I have the following situation which is required to be depicted by a Systems Flow Chart:
My attempt at drawing these diagrams is to figure out the following four things:
1) Input= The Sales Transaction
2) Process= Verification of Credit Card
3) Output= Reciept
4) Stored Data= Prices, Product and Transaction Files
How do I involve the Central Computer?
The model answer to this problem is:
I've looked up several legends that describe the common symbols used in System Flowcharts, but I've never come across a circle and zig-zagged lines. I would like to know the proper definitions for these two symbols. As per my knowledge, they can't represent input, document or storage system. Then what are they?
Lastly, could anyone please share a resource for learning and practising System Flow Chart diagrams or maybe any heuristic that one can use to solve such problems?
So that zig-zag line is Communication link, found it there (page 3), but it maybe depends on tool you are working with.
That zig-zag symbol represents the
transmission of data from one location to
another via communication lines.
Also that circle/elipse stands for the beginning,
end, or a point of interruption in a process or
program. Also used to indicate an external
party.
In your case it is external party.
Related
I got this code from google code :
void QBluetoothDeviceDiscoveryAgent::deviceDiscovered(const QBluetoothDeviceInfo &info)
QBluetoothDeviceInfo::rssi().
But how to get rssi distance from `QBluetoothServiceDiscoveryAgent ?
I tried with
QBluetoothServiceDiscoveryAgent serviceInfo;
quint i =serviceInfo.device().rssi();
here i = -43
how to convert it to distance?
I got the link
Understanding ibeacon distancing
but how to get the transmitter power? to calculate the distance according to formula?
Make sure you understood the implications of QBluetoothDeviceInfo::rssi(). Calling this functions returns immediately with the last stored value when the device was scanned last. If you only receive one advertisement-packet, which happens to be at e.x. -90dB, and then immediately connect, this function will keep returning -90 until you disconnect from it and scan it again. Connected devices usually don't send advertisement-packets so the RSSI you can read via Qt won't be updated during the connection.
As for proximity, it's not so easy to get good values. To accurately convert from RSSI to geometric distance you must know the sender's original/intended signal-strength (or TX-power-level == RSSI at 1m distance). This value will differ between devices. To make things worse, in practice it can also vary by a huge margin depending on things like the sender's battery-level, physical orientations of sender/receiver to eachother, quality of individual parts, random interference from other RF devices....
The BLE-folk has a blog explaining how you should do it. You can read it up here. The linked article doesn't read or assume the theoretical maximum RSSI of the sender but instead it propoposes to gather multiple RSSI-values over time (+ do some mean/mode filtering), and use the current mean-value in comparison with the previous value to determine if you are approaching or moving away from the sender. Paired with some fine-tuning using real-world data you gotta collect, plus documentation-reading and common-sense, you could probably develop a proximity calculation for many or even most sender-devices which would be accurate to about one meter or even less at close proximity. In the end it's a tradeoff between how many devices you wish to 'calibrate' for and those you are okay with having shifted values due to higher or lower TX-power-levels.
The downside being - you can't test for every possible device on the market and as I said earlier, different devices have different TX-power-levels. With this approach you can develop an algorithm to get pretty good measurements for devices which have approximately equal signal-configurations but others will seem far off. The article's author talks about creating different profiles for different vendors but that's not really gonna help (consider two identical beacons ("big/small"), one for large and one for small indoor locations - with RSSI alone you can't reliably determine if you're close to the small beacon or in medium range to the big one unless they identify themselves via GAP or otherwise (forget MAC-addresses if you plan to deploy on MacOS or iOS).
Also, prepare yourself for the joyride that is Android BLE development. Some vendors know that their BLE implementation is so terribly bad and broken, they even disabled the HCI-Logging-Feature on all their ROMs to hide it. Others can be BLE-nuked like Win98 by ethernet, back in the days.
I am working user behavior project. Based on user interaction I have got some data. There is nice sequence which smoothly increases and decreases over the time. But there are little discrepancies, which are very bad. Please refer to graph below:
You can also find data here:
2.0789 2.09604 2.11472 2.13414 2.15609 2.17776 2.2021 2.22722 2.25019 2.27304 2.29724 2.31991 2.34285 2.36569 2.38682 2.40634 2.42068 2.43947 2.45099 2.46564 2.48385 2.49747 2.49031 2.51458 2.5149 2.52632 2.54689 2.56077 2.57821 2.57877 2.59104 2.57625 2.55987 2.5694 2.56244 2.56599 2.54696 2.52479 2.50345 2.48306 2.50934 2.4512 2.43586 2.40664 2.38721 2.3816 2.36415 2.33408 2.31225 2.28801 2.26583 2.24054 2.2135 2.19678 2.16366 2.13945 2.11102 2.08389 2.05533 2.02899 2.00373 1.9752 1.94862 1.91982 1.89125 1.86307 1.83539 1.80641 1.77946 1.75333 1.72765 1.70417 1.68106 1.65971 1.64032 1.62386 1.6034 1.5829 1.56022 1.54167 1.53141 1.52329 1.51128 1.52125 1.51127 1.50753 1.51494 1.51777 1.55563 1.56948 1.57866 1.60095 1.61939 1.64399 1.67643 1.70784 1.74259 1.7815 1.81939 1.84942 1.87731
1.89895 1.91676 1.92987
I would want to smooth out this sequence. The technique should be able to eliminate numbers with characteristic of X and Y, i.e. error in mono-increasing or mono-decreasing.
If not eliminate, technique should be able to shift them so that series is not affected by errors.
What I have tried and failed:
I tried to test difference between values. In some special cases it works, but for sequence as presented in this the distance between numbers is not such that I can cut out errors
I tried applying a counter, which is some X, then only change is accepted otherwise point is mapped to previous point only. Here I have great trouble deciding on value of X, because this is based on user-interaction, I am not really controller of it. If user interaction is such that its plot would be a zigzag pattern, I am ending up with 'no user movement data detected at all' situation.
Please share the techniques that you are aware of.
PS: Data made available in this example is a particular case. There is no typical pattern in which numbers are going to occure, but we expect some range to be continuous with all the examples. Solution I am seeking is generic.
I do not know how much effort you want to involve in this problem but if you want theoretical guaranties,
topological persistence seems well adapted to your problem imho.
Basically with that method, you can filtrate local maximum/minimum by fixing a scale
and there are theoritical proofs that says that if you sampling is
close from your function, then you extracts correct number of maximums with persistence.
You can see these slides (mainly pages 7-9 to get the idea) to get an idea of the method.
Basically, if you take your points as a landscape and imagine a watershed starting from maximum height and decreasing, you have some picks.
Every pick has a time where it is born which is the time where it becomes emerged and a time where it dies which is when it merges with an higher pick. Now a persistence diagram pictures a point for every pick where its x/y coordinates are its time of birth/death (by assumption the first pick does not die and is not shown).
If a pick is a global maximal, then it will be further from the diagonal in the persistence diagram than a local maximum pick. To remove local maximums you have to remove picks close to the diagonal. There are fours local maximums in your example as you can see with the persistence diagram of your data (thanks for providing the data btw) and two global ones (the first pick is not pictured in a persistence diagram):
If you noise your data like that :
You will still get a very decent persistence diagram that will allow you to filter local maximum as you want :
Please ask if you want more details or references.
Since you can not decide on a cut off frequency, and not even on the filter you want to use, I would implement several, and let the user set the parameters.
The first thing that I thought of is running average, and you can see that there are so many things to set, to get different outputs.
We’re using JCo 3.0 to connect to RFCs and read data from SAP R/3. We use one RFC RFC_READ_TABLE often and use a second custom RFC to read employee information. My questions revolve around a third RFC RSAQ_REMOTE_QUERY_CALL. I'm calling an ad-hoc query I built in SAP using this RFC but I’m not getting the expected results. The main problem is that it appears that SAP is ignoring one of my selection criteria and using what was saved in SAP when I originally built it. The date criterion stored in my ad-hoc is 6/23/2013. If I pass in 6/28/2013 from JCo, I get the same results as if I had passed 6/23/2013 from JCo.
We have built several ad-hoc queries whose only criteria is a personnel number and call them successfully using RFC RSAQ_REMOTE_QUERY_CALL.
Background on my ad-hoc query: reporting period of today, joining together four aspects of an employee’s information: their latest action (hire, rehire, etc.), organization (e.g. company), pay (e.g. pay scale level) and communication (e.g. email). The query will run every workday.
Here are my questions:
My ad-hoc has three selection criteria. The first two are simple strings. The third is a date. The date will vary each time the query runs. We are referencing the first criteria using SP$00001, the second with SP$00002 and the third with SP$00003. The order of the criteria changes from the ad-hoc to SQ01 (what was SP$00001 in the ad-hoc is now SP$00003). Shouldn’t we reference them in the order defined in the ad-hoc (e.g. SP$00001)?
The two simple string selections are using OPTION “EQ”. The date criteria is using OPTION GT (greater than). Is “GT” correct?
We have some limited accessibility to SAP. Is there a way to see which SP$ parameters are mapped to which criteria?
If my ad-hoc was saved with five criteria but four of them never change when I call the ad-hoc from JCo, do I just need to set the value of the one or do I need to set the other four as well?
Do I have to call this ad-hoc using a variant (function.getImportParameterList().setValue(“VARIANT”, “VARIANT_NAME”))?
Does the Reporting Period have an impact on the date criteria? I have tried changing the Reporting Period to be PNPBEGDA = today and PNPENDDA = today and noticed no change.
Is there a way in SAP to get a “declaration” of your ad-hoc (name, inputs, outputs, criteria)? I have looked at JCoFunction.toXml() and JCoFunctionTemplate. These are good if you want to see something at runtime before it goes to SAP, but I’m looking for something I can use on the JCo end to help me write Java code that matches the ad-hoc.
I have looked at length on the web for answers to my questions and have not found anything that is useful. If there is anything which would help me, please let me know.
Thanks,
LM
Since I don't know much about SQnn, I won't be able to answer all of your questions...
I don't know, sorry.
It should be, at least it's the usual operator for greater than.
Yes - set an external breakpoint right inside the function module and trace its execution while performing the RFC call. Warning: At least basic ABAP knowledge required.
I don't know, sorry.
I don't know either, sorry.
That would depend on the query, I suspect...
JCo won't be able to help you out there - it doesn't know about queries, it only knows function modules. There might be other RSAQ_* function modules to get that information though.
I played with setting up a variant in SQ01 for my query. I added some settings in the variant that solved my problem and answered several of my questions in my post. The main thing I did was add a dynamically calculated date as part of my criteria. Here's how:
1. In SQ01, access menu "Go To" -> "Maintain Variants".
2. Choose your variant and in subobjects, choose "Attributes" and click "Change".
3. In the displayed list, find your date criterion.
4. Choose "D" in Selection Variable, choose a comparison option (mine was GT for greater than), and a "Name of a Variable" (really, this is the type of dynamic date calculation you need).
5. Go back to the Subobjects panel, choose "Values" and click "Change".
6. Enter any other criteria you need in the "Program selections" section.
7. Save the variant.
By doing this, I don't need to pass anything into the query from JCo. Also, SAP will automatically update the date criteria you entered in step #4 above.
So to to answer my questions from my original post:
1 and 4. It doesn't matter because I'm no longer passing anything in from JCo.
2. "GT" is Greater Than.
3 and 7. If anyone knows, I'd really like to find out.
5. Use the name you as it is in SAP (step #2 above).
6. I still don't know, but it's not holding me up.
I'm posting this in case anyone out there needs this type of information. Thanks to Esti and vwegert for helping me out.
I'm very new in image processing and my first assignment is to make a working program which can recognize faces and their names.
Until now, I successfully make a project to detect, crop the detected image, make it to sobel and translate it to array of float.
But, I'm very confused how to implement the Backpropagation MLP to learn the image so it can recognize the correct name for the detected face.
It's a great honor for all experts in stackoverflow to give me some examples how to implement the Image array to be learned with the backpropagation.
It is standard machine learning algorithm. You have a number of arrays of floats (instances in ML or observations in statistics terms) and corresponding names (labels, class tags), one per array. This is enough for use in most ML algorithms. Specifically in ANN, elements of your array (i.e. features) are inputs of the network and labels (names) are its outputs.
If you are looking for theoretical description of backpropagation, take a look at Stanford's ml-class lectures (ANN section). If you need ready implementation, read this question.
You haven't specified what are elements of your arrays. If you use just pixels of original image, this should work, but not very well. If you need production level system (though still with the use of ANN), try to extract more high level features (e.g. Haar-like features, that OpenCV uses itself).
Have you tried writing your feature vectors to an arff file and to feed them to weka, just to see if your approach might work at all?
Weka has a lot of classifiers integrated, including MLP.
As I understood so far, I suspect the features and the classifier you have chosen not to work.
To your original question: Have you made any attempts to implement a neural network on your own? If so, where you got stuck? Note, that this is not the place to request a complete working implementation from the audience.
To provide a general answer on a general question:
Usually you have nodes in an MLP. Specifically input nodes, output nodes, and hidden nodes. These nodes are strictly organized in layers. The input layer at the bottom, the output layer on the top, hidden layers in between. The nodes are connected in a simple feed-forward fashion (output connections are allowed to the next higher layer only).
Then you go and connect each of your float to a single input node and feed the feature vectors to your network. For your backpropagation you need to supply an error signal that you specify for the output nodes. So if you have n names to distinguish, you may use n output nodes (i.e. one for each name). Make them for example return 1 in case of a match and 0 else. You could very well use one output node and let it return n different values for the names. Probably it would even be best to use n completely different perceptrons, i.e. one for each name, to avoid some side-effects (catastrophic interference).
Note, that the output of each node is a number, not a name. Therefore you need to use some sort of thresholds, to get a number-name relation.
Also note, that you need a lot of training data to train a large network (i.e. to obey the curse of dimensionality). It would be interesting to know the size of your float array.
Indeed, for a complex decision you may need a larger number of hidden nodes or even hidden layers.
Further note, that you may need to do a lot of evaluation (i.e. cross validation) to find the optimal configuration (number of layers, number of nodes per layer), or to find even any working configuration.
Good luck, any way!
Suppose I want to do some data mining on the database of a supermarket. What does that actually mean?
1) What will the output/results be like?
2) Will the output be different every day or change over time?
3) Before applying data mining, do I need to know what I want or will data mining give everything I want automatically?
Data Mining is a general category of techniques that can be applied to different kinds of datasets, just like programming is a general category of techniques that can be applied using different languages to do different things.
None of your questions make any sense.
A1: Data mining will give us an accurate reports about your queries of database of supermarket.
A2: Sure, because Data mining depend on analyzing during time, in this case it depend on your problems or goals that you want to reach it. if your database was very big also you built data warehouse in right way you will get the different output over time.
A3: yes you should determine what are the problems you have to mine then use tools of Data mining to get the results or indicators automatically.
To answer your first question: For the case of supermarket customer data, I could image the following questions:
how many products X are usually sold on Fridays ?
(helps you to determine how many X you should have in stock)
which customers bought product X often in the last month/year ?
Useful when when you introduce a new X-like product: send advertising material (which has a given cost) only to those customers.
given a customer buys product X (e.g. beer) what's the probability that he/she also buys product Y (e.g. chips) ?
useful for the following: make sure X and Y never are on promotional offer at the same time (X and Y are bought together often). Get the customers into the store by offering a rebate on X knowing they'll also by Y at the same time. Or: put a high price X-like product right next to Y, putting the cheaper X somewhere else.
which neighborhoods have the smallest number of customers ?
helps to find out which neighborhoods you could target with advertising to bring more customers into the store.
Often, by 'asking certain questions to the data' one discovers some features and comes up with new questions.
Data mining is a set of techniques. It refers to discovering interesting and unexpected patterns in data.
If you want to apply some data mining techniques, you need to know which one and you should know why. The answer to questions 1, 2 and 3 depends on the techniques that you choose.
For example, if i want to find associations between items sold in a supermarket, i may use association rule mining. If i want to find groups of similar customers, I might use a clustering algorithm. etc.
There is not just ONE technique in data mining.