# Phimatrix Serial Number UPD

where n11, n10, n01, n00, are non-negative counts of numbers of observations that sum to n, the total number of observations. The phi coefficient that describes the association of x and y is

## phimatrix serial number

While there is no perfect way of describing the confusion matrix of true and false positives and negatives by a single number, the Matthews correlation coefficient is generally regarded as being one of the best such measures.[12] Other measures, such as the proportion of correct predictions (also termed accuracy), are not useful when the two classes are of very different sizes. For example, assigning every object to the larger set achieves a high proportion of correct predictions, but is not generally a useful classification.

In this equation, TP is the number of true positives, TN the number of true negatives, FP the number of false positives and FN the number of false negatives. If any of the four sums in the denominator is zero, the denominator can be arbitrarily set to one; this results in a Matthews correlation coefficient of zero, which can be shown to be the correct limiting value.

Career experience as CFO / CIO, most recently for private equity technology company and previously for operating of six public companies. MBA with Big Eight public accounting experience as a CPA. Entrepreneur and developer of PhiMatrix software, sold in over seventy countries. Author of Phi 1.618 : The Golden Number at __www.goldennumber.net__, which receives 1.5M+ visits per year.

The Golden Ratio is based on Fibonacci Numbers. These are a sequence of numbers where the next number is the sum of its two preceding ones. 1, 1, 2, 3, 5, 8, 13, 21 so on and so forth. Leonardo Fibonacci discovered this sequence in around 1200 AD.

Following this sequence to its inevitable conclusion, we reach the golden ratio of 1.618033... In mathematics, this is termed an irrational number or a number where decimal places are never ending and in a non-repeatable sequence, like Pi. Irrational numbers can also be written as a decimal but not as an equation. This number is usually rounded off to be simply 1.618.

Interesting. Can you control how many machines can use a license code? In our current eSellerate system we let people install on 2 machines with the same serial number and they can move it around using the deactivate and active.

I have not looked into this recently (9+ months). The solution would be the serial generator & maintenance of them be on your site. They will call an API (they will help you setup the calls to your API) to get the serial that they sold on your behalf.

if the serial numbers are not generated from user/computer information, you can preload a batch of keys into FS and they will issue them down the list as they sell them. And when you hit a low-water-mark on the list (you define that low water mark), they will email you letting you know that the keys are low so you can add more to the system.

LimeLM is set up to control the number of activations, with settings to control the degree of freedom a user has to activate and deactivate. In addition to setting up a default key for a product, you can create a uniquely defined key for a user. So yes, the user can move the license, even between Windows and Mac. The settings in creating a license include:

The notion of omega may be applied to the individual factors as well as the overall test. A typical use of omega is to identify subscales of a total inventory. Some of that variability is due to the general factor of the inventory, some to the specific variance of each subscale. Thus, we can find a number of different omega estimates: what percentage of the variance of the items identified with each subfactor is actually due to the general factor. What variance is common but unique to the subfactor, and what is the total reliable variance of each subfactor. These results are reported in omega.group object and in the last few lines of the normal output.

Serial mechanisms are usually characterized using an alphanumericnotation which lists the initials of the joint types in order from thebase down the chain. For simplicity, when multiple joints of the sametype are repeated, like "XXX", this is listed as "#X" where "#" is thenumber of repetitions. Examples include:

As mentioned above, the configuration of a robot is a minimal set ofcoordinates defining the position of all links. For serial or branchedfixed-base mechanisms, this is simply a list of individual jointcoordinates. For floating/mobile bases, the configuration is slightlymore complex, requiring the introduction of virtual linkages toaccount for the movement of the base link. The situation for parallelmechanisms is even more complex, and we will withhold this discussionfor later.

The degrees of freedom (dof) of a system define the span of its freelyand independently moving dimensions, and the number of degrees offreedom is also known as its mobility $M$. In the case of a serial orbranched fixed base mechanism, the degrees of freedom are the union ofall individual joint degrees of freedom, and the mobility is the sum ofthe mobilities of all individual joints: $$M = \sum_i=1^n f_i$$ wherethere are $n$ joints and $f_i$ is the mobility of the $i$'th joint, with$f_i = 1$ for revolute, prismatic, and helical joints, and $f_i = 3$ forspherical joints.

For floating and mobile bases, the movement of the robot takes place notonly via joint movement but also of the overall translation and rotationof the mechanism in space. As a result the number of degrees of freedomare increased. To represent this in a more straightforward manner, wetreat floating base robots as fixed-base robots by means of attaching avirtual linkage that expresses the mobility of the root link.

Conceptually, the formula calculates the number of dofs of the maximalcoordinate representation, and then subtracts the number of dofs removedby each joint. That is, if there are $n$ links and $m$ joints, each withmobility $f_1,\ldots,f_m$, then the mobility is given by$$M = 3 n - \sum_j=1^m (3-f_j).$$ in 2D and$$M = 6 n - \sum_j=1^m (6-f_j).$$ in 3D.

"Workspace" is somewhat of an overloaded term in robotics; it is alsoused to refer to the range of positions and orientations of a certainprivileged link, known as the end effector. End effectors aretypically at the far end of a serial chain of links, and are often wheretool points are located since these links have the largest range ofmotion. Depending on context, the workspace may refer to positions only,both positions and orientations, or, less frequently, orientations only.(It is due to this ambiguity that some authors prefer the term "taskspace" to speak specifically of an end-effector's spatial range, but thedual usage of "workspace" is widespread in the field.)

First, let us derive the forward kinematics for an $n$R serial robot.There are $n$ links $l_1,\ldots,l_n$, with the 1st link attached to theworld by a revolute joint, and the remaining $n-1$ links attached to theprior link by a revolute joint. Assume that at the 0 position, thelinks' coordinate frames are defined by their reference transforms:$$T_1,ref, T_2,ref,\ldots, T_n,ref$$each expressed as relative to the world coordinate __system.To__ make notation more convenient we shall represent these by $3\times 3$matrices in homogeneous coordinates. We shall also assume that eachjoint $j_1,\ldots,j_n$ is placed at the origin of the frame of $l_i$,and each joint angle $q_i$ gives the angle of link $l_i$ relative toits parent link, not in absolute heading.

Let us proceed to link 2, which moves in space as a function of both$q_1$ and $q_2$. Imagine $X$ now be a point attached to link 2, and let$\mathbfx^2$ be its coordinates with respect to the link's frame. Due tothe serial nature of the chain, we can imagine first rotating link 2 byangle $q_2$ and then rotating link 1 by angle $q_1$. To perform thisoperation, let us proceed with the following order of transformations:

However, our 2RP example showed that there are multiple choices offrames and axes that define the exact same robot dimensions. In fact,there are an infinite number of equivalent representations formed bymodifying reference frames and joint axes so that the axes represent thesame quantities in world coordinates. Moreover, we may rotate ortranslate a link's reference frame arbitrarily around its joint axis, aslong as we correct for the shift in its zero position. For somepurposes, it is useful to reduce the number of parameters specifying arobot's reference frame by choosing a convention. We have already seena convention where we have chosen to place joint axes at the origin ofthe child frame; in general, the joint could have been placedarbitrarily in space.

Denavit-Hartenberg convention is a well-known minimal parameterconvention for 3D serial robot kinematics. In this convention, jointaxes are always aligned to the $z$ axis of each child link, and theoffset between joints is always pointing along the $x$ axis of theparent link. It is usually not the most convenient representation forthe purposes of robot design and forward kinematics calculations, butdue to the minimal number of parameters used (4 per link) it remainspopular for robot structure optimization problems, like in robotcalibration.

Note that Klamp't numbers the links as they are listed in the URDF file, and assigns a configuration degree-of-freedom to each link. Hence, the 4-element configuration provided in line 7 addresses the links base_link, link_1, link_2, and the dummy end_effector frame.