# Search results with tag "Opencourseware"

### THE SHELL **MODEL** - **MIT OpenCourseWare**

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THE SHELL **MODEL** 22.02 Introduction To Applied Nuclear Physics Spring 2012 1. Atomic Shell **Model ... Dy** 50 82: 126 28 20 8: Nucleon number S: 2p (MeV) 4 3 2 1 0-1-2-3-4-5 5 0 50 100 150: 208: Pb: 114 184: W Ca: 64: Ni: 38: Ar: 14: C: 132: Te: 86: Kr: 102: Mo 50 82: 126 28 20 8: Image by **MIT OpenCourseWare**. After Krane.

### Lecture 3: Signals and systems: part II - **MIT OpenCourseWare**

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The **essen-tial** idea, however, as discussed in Section 3.7 of the text, is that the important aspect of these functions, in particular of the impulse, is not what its value is at each instant of time but how it behaves under integration. Signals and Systems 3-2

**Periodic Table of** the Elements - **MIT OpenCourseWare**

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**Hf** Hafnium 178.49 6.8251 40 Zr Zirconium 91.224 6.6339 39 Y Yttrium 88.90585 6.2173 38 Sr Strontium 87.62 5.6949 56 Ba Barium 137.327 5.2117 73 Ta Tantalum 180.9479 7.5496 54 Xe Xenon 131.293 12.1298 19 K Potassium 39.0983 4.3407 20 Ca Calcium 40.078 6.1132 21 Sc Scandium 44.955910 6.5615 22 Ti Titanium 47.867 6.8281 30 Zn Zinc 65.409 9.3942 31 ...

### Interactions of Photons with Matter - **MIT OpenCourseWare**

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In **Compton** scattering, the incoming gamma-ray **photon** is deflected through an angle θ with respect to its original direction. The **photon** transfers a portion of its energy to the electron (assumed to be initially at rest), which is then known as a recoil electron, or a **Compton** electron. • All angles of scattering are possible.

### Lecture 6: **Genome Assembly** - **MIT OpenCourseWare**

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Efficient de novo assembly of large **genomes** using compressed data structures Jared T Simpson and Richard Durbin Genome Res. 2012. 22: 549-556 SGA algorithm excludes redundant (transitive) edges

### Free **Surface Water** Waves - **MIT OpenCourseWare**

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Therefore the **dynamic** pressure for all depths becomes px z t ) =ρηg (x t , ) cosh[ kz ( +H )] d ( ,, cosh(kH ) (7.39) V. Motion of Fluid Particles below a Wave We can define the motion of fluid particles underneat h a linear progressive wave to have a horizontal motion,ζp and a vertical motion, ηp, such that

**Lecture 8: Hashing I** - **MIT OpenCourseWare**

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**Lecture 8 Hashing I** 6.006 Fall **2011**. Simple Uniform Hashing: An assumption (cheating): Each key is equally likely to be hashed to any slot of table, independent of where other keys are hashed. letn = # keys stored in table m = # slots in table load factor = **n**=m= expected # keys per slot = expected length of a chain. Performance

### Lecture 4 Notes: Arrays and Strings - **MIT OpenCourseWare**

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String **literals** such as “Hello, world!” are actually represented by C++ as a sequence of characters in memory. In other words, a string is simply a character array and can be manipulated as such. Consider the following program: 1 #include <iostream> 2 using namespace std; …

### 18.445 HOMEWORK 4 SOLUTIONS - **MIT OpenCourseWare**

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18.445. HOMEWORK 4 SOLUTIONS variables X and Y are said to be independent conditionally on A is for every non-negative measurable

### Feedback Linearization - **MIT OpenCourseWare**

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Oct 29, 2003 · **Department** of Electrical Engineering and **Computer Science** 6.243j (Fall 2003): DYNAMICS OF NONLINEAR SYSTEMS by A. Megretski Lecture 13: Feedback Linearization1 Using control authority to transform nonlinear models into linear ones is one of the most commonly used ideas of practical nonlinear control design. Generally, the trick helps one

**Practice Right Hand Rule** #1 - **MIT OpenCourseWare**

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**Practice Right Hand Rule** #2 Remember:F v B G GG B =q × What direction is the force on a positive charge when entering a uniform B field in the direction indicated? 1) up 2) down 3) left 4) right 5) into page 6) out of page 7) there is no net force q v B

**Paper 1: An Analysis of** Hart’s ... - **MIT OpenCourseWare**

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Secondary rules on the other hand, set up the procedures **through** which primary rules can be introduced, modified, or enforced. Secondary rules can be thought of as rules about the rules (Hart, 76). Continuing with our football **metaphor**, an example of …

**Area of Part of a Circle** - **MIT OpenCourseWare**

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**Area** = y dx. This is awkward, because near the end the height of the region changes from a constant y = b to the height of the circle y = √ a2 − x2. What if we integrate with respect to y? That seems to work better; there is a single simple expression for the **length** of each horizontal strip: x = a2 − y2. b **Area** = x dy 0 b = 0 a2 − y2 dy

### Transportation Management - **MIT OpenCourseWare**

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**Intermodal** 1% Pipeline 4% Rail 5% Barge 1% Trucking By Sub-Mode Private , 46% Truckload, 44% LTL, 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1975 1987 1999 2003 Trucking Rail Air Freight Barge Note that these modes are all technology based – ... Develop detailed **rules** and relationships

### The Binomial Distribution - **MIT OpenCourseWare**

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**Excel** Calculates Binomial Probabilities Use the function wizard icon or the Insert_Function Command to choose ... **Calculations** shown for Binomial (n=3, p=0.3) = 0.794 Note: this is equivalent to counting success = 1 and failure = 0. 15.063 Summer 2003 1010 Another example:

### Fundamentals of **Lean** - **MIT OpenCourseWare**

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**Lean Enterprise** Value: The Central Concept **Lean** is a process of eliminating waste with the goal of creating value for **enterprise** stakeholders. **Lean Enterprise** Value, Murman et al ... **Small** & fragmented market, depleted workforce, scarce natural resources, little capital

### MOSFET **Equivalent Circuit** Models - **MIT OpenCourseWare**

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Oct 18, 2005 · **2L** µnCox(VGS −VT) 2[1 +λ(VDS −VDSsat)] Then: go = ∂ID ∂VDS | Q = W **2L** µnCox(VGS −VT) 2λ ' λI D ∝ ID L Output resistance is inverse of output conductance: ro = 1 go ∝ L ID VT VGS go 0 0 saturation cut-off ID go 0 0 saturation

### Relative Motion using Rotating Axes - **MIT OpenCourseWare**

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x y z is the time derivative of the **vector** V as seen by the rotating frame. The expression (5) above is known as Coriolis’ theorem. Given an arbitrary **vector**, it relates the derivative of that **vector** as seen by a ﬁxed frame with the derivative of the same **vector** as seen by a rotating frame. Symbolically, we can write, ( ˙ ) xyz = (˙ ) x y

### Lecture 17: Interpolation - **MIT OpenCourseWare**

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lates between sample points by holding each sample value until the next **sam-pling** instant. This generates a staircase-like approximation to the original sig-nal. Linear interpolation, also commonly referred to as a first-order hold, corresponds to connecting the sample points by straight line segments. Both

### Natural frequency and **damping** - **MIT OpenCourseWare**

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13. Natural frequency and **damping** ratio There is a standard, and useful, normalization of the second order homogeneous **linear** constant coeﬃcient ODE mx¨+ bx˙ + kx = 0 under the assumption that both the “mass” m and the “spring con stant” k are positive. It is illustrated in the Mathlet **Damping** Ratio.

### Lecture 9 - **MOSFET** (I) - **MIT OpenCourseWare**

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Oct 06, 2005 · the current-voltage **characteristics** of a **MOSFET**? 6.012 - Microelectronic Devices and Circuits - Fall 2005 Lecture 9-3 1. **MOSFET**: layout, cross-section, symbols source gate body drain inversion layer gate oxide channel polysilicon gate p p n n p+ n+ n+ n+ p +n n+ n n+ gate length g a t e w i d t h STI edge

### First-Order Logic - **MIT OpenCourseWare**

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**talk** about things, and so there's a new kind of syntactic element. There's a new kind of syntactic element called a term. And the term, as we'll see when we do the semantics, is a name for a thing. It's an expression that somehow names a thing in …

### 18.03SCF11 text: Complex Eigenvalues - **MIT OpenCourseWare**

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**1** + i x 2 is a solution, we have (x **1** + i x 2) = A (x **1** + i x 2) = Ax **1** + i Ax 2. Equating real and imaginary parts of this equation, x **1** = Ax, x 2 = Ax 2, which shows exactly that the real vectors x **1** and x 2 are solutions to x = Ax. Example. Find the corresponding two real solutions to …

### Probability mass function (PMF) - **MIT OpenCourseWare**

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We **assu** e ~]xi Px(x) < oo X . Expec a ·on of a Ber o Iii r.v X= 1, 0, w.p. P w.p 1 - p If X is the indicator of an event A, X IA : xpec ation of a ·rorm r v. • nifor on0,1, ... ,n Px(x) ~ 1 n+l 0 1 E[X •••••• n X X . Expectation as a population average • n students ...

**Time Series Analysis** I - **MIT OpenCourseWare**

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Useful **models** of covariance stationary **time series** have. Modest nite values of p and/or include. Moving average **models** depending on a parsimonious number of parameters. MIT 18.S096. **Time Series Analysis Time Series Analysis**. Stationarity and Wold Representation Theorem

### Tissue Repair, Fibrosis, and Healing - **MIT OpenCourseWare**

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Proteoglycans and **Hyaluronan**: Hydrated Gels Proteoglycans have a core of protein to which glycosaminoglycans are attached Glycoproteins are globular proteins with branched monosaccharide chains Proteoglycans such as syndecan can be transmembrane proteins with ligand binding capacity.

### Problem Set 1 Solutions - **MIT OpenCourseWare**

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**recurrence** becomes **S**(n) = **S** ... Solution: **Notice** that the x-coordinates of the vertices form a unimodal array and we can use part (a) to ﬁnd the vertex with the maximum x-coordinate inΘ(lgn) time. (c) Give an algorithm to ﬁnd the vertex with the maximum y …

**Negotiation**: Theory and Practice - **MIT OpenCourseWare**

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Conflict and Conflict **Management**. in The Handbook of Industrial and Organizational Psychology. Edited by Marvin Dunnette. Chicago, IL: Rand McNally, 1976. Prof. Mary P. Rowe—**MIT**, Cambridge, MA 02139 8 of 44

### Chapter 6 - **Water Waves** - **MIT OpenCourseWare**

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Chapter 6 - **Water Waves** 6.**1** Exact (Nonlinear) **Governing Equations** for Surface Gravity **Waves**, Assuming Potential Flow Free surface definition B(x, y = η ( x,z,t) or F(x, y,z,t) = 0 x y y z Unknown variables Velocity ﬁeld: Position of free surface: Pressure ﬁeld: **Governing equations** Continuity: Bernoulli for 1P-Flow: Far way, no disturbance ...

### 15.760: **National Cranberry** Case - **MIT OpenCourseWare**

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=**5400** -600/hr 2200/600 = 3.67hrs = 20:40 pm No more trucks 3200/450 = 7.1 = trucks begin waiting at 14:06 pm 8.67 hrs x (2200/2)/75 = 127 hours 7:00 9:00 11:00 13:00 15:00 17:00 19:00 21:00 23:00 1:00 3:00 Plant is empty after **5400**/600 = 9 hours after 19:00 or 4 am the next morning Total run time = 12600/600 = 21 hours ...

### Estimation with Minimum Square Error - **MIT OpenCourseWare**

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the probability mass of Y below it and the other half above, is **the value** of yb that minimizes the mean absolute deviation, E[ |Y − yb| ]. Also, the mode of Y , which is **the value** of y at which the PDF fY (y) is largest, turns out to minimize the expected **value** of an all-or-none cost function, i.e., a cost that is unity when the

### 6.092 **Lecture 4: Classes and Objects** - **MIT OpenCourseWare**

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Defining **Classes** Using **Classes** References vs Values Static types and methods. Today’s Topics Object oriented programming Defining **Classes** Using **Classes** ... **Classes** and Instances // class **Definition** public class Baby {…} // class Instances Baby shiloh = …

**Lecture 6:Regression Analysis** - **MIT OpenCourseWare**

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**Maximum Likelihood** Estimation Generalized M Estimation. Specifying Estimator Criterion in (2) Least Squares. **Maximum Likelihood**. Robust (Contamination-resistant) Bayes (assume j are r.v.’s with known prior distribution) Accommodating **incomplete**/missing **data** Case Analyses for (4) Checking Assumptions. Residual analysis Model errors i are ...

### 1 Difference **equations** - **MIT OpenCourseWare**

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1 Difference **equations**. 5. The samples grow quickly. Their growth is too rapid to fbe **logarithmic**, unless f[n] is an unusual function like (log n) 20. Their growth is probably also too rapid for f[n] to be a polynomial in n, unless f[n] is. n. a high-degree polynomial. A likely al ternative is **exponential** growth.o T test

### Chapter 9 Backward Induction - **MIT OpenCourseWare**

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Repeat this **procedure** until the origin is the only remaining node. Theoutcomeisthemoves thatarepicked inthe way. Sinceamove ispicked ateach information set, the result is a strategy proﬁle. For an illustration of the **procedure**, consider the game in the following ﬁgure. ... 14.12 **Economic** Applications of Game Theory

### 2D **Rigid Body Dynamics** - **MIT OpenCourseWare**

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Kinematics of Two-Dimensional **Rigid Body Motion** Even though a **rigid body** is composed of an inﬁnite number of particles, the **motion** of these particles is constrained to be such that the **body** remains a **rigid body** during the **motion**. In particular, the only degrees of freedom of a 2D **rigid body** are translation and rotation. Parallel Axes

### Statistics for Applications PsetSol3 - **MIT OpenCourseWare**

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the following **data** on Haptoglobin Type in a sample of 190 people Haptoglobin Type Hp1-1 Hp1-2 Hp2-2 10 68 112 This is precisely the same problem as Example 8.5.1.A of the text and class notes which corresponds to count **data**: (X 1,X 2,X 3) ∼ **Multinomial**(n = 3,p = ((1 − θ)2, 2θ(1 − θ),θ2) distribution. (a).

### Institute Technology DC” - **MIT OpenCourseWare**

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Figure 3: Axial View of Internal Magnet **Motor** A second morphology for an internal magneti **motor** is shown in Figure 3. This geometry has been proposed for highly salient synchronous machines without permanent magnets: such machines would run on the saliency torque and are called synchronous reluctance **motors**. however,

**Tangent Plane to a Level** - **MIT OpenCourseWare**

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**Tangent Plane to a Level** Surface 1. Find the tangent plane to the surface x. 2 + 2y. 2 + 3z. 2 = 36 at the point P = (1, 2, 3). Answer: In order to use gradients we introduce a new variable

**Experiment** 2: **Faraday** Ice Pail - **MIT OpenCourseWare**

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Michael **Faraday** used a metal ice pail as a conducting object to study how charges distributed themselves when a charged object was brought inside the pail. Suppose we lower a positively charged metal ball into the pail without touching it to the pail. When we do this, positive charges move as far away from the ball as possible – to the outer

### Problem Set 1 Solutions - **MIT OpenCourseWare**

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Solution: The **correct** order of these functions is f 1(n);f 4(n);f 3(n);f 2(n). The vari-able n never appears in the **formula** for f 1(n), so despite the multiple exponentials, f 1(n) is constant. Hence, it is asymptotically smaller than f 4(n), which does grow with n. We may rewrite p the **formula** for f 4(n) to be f 4(n) = n n = n1:5. The value of ...

### SIGNALS, **INFERENCE** for to and - **MIT OpenCourseWare**

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SIGNALS, SYSTEMS, and **INFERENCE** — Class Notes for 6.011: Introduction to Communication, Control and Signal Processing Spring 2010 Alan V. Oppenheim and George C. Verghese

### V13.3 Stokes’ Theorem - **MIT OpenCourseWare**

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To prove (3), we turn the left side into a **line** integral around C′, and the right side into a double integral over R, both in the xy-plane. Then we show that these two integrals are equal by **Green**’s theorem. To calculate the **line** integrals around C and C′, we parametrize these curves. Let C′ : x = x(t), y = y(t), t0 ≤ t ≤ t1

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