetic permeability is a physical unit that has the formula symbol µ. Degree Engler is used in Great Britain as a scale to measure kinematic viscosity. In geological applications the darcy is commonly too large for practical . Magnetic permeability is defined as the ratio of flux density to the magnetic force which is given as: $$\mu =\frac{B (Tesla)}{H (\frac{A-t}{m})}$$ Absolute Permeability 3m symbol - Der absolute Favorit . Permeability varies with a magnetic field. Permeability working can be observed in transformers. The following table should be used with caution as the permeability of ferromagnetic materials varies greatly with field strength. (absolute) permeability: scalar or tensor quantity the product of which by the magnetic field strength H in a medium is equal to the magnetic flux density B:. Samples of artificially mixed and packed sands were measured for porosity and permeability. In general, permeability is not a constant, as it can vary with the position in the medium, the frequency of the applied magnetic field, humidity, temperature, and other parameters. {\displaystyle H} For passive magnetic levitation a relative permeability below 1 is needed (corresponding to a negative susceptibility). Define absolute permeability. r ≈ The reciprocal of permeability is magnetic reluctivity. The type of material we use decides the amount of work being done, which in turn means the strength of the magnetic field created around the material. The materials such as Magnesium, Molybdenum, Lithium, possess Paramagnetism. In a nonlinear medium, the permeability can depend on the strength of the magnetic field. Table 1.1, shows the strength of the magnetic field of elements like Co, Ni, and Fe. The resistance of such a substance is accordingly low. absolute permeability. Types of material: Ferromagnetic, Paramagnetic, and Diamagnetic. A relative permeability as 950 with grain size and degree of magnetism ( created by a magnetic is. Symbol ‘ m ’ is that if you are restricted to justone parameter to describe is. The ratio of magnetic flux around itself that has the value 8.854 187 × 10–12 farad per metre as,! Is measured in absolute permeability symbol of darcies or millidarcies die relevanten Unterschiede und die hat! A material to concentrate magnetic flux density to the magnetic field strength and this explains the dependency. Definition of absolute permeability. 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# Meter signature

The meter signature or time signature is an indicator of the meter of a musical work, usually presented in the form of a fraction, the denominator of which indicates the unit of measurement and the numerator of which indicates the number of units that make up a measure. The time signature is typically located at the beginning of the first musical staff of a piece or movement, just after the key signature.

The denominator of the time signature indicates which note value represents the basic beat, or tactus, what a conductor typically would beat. In this position, one most often finds the numbers 2, 4, 8, or 16. These numbers represent, respectively, the half, quarter, eighth, and sixteenth notes. On occasion it contains a 1 (representing a whole note) or 32 (thirty-second note), and very rarely 64 (sixty-fourth note). While numbers falling outside of this two-square pattern (i.e. 3 or 5 or 17) can theoretically make up the denominator, musicians are not trained to understand this notation, as it goes against the grain of Western rhythmic principles, and thus it almost is never written this way by composers.

The numerator of the time signature indicates how many of a given tactus make up a measure. Thus, "common-time," or $\frac{4}{4}$ means four quarter notes make up one measure. This number is subject to much more variety than the denominator, but with numbers between 2 and 8 being most common. Increasingly since the late 19th-century, composers have made frequent use of the so-called "odd meters" such as $\frac{5}{4}$ or $\frac{7}{8}$.

Time signatures do more than represent the basic facts of the meter, they also give clues to the musician as to style and character. Since composers have a variety of choices within this system, in that a triple meter could be written in $\frac{3}{4}$, $\frac{3}{8}$, or $\frac{3}{2}$, the composer makes a conscious choice, based on whether the piece has a broad or lively character. For example, $\frac{2}{2}$ time, often referred to as "cut-time," is the meter of choice for marches, so a musical work written in this movement might suggest a march-like interpretation even if the word "march" were not in the title. Some intelligent deduction is required, however, because it is also the meter of pavanes, a slow-moving dance of which Wagner's wedding march (written in $\frac{4}{4}$ !) is a well-known example.

Two more trends in 20th century music bear mention. The first is the use of frequently changing meter, first used extensively by Stravinsky, who in his Concerto for Piano and Winds wrote passages where every measure is in a different meter. With this practice, it is debatable if a discernible meter is ever established, and composers often seem to use this tool to evade any sense of meter. On quite the opposite side, another trend is for the use of "additive" time signatures, which appear like this:
$\frac{2+3+2}{8}$

What this means is that each measure contains beats of different lengths. Often with this type of time signature, the bottom number does not represent the tactus, rather the smallest rhythmic unit, which is grouped in various configurations into larger pulses. This music often has a discernible groove, and many other musical traditions in Eastern Europe and South America are based on this kind of rhythmic structure.

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# Why do convolution kernels such as Gaussian, Laplacian, LoG almost always seem to be expressed in integers?

I'm a total newb in search of some deeper understanding, but I'm not able to read the maths behind these on Wikipedia.

If I understand correctly, you get the new value for each pixel by multiplying each of its neighbours' values by the corresponding member of the convolution kernel/matrix. For Laplacian there seem to be two commonly used such kernels:

 0 -1  0
-1  4 -1
0 -1  0

and:

-1 -1 -1
-1  8 -1
-1 -1 -1

But why do they use only integers? I believe modern devices have floating point as fast as faster integer math these days.

Is this just a leftover from the past when floating point was slow and now it's become a kind of tradition? Perhaps people just re-using the old info they find from those days without deeper understanding? Or is there an actual reason why integers are used?

In fact, won't the use of integers here result in artefacting? What am I missing?

• related – hippietrail Sep 11 '19 at 7:02
• Do you have enough information to validate an answer? – Laurent Duval Oct 3 '19 at 20:28
• @LaurentDuval: No. I don't. I couldn't get my Android project to work when I tried to add LoG to it and got no answers on SO. I couldn't gain enough understanding in whether I should be able to use both floating point and integer matrices if I used appropriate values and don't know where to ask for help. I also don't understand how I might break Laplacian into two one-dimensional passes though I do for Gaussian. Also for Laplacian I don't know if I can in both float and int, or if it makes sense in int. \-: – hippietrail Oct 4 '19 at 6:55

The Laplacian kernel with the 4 in the middle results from summing second derivatives along the two axes ([1,-2,1]). Those are the right values to use, you can show this by writing out the math for the second derivative and set the distance h to 1 (or search for discrete approximation to derivative). This kernel hasn’t been rounded, the values just happen to be integer.

The other kernel, with 8 in the middle, does not provide correct values for the Laplacian, but uses more input values and hence is a bit more robust against noise (but not by a whole lot).

The assertion "almost always seem to be expressed in integers?" does not seem to be true, in my opinion. However, such kernels are pretty frequent in codes. They are quantized both in support (limited discrete support) and amplitude (signed integer values). $$3\times 3$$ masks with integer coefficients, as you showed, are very familiar, albethey approximations.

Indeed, most (of such linear operators) derive from continuous formulations, combining derivatives and smoothing kernels; the Gaussian being, possibly, the most common of the latter. Sampling in the space or in the value domain result in artifacts, and at the same time in simpler computations (less taps, less bits), this is a fundamental balance.

In 2D, my experience is that sampling has be studied more that quantization, as sampling is way more linear... One example of alternative optimized 2D designs is in:

You image sensor needs to quantize the image information anyways. Typical range of quantization is anywhere between 8 and 16 bits per pixel (per color channel). So your image is already integer, there is no gain in converting it to float.

And yes, integer arithmetic is still much faster than floating point arithmetic. Just check the recent graphic cards, INT8 (or even INT4) computations are experiencing a huge revival because they are so much faster and sometimes enough (inference in machine learning, for instance). Image filtering is a massive-throughput application, you want to squeeze every bit out of it you can.

• Unless I'm missing something, I'm not seeing the connection between not being able to specify something between 0 and -1 and converting the image to float, which it seems like you're saying. The results of some of these filters is a matrix of floats which you may turn back into pixels (quantize) or may do something else with. The something to gain would be the ability to have smooth gradients. This would I suppose also be possible if the integers were spread over a bigger range, but I don't grok the math behind it so there may be a reason for that too. – hippietrail Sep 10 '19 at 6:56
• @hippietrail You need to explain us why that would be better. Say, I want to do edge detection. My image is integers. I'll use the $[0, -1, 0]$ filter, in two dimensions, it will detect edges. You're saying using a $[0, -0.5, 0]$ would be better? Why? The result is just a scaled version (1/2) of the result you'd get via the integer-valued filter. I cannot see how floating point filter coefficients would give us smooth gradients (or anything else that is not the same as rescaling the integer solution). Can you give an example (edit your question maybe)? – Florian Sep 10 '19 at 15:19
• I'm not saying it would be better. I'm just trying to learn understand. I'm from the 8-bit days where we used to do everything in integer yet I still find it counterintuitive. I'll have to come back when I've gained understanding by other methods. Thanks for your patience. – hippietrail Sep 10 '19 at 15:59
• @hippietrail: no problem at all. I hope you get my point though: instead of filtering with, say $[0.1, 0.3]$, you can filter with $[1, 3]$ and divide the result by 10. It's the same. Or don't even divide it, since images are typically displayed normalized anyways. If you're worried about overflows, embed your integer into the next bigger integer type. Strictly speaking this only works for rationals, but I don't see why filtering with $\sqrt{2}$ would be a good idea :) – Florian Sep 10 '19 at 16:04
• Not all filtering results are only meant for display. In my work, which is about quantification, it is very important to preserve fractional results and filter with correctly computed kernels. Rounding in the original image can be modeled as uniformly distributed noise. Rounding the kernels and the filtering result leads to additional imprecision in that is sometimes not at all welcome. – Cris Luengo Sep 15 '19 at 15:13


text:
Ergodicity of Random Walk

The Random walk is a special case of AR(1) with

$x_t = \phi x_{t-1} + \epsilon_t$ with $\phi = 1$

A process is ergodic if two samples of a stochasitc process sampled far (say j < $\infty$ ) apart are independent.

Can someone help me know if the random walk is ergodic and how ?

• Are you sure of your definition of ergodicity? A theorem known to me is "a stationary process is ergodic if any two random variables positioned far apart in the sequence are almost independently distributed". But this theorem cannot be applied to a random walk, since it is not stationary. The general definition of ergodicity is another one. – noob2 May 15 '18 at 0:44


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# Mathematics and Computation

## Friday-Sunday, 19-21 June, 2015Venue: CARMA, The University of Newcastle

This three-day workshop, organized by Jonathan Borwein, is envisioned to include the following sessions:

1. Computer-assisted discovery (Jon Borwein and Matt Tam)
2. Formal proof and computer-assisted proof (Jeremy Avigad and Rob Lewis)
3. Computational group theory (John Cannon, George Willis, Murray Elder)
including celebration of the 50th anniversary of the discovery of the Janko group
4. Computational number theory and related topics (Wadim Zudilin and Richard Brent)

## External Keynote Speaker Biographies

Jeremy Avigad is a Professor of Philosophy and Mathematical Sciences at Carnegie Mellon University, with research interests in mathematical logic, proof theory, philosophy of mathematics, formal verification, automated reasoning, and the history of mathematics. He received a BA in Mathematics from Harvard College in 1989, and a PhD in Mathematics from the University of California, Berkeley, in 1995. He has held visiting positions at the Microsoft Research - Inria Joint Centre in France and at Microsoft Research Redmond. He has also held fellowships from the Andrew W. Mellon Foundation and the John Templeton Foundation, and his research has been supported by the National Science Foundation and Air Force Office of Scientific Research.

Cristian S. Calude, a member of Academia Europaea, is Chair Professor of Computer Science and Director of the Centre for Discrete Mathematics at the University of Auckland, New Zealand. He had more than 25 visiting appointments including visiting professorships at Cambridge University, Ecole Normale Superieure and Ecole Politechnique in Paris, Japan Advanced Institute of Science and Technology, Microsoft Research Trento, Sandia National Laboratories. He works in algorithmic information theory and quantum physics where he published more than 250 articles and 8 books.

John Cannon is perhaps best-known as the originator of Magma, a software package designed for computations in algebra, number theory, algebraic geometry and algebraic combinatorics. It provides a mathematically rigorous environment for defining and working with many algebraic structures, and also supports a number of databases designed to aid computational research in those areas of mathematics which are algebraic in nature.

Don Taylor graduated in 1968 from Monash University with an MSc supervised by Zvonimir Janko. He then travelled to the University of Oxford where he completed a DPhil with Graham Higman. In 1972 Don took up a lectureship at La Trobe University and in 1975 he moved to Sydney where he has been ever since. He has written several books on group theory, the most recent in 2009 (with Gus Lehrer) on complex reflection groups.

## Registration

There is no charge for attending the workshop, but please register at Eventbrite if you wish to attend.

## Venue

The conference will be held in V104, with refreshments upstairs CARMA room, V205, in the Mathematics Building at the University of Newcastle. A map of the campus is available here, click on "V Mathematics" in the list below the map to highlight its position.

## Friday 19th

"A heuristic prover for real inequalities"
2:45-3:30Rob Lewis (Carnegie-Mellon)
"Dependent types and the algebraic hierarchy"
3:30-4:00Coffee
4:00-5:00Cris Calude (Auckland)
"Proving quantum indeterminism: Measurements of value indefinite observables are unpredictable"
5:00-7:00Reception

## Saturday 20th

9:30-10:30John Cannon (Sydney)
"The Classification Theorem for Finite Simple Groups as a Basis for Algorithms for Finite Groups"
10:30-11:00Coffee
11:00-12:00Don Taylor (Sydney)
"Janko's sporadic simple groups: a bit of history"
12:00-1:00Murray Elder (Newcastle)
"Computational problems in infinite groups"
1:00-1:30John Harrison (Newcastle)
"Experimental computations related to the asymptotic behaviour of random walks on certain matrix groups"
1:30-2:30Lunch
"On a family of polynomials related to $\zeta(2,1) = \zeta(3)$"
3:30-4:00Matt Skerritt (Newcastle)
"On the use of GPUs in Mathematical Computation"
4:00-4:30Coffee
4:30-5:30Richard Brent (Newcastle and ANU)
"Asymptotics of some functions arising in number theory and analysis of algorithms via computation and Mellin transforms"
5:30-6:00Attila Egri-Nagy (Western Sydney)
"Extending the computational horizon"
7:00-10:00Workshop Dinner

## Sunday 21st

9:30-10:30Pablo Moscato (Newcastle)
"Using Evolution and L-systems for Intelligent Design and other attempts to narrow the gap between Theory and Practice in Computer Science"
10:30-11:00Coffee
11:00-11:30Michael Rose (Newcastle)
"Expectations over Fractal Sets"
11:30-12:00Matt Tam (Newcastle)
"Reconstruction algorithms in blind ptychographic imaging"
12:00-1:00Jon Borwein (Newcastle)
"Short walks in higher dimensions"
1:00-2:00Lunch

## Transportation

### Sydney Airport to Newcastle

For those arriving at Sydney Airport we recommend taking the train most of the way to Newcastle (the train line has recently been truncated and you will need to transfer to a bus or other alternative at Hamilton Station). For information and trip planning, please visit

www.transportnsw.info

You should take the T2 Airport Line from Domestic/International Airport Station to Central Station and then the Central Coast & Newcastle Line Hamilton Station. From Hamilton Station you must transfer to a bus into the city.

Alternatively, there is the Happy Cabby Airport Shuttle Service which you will need to book in advance.

### Newcastle Airport to Newcastle

For those arriving at the Newcastle Airport we recommend taking a taxi to Newcastle. The taxi rank is adjacent to the arrivals area of the terminal. Newcastle Taxis can be contacted directly, free-of-charge, on the dedicated taxi phone located in the arrivals end of the terminal.

Alternatively, you can catch the 130 or 131 bus from the Newcastle Airport to the Newcastle Station. From Newcastle Station it is an easy walk to the recommended hotels. For more information and/or to plan your exact trip times see the CityRail website or the Port Stephens Coaches timetables.

### Local Transportation in Newcastle

Newcastle Taxis: bookings can be made online or by calling 133 300 within Australia.

For public transport options, please visit www.transportnsw.info.


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# Concentration change in CSTR

1. Sep 1, 2014

### Maylis

Hello,

Suppose A and B are continuously added into a tank, and exit stream consists of A,B,C, and D. I am a little confused on the following point as I follow the example in my textbook.
The reaction is
$A + B → C + D$

It says because (and I quote) ''...Because the system is operated at steady state, if we were to withdraw liquid samples at some location in the tank at various times and analyze them chemically, we would find that the concentrations of the individual species in the different samples were identical. That is, the concentration of the sample taken at 1 P.M. is the same as that of the sample taken at 3 P.M. Because the concentrations are constant and therefore do not change with time,
$\frac {dC_{A}}{dt} = 0$
$r_{A} = 0$
which is incorrect because C and D are being formed from A and B at a finite rate. Consequently, the rate of reaction defined by equation 1-1 cannot apply to a flow system and is incorrect if it is defined in this matter''.

equation 1-1 just equates the change in concentration of a species to the rate of formation/disappearance of a species.

Where I am confused here is exactly what is meant by $\frac {dC_{A}}{dt}$. It seems to be in the stream where A enters, it is 100% A. When it gets into the tank, it is now mixed with B, so it's concentration is less. So that means $\frac {dC_{A}}{dt} \ne 0$.

Perhaps the wording is confusing. So it is saying, if I pick an arbitrary location in the tank, the concentration of the chemical species A should be the same at all times. In my head, I am thinking that the $\frac {dC_{A}}{dt}$ is the change in concentration of A as it moves through the CSTR. At $t = 0$, it enters the reactor as some concentration $C_{A_{0}}$ and leaves the reactor at concentration $C_{A_{\tau}}$, where $t = \tau$ is the residence time of the CSTR. So in this scenario there is a change in concentration of species A over a finite time, hence that derivative should not be equal to zero. This is clearly not what is meant by that equation, which is somewhat alluding me.

It appears to mean that the change in concentration in a very specific location is not changing with time, hence the derivative is zero. But then that begs the question why are we analyzing it in that way, and not what I mentioned before? What am I missing here?

Last edited: Sep 1, 2014
2. Sep 1, 2014

### Staff: Mentor

In the case of both a well-stirred batch reactor and a CSTR, dC/dt is equal to the rate of change of concentration C within the tank. It is not the rate of change of concentration following a parcel of fluid.

Before you can get a feel for this, it is helpful to first consider the case with no reaction in a CSTR. Suppose that the concentration of a trace species is held constant in the feed at C0, so that the concentration within the tank is also C0, as is the concentration in the exit stream. Now, at some time t = 0, we suddenly lower the concentration in the feed to 0. A mass balance on the concentration within the tank will be:
$$V\frac{dC}{dt}=-FC$$
where V is the volume of fluid in the tank and F = feed rate = exit flow rate. What do you get for the concentration in the tank as a function of time?

Chet

3. Sep 1, 2014

### Maylis

When you say it is the change in concentration within the tank, there are still some doubts in my mind. Why wouldn't the change of the concentration of a parcel of fluid entering and exiting the tank be the same as the change of concentration within the tank? The term ''change in concentration within the tank'' is ambiguous to me, so I am not really sure what is meant.

4. Sep 1, 2014

### Staff: Mentor

Please be patient and bear with me. I'll be using the problem I posed to help you understand what is happening. Please provide the solution to the problem I posed so the we can start talking about Residence Time Distributions.

Chet

5. Sep 1, 2014

### Maylis

Yeah I will get back to that, I had my solution typed with latex then my computer crashed right when I finished

6. Sep 1, 2014

### Maylis

Okay, so now for my solution to the problem posed.

To start off with the most general mole balance, since we have an unreacting system. For a species $i$, the general mole balance is for $t < 0$

$\frac {dn_{i}}{dt} = \dot {n_{i,in}} - \dot {n_{i,out}} + \dot {G_{i}}$

With no mole generation, and the number of moles entering the tank equal to the moles exiting the tank, we have

$\frac {dn_{i}}{dt} = 0$.

For the problem posed, at $t = 0$, the general mole balance

$\frac {dn_{i}}{dt} = \dot {n_{i,in}} - \dot {n_{i,out}} + \dot {G_{i}}$

Since the concentration is zero, and we know that the number of moles is equal to the product of volume and concentration, the number of moles coming into the tank is zero, and the generation term is zero as well. This simplifies to

$\frac {dn_{i}}{dt} = \dot {-n_{i,out}}$

We remember that $F$ is the flow rate, Substituting $\dot{n_{i}} = C_{i}F$, we get

$\frac {d(C_{i}V)}{dt} = -C_{i}F$
Since the volume is constant, it can be removed from the derivative,

$V \frac {dC_{i}}{dt} = -C_{i}F$

Using algebra, we get

$\frac {dC_{i}}{C_{i}} = - \frac {F}{V}dt$

Integrating this

$\int_{C_{0}}^{C_{i}} \frac {dC_{i}}{C_{i}} = \int_{0}^{t} - \frac {F}{V}dt$

which becomes

$ln(\frac {C_{i}}{C_{0}}) = - \frac {F}{V}t$

Definining $\frac {V}{F}$ to be the residence time, $\tau$, we get the concentration in the tank as a function of time,

$C_{i} = C_{0}e^{-t/\tau}$

Last edited: Sep 1, 2014
7. Sep 1, 2014

### Maylis

How do I get the dot to be above the letter, instead of how it is right now over the subscripts?

8. Sep 2, 2014

### Staff: Mentor

Excellent. But τ is not the residence time, it is the mean residence time. Your equation shows that, because the tank is well-mixed, some of the trace species comes out right away at time t = 0, while the reaminder comes out at later times. So, there is a distribution of residence times for the trace species in the tank. At any time t, the fraction of the original amount of trace species molecules still remaining in the tank is $e^{-t/\tau}$. So, if reaction were taking place, some of the trace species would be able to leave the tank before any significant amount of reaction occurred, while some of the trace species would have much more time to react before it left the tank.

So the parameter t in the general CSTR equation is just the amount of elapsed time since some change was made (not the reaction time for all of the trace species), and the equation takes into account everything regarding the residence time distribution that I discussed in the previous paragraph in a mathematically correct way. For example, if the trace species is dissociating by a first order reaction, the mass balance equation for the CSTR (with steady flow rate in and out) leads to:

$$V\frac{dC}{dt}=F(C_{in}-C)-kVC$$

If the flow rate in and out, F, is equal to zero, you recover the batch reactor equation (and t is identical to the reaction time), but, if the reaction rate is zero, you recover the flow-with-mixing equation. At steady state, the time derivative is zero (assuming Cin is constant), and you obtain:

$$C=\frac{C_{in}}{1+kτ}$$

Hope this helps.

Chet


text:
# Numerical solving a constrained system of differential equation

I am in trouble on finding a numerical technique to solve the following system of equations

$$\ddot q_1(t)=f_1(q_1(t),q_2(t))$$

$$\ddot q_2(t)=f_2(q_1(t),q_2(t))$$

with a constrain of the kind:

$$q_1(t)+q_2(t)=Q$$

with $Q$ a constant and a nonholonomic constraint:

$$q_1(t)>0 \qquad q_2(t)>0.$$

I would appreciate also good references and whether such kind of question could be more suitable for MathOverflow.

Thanks a lot.

-
If you introduce new variables $u_1$ and $u_2$ such that $q_1 = \exp(u_1)$ and $q_2 = \exp(u_2)$, then the non-holonomic constraint will be automatically satisfied. Mathematica's NDSolve has "Projection" method for projecting on the manifold, which you can use to solve the rest. Once the solution is obtained, postprocess it to recover $q$-s. –  Sasha Jan 31 '12 at 14:48
@Sasha: Thanks a lot! Please, could you expand more on this putting it as answer? –  Jon Jan 31 '12 at 15:50

## 1 Answer

I'm not sure about the problem you want to solve. The system of ODEs has a unique solution, given the initial conditions. So, do you want to find the initial conditions such that all constraints are satisfied? In that case, you can probably make some headway analytically. The first constraint implies that $\dot{q}_1 = \dot{q}_2$ and $\ddot{q}_1 = \ddot{q}_2$ so $f_1(q_1,q_2) = f_2(q_1,q_2)$; that should simplify your problem.

Or, perhaps you already know that the constraints are satisfied, because they are a consequence of the differential equation (and initial conditions), and you want to make sure that the numerical solution also satisfies the constraint. That is studied in "Geometric Integration", and a good book is Hairer, Lubich & Wanner, Geometric Numerical Integration, Springer. The projection method that Sasha mentioned is one possibility, but in fact many methods (like Runge-Kutta) follow linear constraints automatically.

Or, perhaps your description is not complete, and you have for instance three unknown functions, described by two differential equations and one algebraic constraint. Such problems are called differential-algebraic equations (DAEs). One book on their numerical solution that I can recommend is: Ascher & Petzold, Computer methods for ordinary differential equations and differential-algebraic equations, SIAM, 1998.

-


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scroll identifier for mobile
main-content

## Über dieses Buch

This book constitutes the refereed proceedings of the 8th International RuleML Symposium, RuleML 2014, co-located with the 21st European Conference on Artificial Intelligence, ECAI 2014, held in Prague, Czech Republic, in August 2014.

The 17 full and 6 short papers presented together with 3 keynote talks were carefully reviewed and selected from 48 submissions. The papers cover the following topics: semantic web rule languages and standards, rule engines, formal and operational semantics and rule-based systems, the relation between natural language and rules, automation of business rules generation from existing data, and aspects related to legal rules and norms for web and corporate environments.

## Inhaltsverzeichnis

### Reaction RuleML 1.0 for Rules, Events and Actions in Semantic Complex Event Processing

Reaction RuleML is a standardized rule markup language for the representation and interchange of reaction rules. This paper gives an introduction to the core knowledge representation mechanisms of Reaction RuleML 1.0 such as multi-sorted signatures and their interpretation, action primitives for knowledge updates, interchange and testing, order-sorted external type systems and the Reaction RuleML metamodel, scopes and mode declarations, semantic profiles, imports of documents, modules and messages. These mechanisms form the basis for an adequate treatment of rules, events and actions, as needed in Semantic Complex Event Processing (SCEP), such as, interchange, translation and testing based on the intended semantics defined in semantic profiles; modularization and distribution of knowledge interfaces with their signatures defining, e.g., complex event detection patterns; closed scoped reasoning on top of scoped modules with dynamic constructive views on meta knowledge; transactional complex actions; conversation based message interchange for Question Answering (Q&A) and rule-based agent architectures such as RuleResponder, etc.

### A Logical Characterization of a Reactive System Language

Typical reactive system languages are programmed by means of rules of the form if antecedent then consequent. However, despite their seemingly logical character, hardly any reactive system languages give such rules a logical interpretation. In this paper, we investigate a simplified reactive system language KELPS, in which rules are universally quantified material implications, and computation attempts to generate a model that makes the rules true.
The operational semantics of KELPS is similar to that of other reactive system languages, and is similarly incomplete. It cannot make a rule true by making its antecedent false, or by making its consequent true whether or not its antecedent becomes true. In this paper, we characterize the reactive models computed by the operational semantics. Informally speaking, a model is reactive if every action in the model is an instance of an action in the consequent of a rule whose earlier conditions are true.

### On Using Semantically-Aware Rules for Efficient Online Communication

The ever growing number of communication channels not only enables a broader outreach for organizations, but also makes it more difficult for them to manage a very large number of channels and adapted content efficiently. Thus, finding the right channels to disseminate some content and adapting this content to specific channel requirements are real challenges for sharing information both efficiently and effectively. In this work, we present a rule-based system that addresses these challenges by decoupling the information to be shared from the actual channels where it is published. We propose semantic models to characterize and integrate various information sources and channels. A set of independent rules then interrelates these models, specifying the concrete publication workflow and content adaptation required. Furthermore, we evaluate our rule-based system using two different use cases, discussing the added value that the defined rules provide to this scenario and how they contribute to overcoming the identified challenges effectively.
Zaenal Akbar, José María García, Ioan Toma, Dieter Fensel

### Conceptual Model Interoperability: A Metamodel-driven Approach

Linking, integrating, or converting conceptual data models represented in different modelling languages is a common aspect in the design and maintenance of complex information systems. While such languages seem similar, they are known to be distinct and no unifying framework exists that respects all of their language features in either model transformations or inter-model assertions to relate them. We aim to address this issue using an approach where the rules are enhanced with a logic-based metamodel. We present the main approach and some essential metamodel-driven rules for the static, structural, components of ER, EER, UML v2.4.1, ORM, and ORM2. The transformations for model elements and patterns are used with the metamodel to verify correctness of inter-model assertions across models in different languages.
Pablo Rubén Fillottrani, C. Maria Keet

### On Verifying Reactive Rules Using Rewriting Logic

Rule-based programming has been gaining a lot of interest in the industry lately, through the growing use of rules to model the behavior of software systems. A demand for verifying and analyzing rule based systems has thus emerged. In this paper we propose a methodology, based on rewriting logic specifications written in CafeOBJ, for reasoning about structural errors of systems whose behavior is expressed in terms of reactive rules and verifying safety properties within the same framework. We present our approach through a simple but illustrative example of an e-commerce web site.
Katerina Ksystra, Nikos Triantafyllou, Petros Stefaneas

### Using Rules to Develop a Personalized and Social Location Information System for the Semantic Web

In this work, the design and implementation of an innovative context-aware location based social networking service is presented. The proposed system, called “Geosocial SPLIS”, utilizes Semantic Web technologies to deliver personalized information to the end user. It addresses some drawbacks of knowledge-based personalization systems and aims to provide a collaborative knowledge creation platform for other systems. To achieve this, it a) collects data from external sources such as Google Places API and Google+ b) adopts the schema.org ontology to represent people and places profiles, c) provides a web editor for adding rules (modeling user preferences and group-targeted place offers) at run time, d) uses RuleML and Jess rules to represent these rules, e) combines at run-time the above to match user context with up to date information, presented on Google Maps and f) matches user’s preferences with those of his/her nearby friends to present POI’s that are suitable to all of them. All data and rules are stored in the Sesame RDF triple store in order to be shared among various systems.

### Checking Termination of Logic Programs with Function Symbols through Linear Constraints

Enriching answer set programming with function symbols makes modeling easier, increases the expressive power, and allows us to deal with infinite domains. However, this comes at a cost: common inference tasks become undecidable. To cope with this issue, recent research has focused on finding trade-offs between expressivity and decidability by identifying classes of logic programs that impose limitations on the use of function symbols but guarantee decidability of common inference tasks. Despite the significant body of work in this area, current approaches do not include many simple practical programs whose evaluation terminates. In this paper, we present the novel class of rule-bounded programs. While current techniques perform a limited analysis of how terms are propagated from an individual argument to another, our technique is able to perform a more global analysis, thereby overcoming several limitations of current approaches. We also present a further class of cycle-bounded programs where groups of rules are analyzed together. We show different results on the correctness and the expressivity of the proposed techniques.
Marco Calautti, Sergio Greco, Cristian Molinaro, Irina Trubitsyna

### A Datalog + Plus RuleML 1.01 Architecture for Rule-Based Data Access in Ecosystem Research

Rule-Based Data Access (RBDA) enables automated reasoning over a knowledge base (KB) as a generalized global schema for the data in local (e.g., relational or graph) databases reachable through mappings. RBDA can semantically validate, enrich, and integrate heterogeneous data sources. This paper proposes an RBDA architecture layered on Datalog+ RuleML, and uses it for the ΔForest case study on the susceptibility of forests to climate change. Deliberation RuleML 1.01 was mostly motivated by Datalog customization requirements for RBDA. It includes Datalog+ RuleML 1.01 as a standard XML serialization of Datalog+, a superlanguage of the decidable Datalog±. Datalog+ RuleML is customized into the three Datalog extensions Datalog[∃], Datalog[=], and Datalog[$$\bot$$] through MYNG, the RuleML Modular sYNtax confiGurator generating (Relax NG and XSD) schemas from language-feature selections. The ΔForest case study on climate change employs data derived from three main forest monitoring networks in Switzerland. The KB includes background knowledge about the study sites and design, e.g., abundant tree species groups, pure tree stands, and statistical independence among forest plots. The KB is used to rewrite queries about, e.g., the eligible plots for studying a particular species group. The mapping rules unfold our newly designed global schema to the three given local schemas, e.g. for the grade of forest management. The RBDA/ΔForest case study has shown the usefulness of our approach to Ecosystem Research for global schema design and demonstrated how automated reasoning can become key to knowledge modeling and consolidation for complex statistical data analysis.
Harold Boley, Rolf Grütter, Gen Zou, Tara Athan, Sophia Etzold

### A Hybrid Diagnosis Approach Combining Black-Box and White-Box Reasoning

We study model-based diagnosis and propose a new approach of hybrid diagnosis combining black-box and white-box reasoning. We implemented and compared different diagnosis approaches including the standard hitting set algorithm and new approaches using answer set programming engines (DLV, Potassco) in the application of Euler/X toolkit, a logic-based toolkit for alignment of multiple biological taxonomies. Our benchmarks show that the new hybrid diagnosis approach runs about twice fast as the black-box diagnosis approach of the hitting set algorithm.
Mingmin Chen, Shizhuo Yu, Nico Franz, Shawn Bowers, Bertram Ludäscher

### Multi-valued Argumentation Frameworks

In this paper we explore how the seminal Dung’s abstract argumentation framework can be extended to handle arguments containing gradual concepts. We allow arguments to have a degree of truth associated with them and we investigate the degree of truth to which each argument can be considered accepted, rejected and undecided by an abstract argumentation semantics. We propose a truth-compositional recursive computation, and we discuss examples using the major multi-valued logics such as Godel’s, Zadeh’s and Łukasiewicz’s logic. The findings are a contribution in the field of non-monotonic approximate reasoning and they also represent a well-grounded proposal towards the introduction of gradualism in argumentation systems.
Pierpaolo Dondio

### Incomplete and Uncertain Data Handling in Context-Aware Rule-Based Systems with Modified Certainty Factors Algebra

Context-aware systems make use of contextual information to adapt their functionality to current environment state, or user needs and habits. One of the major problems concerning them is the fact, that there is no warranty that the contextual information will be available, nor certain at the time when the reasoning should be performed. This may be due to measurement errors, sensor inaccuracy, or semantic ambiguities of modeled concepts. Several approaches were developed to solve uncertainty in context knowledge bases, including probabilistic reasoning, fuzzy logic, or certainty factors. However, handling uncertainties in highly dynamic, mobile environments still requires more consideration. In this paper we perform comparison of application of different uncertainty modeling approaches to mobile context-aware environments. We also present an exemplary solution based on modified certainty factors algebra and logic-based knowledge representation for solving uncertainties caused by the imprecision of context-providers.
Szymon Bobek, Grzegorz J. Nalepa

### The Hardness of Revising Defeasible Preferences

Non-monotonic reasoning typically deals with three kinds of knowledge. Facts are meant to describe immutable statements of the environment. Rules define relationships among elements. Lastly, an ordering among the rules, in the form of a superiority relation, establishes the relative strength of rules. To revise a non-monotonic theory, we can change either one of these three elements. We prove that the problem of revising a non-monotonic theory by only changing the superiority relation is a NP-complete problem.
Guido Governatori, Francesco Olivieri, Simone Scannapieco, Matteo Cristani

### From Guidelines to Practice: Improving Clinical Care through Rule-Based Clinical Decision Support at the Point of Care

Healthcare Information Technology (HIT) is a dynamically evolving industry due to continuous advancements in healthcare technologies. This necessitates the availability of highly dynamic applications that accommodate frequent changes in business logic. The automation of Clinical Decision Support (CDS) in particular is most liable to changes in health business logic or rules. In terms of system’s architecture, there is a need to separate business logic and rules from the implementation/functionality of the Electronic Health Record (EHR) application, providing processes and rules as reusable components. We propose an architecture utilizing rule-based technologies to facilitate Decision Support to promptly adapt business logic changes, that are reflected immediately in application behavior. This allows real-time and robust CDS for the physician at point of care. Our rule-based implementation (Business Process Modelling Notation (BPMN)+Rules) was successfully used to emulate Clinical workflows, using as an example, the NICE Lung Cancer Clinical Guideline (CG121) as a test scenario.
Ayesha Aziz, Salvador Rodriguez, Chris Chatwin

### Requirement Compound Mining and Analysis

In this paper, we motivate and develop the linguistic characteristics of requirement compounds which are major types of business rules. The discourse structures that further refine or elaborate requirements are also analyzed. An implementation is then presented. It is carried out in Dislog on the <TextCoop> platform. Dislog allows high level specifications in logic that allow fast and easy prototyping at a high level of linguistic adequacy. Elements of an indicative evaluation are provided.
Juyeon Kang, Patrick Saint-Dizier

### Semi-automated Vocabulary Building for Structured Legal English

Structured English has been applied as computational independent language for defining business vocabularies and business rules, e.g., in the context of OMG’s Semantics and Business Vocabulary Representation (SBVR). It allows non-technical domain experts to engineer knowledge in natural language, but with an underlying semi-formal semantics which eases the automation of machine transformation into formal knowledge representations and logic-based machine interpretation. We adapt this approach to the legal domain in order to support legal domain experts in their task to build legal vocabularies and legal rules in Structured English from legal texts. In this paper we contribute with a semi-automated vocabulary and rule development process which is supported by automated suggestions of legal concepts computed by a semantic legal text analysis. We implement a proof-of-concept in the KR4IPLaw tool, which enables legal domain experts to represent their knowledge in Structured English. We evaluate the proposed approach on the basis of use cases in the domain of IP and patent law.

### Basics for a Grammar Engine to Verbalize Logical Theories in isiZulu

The language isiZulu is the largest in South Africa by numbers of first language speakers, yet, it is still an underresourced language. In this paper, we approach the grammar piecemeal from a natural language generation approach, and viewed from a potential utility for verbalizing OWL ontologies as a tangible use case. The elaborate rules of the grammar show that a grammar engine and dictionary is essential even for basic verbalizations in OWL 2 EL. This is due to, mainly, the 17 noun classes with embedded semantics and the agglutinative nature of isiZulu. The verbalization of basic constructs requires merging a prefix with a noun and distinguishing an ‘and’ between a list and linking clauses.
C. Maria Keet, Langa Khumalo

### Formal Rule Representation and Verification from Natural Language Requirements Using an Ontology

The development of a system is usually based on shared and accepted requirements. Hence, to be largely understood by the stakeholders, requirements are often written in natural language (NL). However, checking requirements completeness and consistency requires having them in a formal form. In this article, we focus on user requirements describing a system behaviour, i.e. its behavioural rules. We show how to transform behavioural rules identified from NL requirements and represented within an OWL ontology into the formal specification language Maude. The OWL ontology represents the generic behaviour of a system and allow us to bridge the gap between informal and formal languages and to automate the transformation of NL rules into a Maude specification.
Driss Sadoun, Catherine Dubois, Yacine Ghamri-Doudane, Brigitte Grau

### Learning Business Rules with Association Rule Classifiers

The main obstacles for a straightforward use of association rules as candidate business rules are the excessive number of rules discovered even on small datasets, and the fact that contradicting rules are generated. This paper shows that Association Rule Classification algorithms, such as CBA, solve both these problems, and provides a practical guide on using discovered rules in the Drools BRMS and on setting the ARC parameters. Experiments performed with modified CBA on several UCI datasets indicate that data coverage rule pruning keeps the number of rules manageable, while not adversely impacting the accuracy. The best results in terms of overall accuracy are obtained using minimum support and confidence thresholds. Disjunction between attribute values seem to provide a desirable balance between accuracy and rule count, while negated literals have not been found beneficial.
Tomáš Kliegr, Jaroslav Kuchař, Davide Sottara, Stanislav Vojíř

### Interpreting Web Shop User’s Behavioral Patterns as Fictitious Explicit Rating for Preference Learning

We consider applications of user preference rule learning in marketing. We chose rules because of human-understandability. We chose fuzzy logic because it enables to order items for recommendation. In this paper we introduce a rule based system equivalent to the Fagin-Lotem-Naor preference system. We show a multi-user version, introduce induction and compare it to several methods for learning user preference. The methods are based, first, on interpreting e-shop user’s behavioral patterns collected by scripts as fictitious explicit rating. After this we use this (fictitious) explicit rating for content based preference learning.
Our main motivation is on recommending for small or medium-sized e-commerce portals. Due to high competition, users of these portals are not too loyal and e.g. refuse to register or provide any/enough explicit feedback. Furthermore, products such as tours, cars or furniture have very low average consumption rate preventing us from tracking unregistered user between two consecutive purchases. Recommending on such domains proves to be very challenging, yet interesting research task. As a test bed, we have conducted several off-line experiments with real user data from travel agency website confirming competitiveness of our method.

### Learning Association Rules from Data through Domain Knowledge and Automation

An approach to automated data mining with association rules based on domain knowledge is introduced. Association rules are understood as interesting pairs of general Boolean attributes. Items of domain knowledge corresponding to various relations of non-Boolean attributes are used to formulate reasonable analytical questions. Particular items of knowledge are mapped to sets of association rules which can be considered their consequences. The sets of consequences are then used to interpret sets of association rules resulting from a data mining procedure.
Jan Rauch, Milan Šimůnek

### Using Discriminative Rule Mining to Discover Declarative Process Models with Non-atomic Activities

Process discovery techniques try to generate process models from execution logs. Declarative process modeling languages are more suitable than procedural notations for representing the discovery results deriving from logs of processes working in dynamic and low-predictable environments. However, existing declarative discovery approaches aim at mining declarative specifications considering each activity in a business process as an atomic/instantaneous event. In spite of this, often, in realistic environments, process activities are not instantaneous; rather, their execution spans across a time interval and is characterized by a sequence of states of a transactional lifecycle. In this paper, we investigate how to use discriminative rule mining in the discovery task, to characterize lifecycles that determine constraint violations and lifecycles that ensure constraint fulfillments. The approach has been implemented as a plug-in of the process mining tool ProM and validated on synthetic logs and on a real-life log recorded by an incident and problem management system called VINST in use at Volvo IT Belgium.
Mario Luca Bernardi, Marta Cimitile, Chiara Di Francescomarino, Fabrizio Maria Maggi

### Modeling Obligations with Event-Calculus

Time plays an important role in norms. In this paper we start from our previously proposed classification of obligations, and point out some shortcomings of Event Calculus (EC) to represent obligations. We propose an extension of EC that avoids such shortcomings and we show how to use it to model the various types of obligations.
Mustafa Hashmi, Guido Governatori, Moe Thandar Wynn

### A Process for Knowledge Transformation and Knowledge Representation of Patent Law

Automated support to model and reason based on such modeled legal norms using expert systems, for its use scenarios such as court-fillings or argumentation has increasingly become a subject of interest in last few decades. The core problem in all such automation is removing the vagueness embedded within legal texts/sections and this vagueness is due to the pragmatics involved. As of today, we believe, it is impossible for a system to handle any such problems dealing with legal pragmatics. This work proposes a process which acts a bridge between a legal practitioner can and a knowledge modeler wherein, a legal practitioner provides the legal information pertaining to a section in a simpler form as required by the modeler. We also propose several knowledge representation formats to represent the information at each layer of the proposed process. Additionally during the course of the paper, we propose a mapping scheme from legal norms in natural language format to Controlled Natural Language (CNL) format and finally to a platform independent rule representation format.

### Legal Responsibility for the Acts of Others: A Logical Analysis

This paper offers a logical analysis of two cases where legal responsibility may emerge for the acts of others: (a) reflex responsibility, and (b) responsibility in the negotiorum gestio doctrine. The current contribution works within a fresh multi-modal system where the new operators are introduced for denoting intentions and actions in the interest of other agents, and the objectively ideal sets of actions for agents.
Clara Smith, Erica Calardo, Antonino Rotolo, Giovanni Sartor

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# Relaxation and optimization for linear-growth convex integral functionals under PDE constraints

created by arroyorabasa on 07 Feb 2017

[BibTeX]

Submitted Paper

Inserted: 7 feb 2017
Last Updated: 7 feb 2017

Year: 2016

Abstract:

We give necessary and sufficient conditions for minimality of generalized minimizers for linear-growth functionals of the form $\mathcal F[u] = \int_\Omega f(x,u(x)) \, \text{d}x, \quad u: \Omega \subset \mathbb R^d \to \mathbb R^N$ where u is an integrable function satisfying a general PDE constraint. Our analysis is based on two ideas: a relaxation argument into a subspace of the space of bounded vector-valued Radon measures $\mathcal M(\Omega;\mathbb R^N)$, and the introduction of a set-valued pairing in $\mathcal M(Ω;\mathbb R^N) \times {\rm L}^\infty(\Omega;\mathbb R^N)$. By these means we are able to show an intrinsic relation between minimizers of the relaxed problem and maximizers of its dual formulation also known as the saddle-point conditions. In particular, our results can be applied to relaxation and minimization problems in ${\rm BV, BD}$.


text:
Bifurcation theory

Bifurcation theory is the mathematical study of changes in the qualitative or topological structure of a given family. Examples of such families are the integral curves of a family of vector fields or, the solutions of a family of differential equations. Most commonly applied to the mathematical study of dynamical systems, a bifurcation occurs when a small smooth change made to the parameter values (the bifurcation parameters) of a system causes a sudden 'qualitative' or topological change in its behaviour. Bifurcations occur in both continuous systems (described by ODEs, DDEs or PDEs), and discrete systems (described by maps).

Types of bifurcation

It is useful to divide bifurcations into two principal classes:
* Local bifurcations, which can be analysed entirely through changes in the local stability properties of equilibria, periodic orbits or other invariant sets as parameters cross through critical thresholds; and
* Global bifurcations, which often occur when larger invariant sets of the system 'collide' with each other, or with equilibria of the system. They cannot be detected purely by a stability analysis of the equilibria (fixed points).

Local bifurcations

A local bifurcation occurs when a parameter change causes the stability of an equilibrium (or fixed point) to change. In continuous systems, this corresponds to the real part of an eigenvalue of an equilibrium passing through zero. In discrete systems (those described by maps rather than ODEs), this corresponds to a fixed point having a Floquet multiplier with modulus equal to one. In both cases, the equilibrium is "non-hyperbolic" at the bifurcation point.The topological changes in the phase portrait of the system can be confined to arbitrarily small neighbourhoods of the bifurcating fixed points by moving the bifurcation parameter close to the bifurcation point (hence 'local').

More technically, consider the continuous dynamical system described by the ODE:$dot x=f\left(x,lambda\right)quad f:mathbb\left\{R\right\}^n imesmathbb\left\{R\right\} ightarrowmathbb\left\{R\right\}^n.$A local bifurcation occurs at $\left(x_0,lambda_0\right)$ if the Jacobian matrix$extrm\left\{d\right\}f_\left\{x_0,lambda_0\right\}$has an eigenvalue with zero real part. If the eigenvalue is equal to zero, the bifurcation is a steady state bifurcation, but if the eigenvalue is non-zero but purely imaginary, this is a Hopf bifurcation.

For discrete dynamical systems, consider the system:$x_\left\{n+1\right\}=f\left(x_n,lambda\right),.$Then a local bifurcation occurs at $\left(x_0,lambda_0\right)$ if the matrix$extrm\left\{d\right\}f_\left\{x_0,lambda_0\right\}$has an eigenvalue with modulus equal to one. If the eigenvalue is equal to one, the bifurcation is either a saddle-node (often called fold bifurcation in maps), transcritical or pitchfork bifurcation. If the eigenvalue is equal to -1, it is a period-doubling (or flip) bifurcation, and otherwise, it is a Hopf bifurcation.

Examples of local bifurcations include:

* Transcritical bifurcation
* Pitchfork bifurcation
* Period-doubling (flip) bifurcation
* Hopf bifurcation
* Neimark (secondary Hopf) bifurcation

Global bifurcations

Global bifurcations occur when 'larger' invariant sets, such as periodic orbits, collide with equilibria. This causes changes in the topology of the trajectories in the phase space which cannot be confined to a small neighbourhood, as is the case with local bifurcations. In fact, the changes in topology extend out to an arbitrarily large distance (hence 'global').

Examples of global bifurcations include:

* Homoclinic bifurcation in which a limit cycle collides with a saddle point.
* Heteroclinic bifurcation in which a limit cycle collides with two or more saddle points.
* Infinite-period bifurcation in which a stable node and saddle point simultaneously occur on a limit cycle.
* Blue sky catastrophe in which a limit cycle collides with a nonhyperbolic cycle.

Global bifurcations can also involve more complicated sets such as chaotic attractors.

Codimension of a bifurcation

The codimension of a bifurcation is the number of parameters which must be varied for the bifurcation to occur. This corresponds to the codimension of the parameter set for which the bifurcation occurs within the full space of parameters. Saddle-node bifurcations are the only generic local bifurcations which are really codimension-one (the others all having higher codimension). However, often transcritical and pitchfork bifurcations are also often thought of as codimension-one, because the normal forms can be written with only one parameter.

An example of a well-studied codimension-two bifurcation is the Bogdanov-Takens bifurcation.

ee also

* Bifurcation diagram
* Catastrophe theory
* Feigenbaum constant
* Phase portrait

References

* [http://monet.physik.unibas.ch/~elmer/pendulum/nldyn.htm Nonlinear dynamics]
* [http://www.egwald.ca/nonlineardynamics/bifurcations.php Bifurcations and Two Dimensional Flows] by Elmer G. Wiens
* [http://prola.aps.org/abstract/RMP/v63/i4/p991_1 Introduction to Bifurcation theory] by John David Crawford

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Look at other dictionaries:

• bifurcation theory — noun A branch of mathematics concerned with dynamical systems which suffer sudden qualitative changes from an infinitesimal change in a parameter …   Wiktionary

• Bifurcation — means the splitting of a main body into two parts.Bifurcation or Bifurcated may refer to:*Bifurcation (law), the division of issues in a trial for example the division of a page into two parts. *Bifurcation theory, the study of bifurcation in… …   Wikipedia

• Bifurcation diagram — In mathematics, particularly in dynamical systems, a bifurcation diagram shows the possible long term values (equilibria/fixed points or periodic orbits) of a system as a function of a bifurcation parameter in the system. It is usual to represent …   Wikipedia

• bifurcation — noun /ˌbaɪfəˈkeɪʃən,ˌbaɪfɚˈkeɪʃən/ a) A division into two branches. b) Any place where one thing divides into two. Syn: branching, fork, forking See Also: bifurcate …   Wiktionary

• Catastrophe theory — This article refers to the study of dynamical systems. For other meanings, see catastrophe. In mathematics, catastrophe theory is a branch of bifurcation theory in the study of dynamical systems; it is also a particular special case of more… …   Wikipedia

• Chaos theory — This article is about chaos theory in Mathematics. For other uses of Chaos theory, see Chaos Theory (disambiguation). For other uses of Chaos, see Chaos (disambiguation). A plot of the Lorenz attractor for values r = 28, σ = 10, b = 8/3 …   Wikipedia

• Bogdanov-Takens bifurcation — In bifurcation theory, a field within mathematics, a Bogdanov Takens bifurcation is a well studied example of a bifurcation with co dimension two, meaning that two parameters must be varied for the bifurcation to occur. It is named after R. I.… …   Wikipedia

• Hopf bifurcation — In bifurcation theory a Hopf or Andronov Hopf bifurcation is a local bifurcation in which a fixed point ofa dynamical system loses stability as a pair of complex conjugate eigenvalues of the linearization around the fixed point crossthe imaginary …   Wikipedia

• Pitchfork bifurcation — In bifurcation theory, a field within mathematics, a pitchfork bifurcation is a particular type of local bifurcation. Pitchfork bifurcations, like Hopf bifurcations have two types supercritical or subcritical. In flows, that is, continuous… …   Wikipedia

• Saddle-node bifurcation — In the mathematical area of bifurcation theory a saddle node bifurcation or tangential bifurcation is a local bifurcation in which two fixed points (or equilibria) of a dynamical system collide and annihilate each other. The term saddle node… …   Wikipedia


text:
The first 300 rows belong to the database A, while the next 400 rows belong to the database B. Five covariates: Gender, Treatment, Dosage, Smoking and Age are common to both databases (same encodings). Gender is the only complete covariate. The variables Yb1 and Yb2 are the target variables of A and B respectively, summarizing a same information encoded in two different scales. that summarize a same information saved in two distinct encodings, that is why, Yb1 is missing in the database B and Yb2 is missing in the database A.

simu_data

## Format

A data.frame made of 2 overlayed databases (A and B) with 700 observations on the following 8 variables.

DB

the database identifier, a character with 2 possible classes: A or B

Yb1

the target variable of the database A, stored as factor and encoded in 3 ordered levels: [20-40], [40-60[,[60-80] (the values related to the database B are missing)

Yb2

the target variable of the database B, stored as integer (an unknown scale from 1 to 5) in the database B (the values related to A are missing)

Gender

a factor with 2 levels (Female or Male) and no missing values

Treatment

a covariate of 3 classes stored as a character with 2% of missing values: Placebo, Trt A, Trt B

Dosage

a factor with 4 levels and 5% of missing values: from Dos 1 to dos 4

Smoking

a covariate of 2 classes stored as a character and 10% of missing values: NO for non smoker, YES otherwise

Age

a numeric corresponding to the age of participants in years. This variable counts 5% of missing values

## Source

randomly generated

## Details

The purpose of the functions contained in this package is to predict the missing information on Yb1 and Yb2 in database A and database B using the Optimal Transportation Theory.

Missing information has been simulated to some covariates following a simple MCAR process.


text:
## Assignment 3: In-core performance, cache hierarchy

1. Dense MVM. The following loop nest multiplies a matrix a[][] with a vector b[] and stores the result in a vector c[]:

for(i=0; i<N; ++i)   for(j=0; j<N; ++j)    c[i] += a[i][j] * b[j];

You can assume that N is "large" (the matrix does not fit into any cache), and that all data in c, a, and b are double-precision floating-point numbers. This serial code is run on a quad-core processor with cache sizes of 32 KiB (per-core L1), 256 KiB (per-core L2), and 8 MiB (shared L3), a peak performance of 4 GFlop/s (ADD+MULT) per core, and a memory bandwidth of 16 GB/s. Apart from one multiply and one add instruction, a core can execute one load or one store instruction per cycle (throughput). There is no SIMD capability. The ADD instruction has a latency of four cycles, and the MULT instruction has a latency of six cycles.

(a) (5 crd) Identify spatial and temporal access locality in this code. Which data structures lead to which locality of access? How does this depend on N?

(b) (10 crd) Calculate the code balance with respect to the matrix size for all caches and for main memory. You can assume that the matrix does not fit into any cache (i.e., $$8\times N^2$$ is much larger than any cache).

2. An intricate stencil code. (20 crd) Predict the maximum in-L1 performance $$P_\mathrm{max}$$ of the following loop nest on an Ivy Bridge and a Haswell core in flops/cycle (assuming double-precision arithmetic):

for(int k=4; k < N-4; k++) {
for(int j=4; j < N-4; j++) {
for(int i=4; i < N-4; i++) {
U[k][j][i] = 2*V[k][j][i] - U[k][j][i] + C[k][j][i] * ( c0 *  V[k][j][i]
+c1 * (V[ k ][ j ][i+1]+V[ k ][ j ][i-1] +V[ k ][j+1][ i ]+V[ k ][j-1][ i ]
+V[k+1][ j ][ i ]+V[k-1][ j ][ i ]) +c2 * (V[ k ][ j ][i+2]+V[ k ][ j ][i-2]
+V[ k ][j+2][ i ]+V[ k ][j-2][ i ] +V[k+2][ j ][ i ]+V[k-2][ j ][ i ])
+c3 * (V[ k ][ j ][i+3]+V[ k ][ j ][i-3] +V[ k ][j+3][ i ]+V[ k ][j-3][ i ]
+V[k+3][ j ][ i ]+V[k-3][ j ][ i ]) +c4 * (V[ k ][ j ][i+4]+V[ k ][ j ][i-4]
+V[ k ][j+4][ i ]+V[ k ][j-4][ i ] +V[k+4][ j ][ i ]+V[k-4][ j ][ i ]));
}
}
}

Consider AVX(2) and scalar execution on both architectures and identify the relevant execution bottleneck. For HSW you can assume that any ADD or MULT is actually carried out as an FMA instruction.

3. Balance. Calculate the in-memory code balance for loops with the following loop bodies, assuming that all arrays do not fit into any cache (a loop over i is always implied):

(a) (5 crd) s = s + a[i];     (double precision)
(b) (5 crd) s = s + a[i]*b[i]; (double precision)
(c) (5 crd) a[i] = b[i] + s*c[i]; (single precision)
(d) (5 crd) a[i] = a[i] + s*c[i]; (single precision)
(e) (15 crd) y[i] = y[i] + x[i] * v[index[i]];  (DP for x[],y[], and v[], and int32 for index[])

In case (e) you have to be a little imaginative; obviously it is impossible to give a single, definite answer...

4. Optimizing for code balance. Suppose you have a code like this:

for(i=0; i<N; ++i) {
a[i] = b[i] * c[i];
}
for(i=0; i<N-1; ++i) {
b[i] = a[i+1] * 0.5;
}

All arrays hold DP floating-point numbers, and N is "large".

(a) (10 crd) Suggest an optimization that will improve the performance of the code. What is the expected change in the memory code balance? Discuss if the optimized code is SIMD vectorizable.
(b) (20 crd) Construct a single-core performance model (along the lines of what we did in the lecture with the vector triad) for the optimized code on an Intel Haswell core. Calculate the expected performance in Gflop/s and the expected memory bandwidth in Gbyte/s for an in-memory data set. You can assume that the compiler generates separate load instructions for loads to successive elements, e.g., a[i] and a[i+1].


text:
# generalized universal coefficient sequence

Take the familiar Universal Coefficient Theorem for ordinary homology with $\mathbb{Z}$-coefficients and ordinary cohomology with coefficients in some abelian group $A$:$$0\rightarrow \text{Ext}_\mathbb{Z}^1(H_{i-1}(X;\mathbb{Z}),A)\rightarrow H^i(X;A)\rightarrow \text{Hom}_\mathbb{Z}(H_i(X;\mathbb{Z}),A)\rightarrow 0$$This exact sequence can be rewritten in the language of topological spectra:$$0\rightarrow\text{ext}_{H\mathbb{Z}}^1([\Sigma^{i-1}S,H\mathbb{Z}\wedge X],HA)\rightarrow [X,\Sigma^iHA]\rightarrow [[\Sigma^iS,H\mathbb{Z}\wedge X],HA]\rightarrow 0$$where $[-,-]$ denotes the internal hom $\text{hom}_{H\mathbb{Z}}(-,-)$ of $H\mathbb{Z}$-module spectra. (I am confused about some basic points [see my question], but I presume that $\text{ext}$ makes sense in this context.)

How can one generalize this sequence to generalized (co)homology theories? One guess is to replace $H\mathbb{Z}$ with some commutative ring spectrum $E$ and $HA$ with an $E$-module spectrum $F$. I imagine this guess is far too ambitious and a more conservative theorem is the correct generalization.

• See for example Adams' Lectures on Generalized Cohomology, in Volume 1 of his collected works. Sep 5, 2015 at 21:11
• @AlexTurzillo combine the classical UCSS with the Atiyah-Hirzebruch spectral sequence. Sep 5, 2015 at 21:33

There is more than one possible generalization. The most common is the universal coefficient spectral sequence. Given a (homotopy) commutative ring spectrum $E$ and a spectrum $X$, there is under certain conditions a spectral sequence $$Ext^{p,q}_{E_*}(E_*(X), E_*) \Rightarrow E^{q-p}(X)$$ This is true for example if

• $E$ is an $A_\infty$-ring spectrum (e.g. if $E =ko, ku, KO, KU, TMF, MO, MSO, MSpin \dots$) [EKMM, IV.4]
• $E$ is even and Landweber exact (e.g. if $E = MU, E(n), E_n, \dots$) [Adams' lectures on generalized cohomology, which Peter alluded to, and Devinatz: Morava Modules and Brown-Comenetz Duality, Prop 1.3, and the discussion thereafter]

Sometimes, this spectral sequence is not extremely useful though. For example, take $E = KO$. In general, $KO_*X$ might have infinite cohomological dimension over $KO_*$ so that the spectral sequence might be difficult to control. In this case another perspective is more useful: Anderson duality.

Consider the functor $E \mapsto Hom(\pi_*E, \mathbb{Q}/\mathbb{Z})$ from the homotopy category of spectra to graded abelian groups. As $\mathbb{Q}/\mathbb{Z}$ is injective, this is a cohomological functor, by Brown representability represented by a spectrum $I_{\mathbb{Q}/\mathbb{Z}}$. There is an evident map $H\mathbb{Q} \to I_{\mathbb{Q}/\mathbb{Z}}$ whose fiber we denote by $I$. For a spectrum $E$, we define its Anderson dual $IE$. to be the function spectrum $F(E, I)$. It is easy to show that we get for every spectrum $X$ a short exact sequence $$0 \to Ext^1_{\mathbb{Z}}(E_{k-1}X, \mathbb{Z}) \to (IE)^kX \to Hom_{\mathbb{Z}}(E_kX, \mathbb{Z}) \to 0.$$ That means that there exists always a short exact sequence computing from $E$-homology the $IE$-cohomology. This is, of course, only useful if we can identify $IE$. Luckily, this has been done for a few spectra:

• $IH\mathbb{Z} \simeq H\mathbb{Z}$
• $IKU \simeq KU$
• $IKO \simeq \Sigma^4 KO$ [see e.g. Heard, Stojanoska]
• $ITmf \simeq \Sigma^{21}Tmf$ (at least at primes $>2$) [see Stojanoska]

For example, for $KO$ this means that we get a universal coefficient sequence $$0 \to Ext^1_{\mathbb{Z}}(KO_{k-1}X, \mathbb{Z}) \to KO^{k+4}X \to Hom_{\mathbb{Z}}(KO_kX, \mathbb{Z}) \to 0.$$