Axis Ip Utility Tool Download
Azucena Mcquay
Does anyone know if you can load the auto axis utility in Creo 3? If so, how do you do this? We had it in Creo 2 and now it is gone in Creo 3. Plus when I try to register the Creo 2 one I'm using in Creo 3 it says it can't run it. I've also tried adding the prodev.dat to the config and it won't stay saved in there. Can anyone help?
I am not trying to run a Creo 3 part in Creo 2. What I'm describing is a utility/auxiliary application we had in Creo 2 that would auto axis all the holes on step file brought in that didn't have any. When I try to run/add this utility in Creo 3 I get this:
If you have the flexible modeling tools in Creo 3.0, you can use the pattern recognition command to recognize patterns of features. If you place an axis on the leading feature that was recognized (typically a hole), you can make a pattern of axis relatively quickly. Might be something to look into if you haven't already.
I need a lil help with project I am working on so I figured why not ask the SME's on IPVM. I am trying to locate tool or utility that can go out and discover ONVIF IP Cameras then export the configuration/device information for auditing purposes. Unfortunately the ONVIF DM does not appear to have that functionality from what I can gather, its more basic and has no export/reporting capabilities.
Any bones that can be thrown my way is much appreciated, this is a HUGE task that right now is a very manual process because the VMS in place does not have this Enterprise Reporting function. With an estimated 28k IP cameras you can do the math, tons of man hours.
All of the cameras are on a closed IP network that that is connected to the Secondary NIC of the NVR Appliance running a embedded WinOS, trying to find a way to prevent trucks rolls to potentially 1k+ locations to gather the data for Compliance Reporting and Remediation. My thought process is that we might potentially might be able to take a tool (if it were to exist) and package it as a script that can be run via the OS and distributed from the enterprise controller.
Check out the Bosch Configuration Manager. It discovers ONVIF cameras and pulls a lot of info. It does have an export feature but I am not sure how much details you get as I have not tried to export yet.
I'm in the process of updating the website where it can be downloaded from. I'll also need to modify the utility to cater for large numbers of cameras but shouldn't take long. The utility is also free.
Even though I'm biased, this would probably not be a pleasant experience. You would have to install a lot of software just to collect the information, including dozens or more Recording Servers as I don't know what would happen if you tried to add 28k cameras to one system even if you weren't actually streaming. Maybe it would be a good test for our large scale test team?
The resulting reports would contain most of the desired info, but at present it would be in PDF format, so if you wanted to use it in any kind of external reporting tool like Excel or Crystal you would be out of luck. And imagine Adobe trying to open a PDF with many thousands of pages! You'd probably need 16GB of RAM just to open it haha...
Sure, I'm almost done with another project so will make it available here in just a few days. It will be able to access any number of IP Address ranges but that's an interesting question for this requirement, are the 28k devices in an IP sequence on say a 10.x range or across different blocks with even single IPs here and there? Do they all have the same login details? I'll try cater for the different scenarios with the utility ;)
The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.
Background: Tremor is a common feature of a variety of neurological disorders. In genetic studies of essential tremor (ET), investigators need to screen potential enrollees by mail or telephone to exclude those with other neurological conditions, especially dystonia. In clinical settings, the differentiation of ET and dystonia may also be very challenging. We hypothesized that the spiral axis, described below, is a useful screening tool to distinguish ET cases from dystonia cases.
Methods: We analyzed the hand-drawn spirals of 135 individuals enrolled in a genetics study at Columbia University Medical Center. Each of the four spirals was assessed for the presence of a single identifiable tremor orientation axis, and a spiral axis score (range = 0-4) [a single axis on all 4 spirals] was assigned to each enrollee.
Conclusion: Handwritten spirals appear to have a single predominant axis in more ET than dystonia cases. The evaluation of this axis has moderate diagnostic validity as a screening tool to distinguish ET cases from those with dystonia. Although this study did not assess the utility of this tool in clinical practice settings, future studies should do so.
Use Scatterplot to make enhanced scatterplots, with options to include boxplots in the margins, a linear regression line, a smooth curve via non-parametric regression, a smoothed conditional spread, outlier identification, and a regression line.
The smooth curve can help users more readily see the nature of the relationship between two variables relative to a traditional scatter plot, particularly in cases where there are many observations or a high level of dispersion in the data.
This tool uses the R tool. Go to Options > Download Predictive Tools and sign in to the Alteryx Downloads and Licenses portal to install R and the packages used by the R tool. Visit Download and Use Predictive Tools.
Y (vertical) field: The field (column) to use on the plot's vertical axis. Either a numerical field or a binary categorical field can be used. If a binary categorical field is selected, a new field (with the suffix ".num" appended to the original field name) is created that has numeric values of either zero or one. If a categorical variable with more than two values is selected, the node returns an error.
The Y field is a binary categorical variable: A check-box to indicate that the Y field is a binary categorical variable. When checked, you are asked to indicate the field value that will correspond to a value of one (the "target"), with entries with the other field value taking the value zero.
Show spread: Two curves showing the results of loess models to both the root-mean-square positive and negative residuals from the original loess line to display conditional spread and asymmetry in the errors. Included by default.
Marginal boxplots: Includes univariate boxplots of the X and Y field along each respective access. This is useful in assessing the distribution of values for both fields, and they are included by default.
Jitter X: When selected, the X values are randomly perturbed by a small amount. This is useful if a larger number of records in the X field take on one or a small number of values. It only influences the appearance points on the graphs, not the fitted regression and loess lines.
Jitter Y: When selected, the Y values are randomly perturbed by a small amount. This is useful if a larger number of records in the Y field take on one or a small number of values. It only influences the appearance points on the graphs, not the fitted regression and loess lines.
Plot by groups: This option allows for an examination of the effect of a categorical field on the relationship between the X and Y fields, with each value of the categorical resulting in a group of X and Y values. Groups are plotted with different colors and plotting characters. If this option is selected, you are asked to give the categorical field to be used in creating groups, (optionally) whether they would like regression and loess curves plotted for each group, and the location of the legend that identifies the different groups.
When you have an object selected and this tool selected and then hover your pointer on one of the three axis control points you should see something like this (I'm using rotating around Z for clarity):
I have general concept how to approach it in terms of coding.
But here I am not asking about the specific algorithms. Rather doing more research in the topic.
While there is plenty to read and resources available on the net, that I can refer to, I would like simply ask, if you have any good additional references in your opinion, which may be worth to share and read.
Both links are very nice readings.
Second one has more like reinforced few of my concept, adding extra, regarding more type of curves.
Regarding first article, this is something I will come back and read again through. There are few keywords listed, of some I want to get more familiar with.
Yep, this is some of my potential concerns. But way I may try to approach it, is by limiting, of how many utilities graphs I can plot, to evaluate score at once. Then maybe create I create sub system with another Utility AI. Just kind of like Behaviour Tree leafs work. That would be kind of hybrid approach.
However, this concept is not yet decided.