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  • How Do Nautilus Album Art Thumbnails work?

    - by Amir Adar
    There's something for which I've been searching an answer for a while now, but to no avail, and it's strange to me, as it seems like a thing that people would talk about: one of those nice little nonsense that enhance the computing experience a little bit. Anyway. I have a fair music collection. I save all the songs as ogg files. All is fine, and I can listen to the files, but there's something weird with the files in Nautilus: some have icons displaying their album art, while others don't, and I just can't understand WHY. I read on this site today that it's a matter of embedding the album art to the file, but that's not true, as I embedded the album art to the files I wanted several times, to no avail. Furthermore, removing an embedded album art from a file didn't have any effect on those that ARE displaying the icons. So my question is: How does it work? Where does Nautilus (or Ubuntu, I don't know) get the picture from? How do I edit it? Thanks in advance! -Amir

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  • Predicting Likelihood of Click with Multiple Presentations

    - by Michel Adar
    When using predictive models to predict the likelihood of an ad or a banner to be clicked on it is common to ignore the fact that the same content may have been presented in the past to the same visitor. While the error may be small if the visitors do not often see repeated content, it may be very significant for sites where visitors come repeatedly. This is a well recognized problem that usually gets handled with presentation thresholds – do not present the same content more than 6 times. Observations and measurements of visitor behavior provide evidence that something better is needed. Observations For a specific visitor, during a single session, for a banner in a not too prominent space, the second presentation of the same content is more likely to be clicked on than the first presentation. The difference can be 30% to 100% higher likelihood for the second presentation when compared to the first. That is, for example, if the first presentation has an average click rate of 1%, the second presentation may have an average CTR of between 1.3% and 2%. After the second presentation the CTR stays more or less the same for a few more presentations. The number of presentations in this plateau seems to vary by the location of the content in the page and by the visual attraction of the content. After these few presentations the CTR starts decaying with a curve that is very well approximated by an exponential decay. For example, the 13th presentation may have 90% the likelihood of the 12th, and the 14th has 90% the likelihood of the 13th. The decay constant seems also to depend on the visibility of the content. Modeling Options Now that we know the empirical data, we can propose modeling techniques that will correctly predict the likelihood of a click. Use presentation number as an input to the predictive model Probably the most straight forward approach is to add the presentation number as an input to the predictive model. While this is certainly a simple solution, it carries with it several problems, among them: If the model learns on each case, repeated non-clicks for the same content will reinforce the belief of the model on the non-clicker disproportionately. That is, the weight of a person that does not click for 200 presentations of an offer may be the same as 100 other people that on average click on the second presentation. The effect of the presentation number is not a customer characteristic or a piece of contextual data about the interaction with the customer, but it is contextual data about the content presented. Models tend to underestimate the effect of the presentation number. For these reasons it is not advisable to use this approach when the average number of presentations of the same content to the same person is above 3, or when there are cases of having the presentation number be very large, in the tens or hundreds. Use presentation number as a partitioning attribute to the predictive model In this approach we essentially build a separate predictive model for each presentation number. This approach overcomes all of the problems in the previous approach, nevertheless, it can be applied only when the volume of data is large enough to have these very specific sub-models converge.

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  • The softer side of BPM

    - by [email protected]
    BPM and RTD are great complementary technologies that together provide a much higher benefit than each of them separately. BPM covers the need for automating processes, making sure that there is uniformity, that rules and regulations are complied with and that the process runs smoothly and quickly processes the units flowing through it. By nature, this automation and unification can lead to a stricter, less flexible process. To avoid this problem it is common to encounter process definition that include multiple conditional branches and human input to help direct processing in the direction that best applies to the current situation. This is where RTD comes into play. The selection of branches and conditions and the optimization of decisions is better left in the hands of a system that can measure the results of its decisions in a closed loop fashion and make decisions based on the empirical knowledge accumulated through observing the running of the process.When designing a business process there are key places in which it may be beneficial to introduce RTD decisions. These are:Thresholds - whenever a threshold is used to determine the processing of a unit, there may be an opportunity to make the threshold "softer" by introducing an RTD decision based on predicted results. For example an insurance company process may have a total claim threshold to initiate an investigation. Instead of having that threshold, RTD could be used to help determine what claims to investigate based on the likelihood they are fraudulent, cost of investigation and effect on processing time.Human decisions - sometimes a process will let the human participants make decisions of flow. For example, a call center process may leave the escalation decision to the agent. While this has flexibility, it may produce undesired results and asymetry in customer treatment that is not based on objective functions but subjective reasoning by the agent. Instead, an RTD decision may be introduced to recommend escalation or other kinds of treatments.Content Selection - a process may include the use of messaging with customers. The selection of the most appropriate message to the customer given the content can be optimized with RTD.A/B Testing - a process may have optional paths for which it is not clear what populations they work better for. Rather than making the arbitrary selection or selection by committee of the option deeped the best, RTD can be introduced to dynamically determine the best path for each unit.In summary, RTD can be used to make BPM based process automation more dynamic and adaptable to the different situations encountered in processing. Effectively making the automation softer, less rigid in its processing.

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  • Ignoring Robots - Or Better Yet, Counting Them Separately

    - by [email protected]
    It is quite common to have web sessions that are undesirable from the point of view of analytics. For example, when there are either internal or external robots that check the site's health, index it or just extract information from it. These robotic session do not behave like humans and if their volume is high enough they can sway the statistics and models.One easy way to deal with these sessions is to define a partitioning variable for all the models that is a flag indicating whether the session is "Normal" or "Robot". Then all the reports and the predictions can use the "Normal" partition, while the counts and statistics for Robots are still available.In order for this to work, though, it is necessary to have two conditions:1. It is possible to identify the Robotic sessions.2. No learning happens before the identification of the session as a robot.The first point is obvious, but the second may require some explanation. While the default in RTD is to learn at the end of the session, it is possible to learn in any entry point. This is a setting for each model. There are various reasons to learn in a specific entry point, for example if there is a desire to capture exactly and precisely the data in the session at the time the event happened as opposed to including changes to the end of the session.In any case, if RTD has already learned on the session before the identification of a robot was done there is no way to retract this learning.Identifying the robotic sessions can be done through the use of rules and heuristics. For example we may use some of the following:Maintain a list of known robotic IPs or domainsDetect very long sessions, lasting more than a few hours or visiting more than 500 pagesDetect "robotic" behaviors like a methodic click on all the link of every pageDetect a session with 10 pages clicked at exactly 20 second intervalsDetect extensive non-linear navigationNow, an interesting experiment would be to use the flag above as an output of a model to see if there are more subtle characteristics of robots such that a model can be used to detect robots, even if they fall through the cracks of rules and heuristics.In any case, the basic and simple technique of partitioning the models by the type of session is simple to implement and provides a lot of advantages.

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  • Is RTD Stateless or Stateful?

    - by [email protected]
    Yes.   A stateless service is one where each request is an independent transaction that can be processed by any of the servers in a cluster.  A stateful service is one where state is kept in a server's memory from transaction to transaction, thus necessitating the proper routing of requests to the right server. The main advantage of stateless systems is simplicity of design. The main advantage of stateful systems is performance. I'm often asked whether RTD is a stateless or stateful service, so I wanted to clarify this issue in depth so that RTD's architecture will be properly understood. The short answer is: "RTD can be configured as a stateless or stateful service." The performance difference between stateless and stateful systems can be very significant, and while in a call center implementation it may be reasonable to use a pure stateless configuration, a web implementation that produces thousands of requests per second is practically impossible with a stateless configuration. RTD's performance is orders of magnitude better than most competing systems. RTD was architected from the ground up to achieve this performance. Features like automatic and dynamic compression of prediction models, automatic translation of metadata to machine code, lack of interpreted languages, and separation of model building from decisioning contribute to achieving this performance level. Because  of this focus on performance we decided to have RTD's default configuration work in a stateful manner. By being stateful RTD requests are typically handled in a few milliseconds when repeated requests come to the same session. Now, those readers that have participated in implementations of RTD know that RTD's architecture is also focused on reducing Total Cost of Ownership (TCO) with features like automatic model building, automatic time windows, automatic maintenance of database tables, automatic evaluation of data mining models, automatic management of models partitioned by channel, geography, etcetera, and hot swapping of configurations. How do you reconcile the need for a low TCO and the need for performance? How do you get the performance of a stateful system with the simplicity of a stateless system? The answer is that you make the system behave like a stateless system to the exterior, but you let it automatically take advantage of situations where being stateful is better. For example, one of the advantages of stateless systems is that you can route a message to any server in a cluster, without worrying about sending it to the same server that was handling the session in previous messages. With an RTD stateful configuration you can still route the message to any server in the cluster, so from the point of view of the configuration of other systems, it is the same as a stateless service. The difference though comes in performance, because if the message arrives to the right server, RTD can serve it without any external access to the session's state, thus tremendously reducing processing time. In typical implementations it is not rare to have high percentages of messages routed directly to the right server, while those that are not, are easily handled by forwarding the messages to the right server. This architecture usually provides the best of both worlds with performance and simplicity of configuration.   Configuring RTD as a pure stateless service A pure stateless configuration requires session data to be persisted at the end of handling each and every message and reloading that data at the beginning of handling any new message. This is of course, the root of the inefficiency of these configurations. This is also the reason why many "stateless" implementations actually do keep state to take advantage of a request coming back to the same server. Nevertheless, if the implementation requires a pure stateless decision service, this is easy to configure in RTD. The way to do it is: Mark every Integration Point to Close the session at the end of processing the message In the Session entity persist the session data on closing the session In the session entity check if a persisted version exists and load it An excellent solution for persisting the session data is Oracle Coherence, which provides a high performance, distributed cache that minimizes the performance impact of persisting and reloading the session. Alternatively, the session can be persisted to a local database. An interesting feature of the RTD stateless configuration is that it can cope with serializing concurrent requests for the same session. For example, if a web page produces two requests to the decision service, these requests could come concurrently to the decision services and be handled by different servers. Most stateless implementation would have the two requests step onto each other when saving the state, or fail one of the messages. When properly configured, RTD will make one message wait for the other before processing.   A Word on Context Using the context of a customer interaction typically significantly increases lift. For example, offer success in a call center could double if the context of the call is taken into account. For this reason, it is important to utilize the contextual information in decision making. To make the contextual information available throughout a session it needs to be persisted. When there is a well defined owner for the information then there is no problem because in case of a session restart, the information can be easily retrieved. If there is no official owner of the information, then RTD can be configured to persist this information.   Once again, RTD provides flexibility to ensure high performance when it is adequate to allow for some loss of state in the rare cases of server failure. For example, in a heavy use web site that serves 1000 pages per second the navigation history may be stored in the in memory session. In such sites it is typical that there is no OLTP that stores all the navigation events, therefore if an RTD server were to fail, it would be possible for the navigation to that point to be lost (note that a new session would be immediately established in one of the other servers). In most cases the loss of this navigation information would be acceptable as it would happen rarely. If it is desired to save this information, RTD would persist it every time the visitor navigates to a new page. Note that this practice is preferred whether RTD is configured in a stateless or stateful manner.  

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  • Tips on ensuring Model Quality

    - by [email protected]
    Given enough data that represents well the domain and models that reflect exactly the decision being optimized, models usually provide good predictions that ensure lift. Nevertheless, sometimes the modeling situation is less than ideal. In this blog entry we explore the problems found in a few such situations and how to avoid them.1 - The Model does not reflect the problem you are trying to solveFor example, you may be trying to solve the problem: "What product should I recommend to this customer" but your model learns on the problem: "Given that a customer has acquired our products, what is the likelihood for each product". In this case the model you built may be too far of a proxy for the problem you are really trying to solve. What you could do in this case is try to build a model based on the result from recommendations of products to customers. If there is not enough data from actual recommendations, you could use a hybrid approach in which you would use the [bad] proxy model until the recommendation model converges.2 - Data is not predictive enoughIf the inputs are not correlated with the output then the models may be unable to provide good predictions. For example, if the input is the phase of the moon and the weather and the output is what car did the customer buy, there may be no correlations found. In this case you should see a low quality model.The solution in this case is to include more relevant inputs.3 - Not enough cases seenIf the data learned does not include enough cases, at least 200 positive examples for each output, then the quality of recommendations may be low. The obvious solution is to include more data records. If this is not possible, then it may be possible to build a model based on the characteristics of the output choices rather than the choices themselves. For example, instead of using products as output, use the product category, price and brand name, and then combine these models.4 - Output leaking into input giving the false impression of good quality modelsIf the input data in the training includes values that have changed or are available only because the output happened, then you will find some strong correlations between the input and the output, but these strong correlations do not reflect the data that you will have available at decision (prediction) time. For example, if you are building a model to predict whether a web site visitor will succeed in registering, and the input includes the variable DaysSinceRegistration, and you learn when this variable has already been set, you will probably see a big correlation between having a Zero (or one) in this variable and the fact that registration was successful.The solution is to remove these variables from the input or make sure they reflect the value as of the time of decision and not after the result is known. 

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  • Short Season, Long Models - Dealing with Seasonality

    - by Michel Adar
    Accounting for seasonality presents a challenge for the accurate prediction of events. Examples of seasonality include: ·         Boxed cosmetics sets are more popular during Christmas. They sell at other times of the year, but they rise higher than other products during the holiday season. ·         Interest in a promotion rises around the time advertising on TV airs ·         Interest in the Sports section of a newspaper rises when there is a big football match There are several ways of dealing with seasonality in predictions. Time Windows If the length of the model time windows is short enough relative to the seasonality effect, then the models will see only seasonal data, and therefore will be accurate in their predictions. For example, a model with a weekly time window may be quick enough to adapt during the holiday season. In order for time windows to be useful in dealing with seasonality it is necessary that: The time window is significantly shorter than the season changes There is enough volume of data in the short time windows to produce an accurate model An additional issue to consider is that sometimes the season may have an abrupt end, for example the day after Christmas. Input Data If available, it is possible to include the seasonality effect in the input data for the model. For example the customer record may include a list of all the promotions advertised in the area of residence. A model with these inputs will have to learn the effect of the input. It is possible to learn it specific to the promotion – and by the way learn about inter-promotion cross feeding – by leaving the list of ads as it is; or it is possible to learn the general effect by having a flag that indicates if the promotion is being advertised. For inputs to properly represent the effect in the model it is necessary that: The model sees enough events with the input present. For example, by virtue of the model lifetime (or time window) being long enough to see several “seasons” or by having enough volume for the model to learn seasonality quickly. Proportional Frequency If we create a model that ignores seasonality it is possible to use that model to predict how the specific person likelihood differs from average. If we have a divergence from average then we can transfer that divergence proportionally to the observed frequency at the time of the prediction. Definitions: Ft = trailing average frequency of the event at time “t”. The average is done over a suitable period of to achieve a statistical significant estimate. F = average frequency as seen by the model. L = likelihood predicted by the model for a specific person Lt = predicted likelihood proportionally scaled for time “t”. If the model is good at predicting deviation from average, and this holds over the interesting range of seasons, then we can estimate Lt as: Lt = L * (Ft / F) Considering that: L = (L – F) + F Substituting we get: Lt = [(L – F) + F] * (Ft / F) Which simplifies to: (i)                  Lt = (L – F) * (Ft / F)  +  Ft This latest expression can be understood as “The adjusted likelihood at time t is the average likelihood at time t plus the effect from the model, which is calculated as the difference from average time the proportion of frequencies”. The formula above assumes a linear translation of the proportion. It is possible to generalize the formula using a factor which we will call “a” as follows: (ii)                Lt = (L – F) * (Ft / F) * a  +  Ft It is also possible to use a formula that does not scale the difference, like: (iii)               Lt = (L – F) * a  +  Ft While these formulas seem reasonable, they should be taken as hypothesis to be proven with empirical data. A theoretical analysis provides the following insights: The Cumulative Gains Chart (lift) should stay the same, as at any given time the order of the likelihood for different customers is preserved If F is equal to Ft then the formula reverts to “L” If (Ft = 0) then Lt in (i) and (ii) is 0 It is possible for Lt to be above 1. If it is desired to avoid going over 1, for relatively high base frequencies it is possible to use a relative interpretation of the multiplicative factor. For example, if we say that Y is twice as likely as X, then we can interpret this sentence as: If X is 3%, then Y is 6% If X is 11%, then Y is 22% If X is 70%, then Y is 85% - in this case we interpret “twice as likely” as “half as likely to not happen” Applying this reasoning to (i) for example we would get: If (L < F) or (Ft < (1 / ((L/F) + 1)) Then  Lt = L * (Ft / F) Else Lt = 1 – (F / L) + (Ft * F / L)  

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  • External USB hard drive makes noises when the computer is turned off

    - by Amir Adar
    I have an external USB hard drive of 500GB. I can't tell what model it is exactly, as nothing specific is written on it and I don't have the box anymore. I use it as a backup disk. It works absolutely fine when the computer is turned on: no problems with writing or reading, and everything is done in dead silence. However, if I turn the computer off and the disk is still connected, it stays on and makes clicking noises. For that reason I only connect it when I need to back up or restore. Does that mean there's a problem with the disk, or with some preferences in the system itself? Or something else?

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  • Customer retention - why most companies have it wrong

    - by Michel Adar
    At least in the US market it is quite common for service companies to offer an initially discounted price to new customers. While this may attract new customers and robe customers from competitors, it is my argument that it is a bad strategy for the company. This strategy gives an incentive to change companies and a disincentive to stay with the company. From the point of view of the customer, after 6 months of being a customer the company rewards the loyalty by raising the price. A better strategy would be to reward customers for staying with the company. For example, by lowering the cost by 5% every year (compound discount so it does never get to zero). This is a very rational thing to do for the company. Acquiring new customers and setting up their service is expensive, new customers also tend to use more of the common resources like customer service channels. It is probably true for most companies that the cost of providing service to a customer of 10 years is lower than providing the same service in the first year of a customer's tenure. It is only logical to pass these savings to the customer. From the customer point of view, the competition would have to offer something very attractive, whether in terms of price or service, in order for the customer to switch. Such a policy would give an advantage to the first mover, but would probably force the competitors to follow suit. Overall, I would expect that this would reduce the mobility in the market, increase loyalty, increase the investment of companies in loyal customers and ultimately, increase competition for providing a better service. Competitors may even try to break the scheme by offering customers the porting of their tenure, but that would not work that well because it would disenchant existing customers and would be costly, assuming that it is costlier to serve a customer through installation and first year. What do you think? Is this better than using "save offers" to retain flip-floppers?

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  • Can't login to Unity 3d after enabling Xinerama for a short moment

    - by Amir Adar
    Today I connected a second monitor to my computer. I set it up using nVidia's control panel, and all was working quite well, so I figured it won't be a problem to try Xinerama, just to see the difference between that and twinview. After enabling Xinerama and restarting the X session, I saw that I was logged into a Unity 2d session. I thought it was a problem with Xinerama, so I switched back to twinview, but it still logged me into Unity 2d. I tried disconnecting the second monitor, no luck: still Unity 2d. I tried changing GPU drivers and installing drivers from a separate ppa, and still I was logged into Unity 2d. Up until this point, I didn't have any problem logging into Unity 3d. It only happened after I tried using Xinerama. I should note that I was doing all this while updates were going on in the background, so it could be something related to that, though I can't imagine what (I tried booting with another kernel, but no luck). So what exactly happened? Did changing the mode to Xinerama triggered some other changes that I'm not aware of? Did these updates cause a certain malfunction in the driver? Is it something else?

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  • how to crop an image using rectangale overlay and touch on iphone

    - by Amir
    Hey Everyone, I am looking for a good tutorial or sample code, that would show how to crop an image taking from iphone camera something in lines of http://www.defusion.org.uk/code/javascript-image-cropper-ui-using-prototype-scriptaculous/ but you would control the corners with your fingers any tip would be greatly appericated, as i am new to iphone dev. Thanks, Amir

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  • Image improvment methods for OCR Engine

    - by Amir
    Hello every one, We are working on a software that uses OPENOCR engine to do some OCR on given images, given we are using .NET framework , i was wondering if anyone knows about any good possible filters or sharpening methods that can be applied to the image prior to sending it to OCR engine. I have found for example a grayscaled image is much easier for OCR engine to read than a color images. are there any other techniques or image filttering that you guys know of , that can decrease the error margin by OCR engine ? Thanks a million -Amir

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  • How to detach a sql server 2008 database that is not in database list?

    - by Amir
    I installed SQL Server 2008 on Windows 7. Then I created a database. After 2 days I reinstalled Windows and SQL Server. Now I am trying to attach my database file, but I have encountered the error below. I think that the files are like an attached file and I can't attach them. What is difference between an attached file and a non-attached file? How can I attach this file? Please Help Me. Error Text: TITLE: Microsoft SQL Server Management Studio Attach database failed for Server 'AMIR-PC'. (Microsoft.SqlServer.Smo) For help, click: http://go.microsoft.com/fwlink?ProdName=Microsoft+SQL+Server&ProdVer=10.50.1600.1+((KJ_RTM).100402-1540+)&EvtSrc=Microsoft.SqlServer.Management.Smo.ExceptionTemplates.FailedOperationExceptionText&EvtID=Attach+database+Server&LinkId=20476 ------------------------------ ADDITIONAL INFORMATION: An exception occurred while executing a Transact-SQL statement or batch. (Microsoft.SqlServer.ConnectionInfo) Unable to open the physical file "F:\Company.mdf". Operating system error 5: "5(Access is denied.)". (Microsoft SQL Server, Error: 5120) For help, click: http://go.microsoft.com/fwlink?ProdName=Microsoft+SQL+Server&ProdVer=10.50.1600&EvtSrc=MSSQLServer&EvtID=5120&LinkId=20476

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  • MySQL query to view vertical data

    - by wenkhairu
    I have MySQL data that looks like this: +----------------------------------------+ |Name | kode | jum | +----------------------------------------+ | aman |kode1 | 2 | | aman |kode2 | 1 | | jhon |kode1 | 4 | | amir |kode2 | 4 | +--------------------+-----------+-------+ How can I make the table look like this one, using a MySQL query? kode1 kode2 count aman 2 1 3 jhon 0 4 4 amir 0 4 4

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  • trying to decide between asp.net and jsp

    - by Amir
    Hey Guys, I am wondering if anyone can shed some lights on the situation. I am about to start a project and trying to figure out what solution is best to go with asp.net or java jsp pages I have personally worked alot with .net and am really happy with the framework and Visual studio as IDE I find it easy to work with and there is a massive community support behind .net, i can get alot done quickly I have not every written anything use java jsp, there will be a learning curve here , so my experience is limited here. however after seeing jira i am very impressed with its capabilities, it has changed alot since the old days ( java 1.2 ) that i used to work with, and the fact that it runs under linux is a huge plus, so i am trying to decide is the learning curve, worth the price ? so given the situation above what would you recommended? Thanks, Amir

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  • Installing Matlab on ubuntu 12.04 32 bits

    - by Amir
    I have been trying to install Matlab2012a, matlab2012b and Matlab2013a for like 4 hours, triedto fix my prospective errors regarding the posts 2012a, Ubuntu-Matlab Documentation and Matlab-central. But either i am recieving an error while the installation GUI pops-up with the error : The application encountered an unexpected error and needs to close. You may want to try re-installing your product(s). More information can be found at /tmp/mathworks_amir.log On the other hand for 2012a. and the errors for 2012b and 2013a is : `Installing ... Exception in thread "main" com.google.inject.ProvisionException: Guice provision errors: 1) Error in custom provider, java.lang.RuntimeException: java.lang.reflect.InvocationTargetException at com.mathworks.wizard.WizardModule.provideDisplayProperties(WizardModule.java:60) while locating com.mathworks.instutil.DisplayProperties at com.mathworks.wizard.ui.components.ComponentsModule.providePaintStrategy(ComponentsModule.java:76) while locating com.mathworks.wizard.ui.components.PaintStrategy for parameter 4 at com.mathworks.wizard.ui.components.SwingComponentFactoryImpl.(SwingComponentFactoryImpl.java:110) while locating com.mathworks.wizard.ui.components.SwingComponentFactoryImpl while locating com.mathworks.wizard.ui.components.SwingComponentFactory for parameter 1 at com.mathworks.wizard.ui.WizardUIImpl.(WizardUIImpl.java:65) while locating com.mathworks.wizard.ui.WizardUIImpl while locating com.mathworks.wizard.ui.WizardUI annotated with @com.google.inject.name.Named(value=BaseWizardUI) at com.mathworks.wizard.ui.UIModule.provideWizardUI(UIModule.java:50) while locating com.mathworks.wizard.ui.WizardUI for parameter 0 at com.mathworks.wizard.ExceptionHandlerImpl.(ExceptionHandlerImpl.java:22) while locating com.mathworks.wizard.ExceptionHandlerImpl while locating com.mathworks.wizard.ExceptionHandler 1 error at com.google.inject.InjectorImpl$4.get(InjectorImpl.java:767) at com.google.inject.InjectorImpl.getInstance(InjectorImpl.java:793) at com.mathworks.wizard.WizardLauncher.startWizard(WizardLauncher.java:160) at com.mathworks.wizard.WizardLauncher.start(WizardLauncher.java:75) at com.mathworks.wizard.AbstractLauncher.launch(AbstractLauncher.java:27) at com.mathworks.wizard.AbstractLauncher.launchStandalone(AbstractLauncher.java:18) at com.mathworks.professionalinstaller.Launcher.main(Launcher.java:21) Caused by: java.lang.RuntimeException: java.lang.reflect.InvocationTargetException at com.google.inject.internal.ProviderMethod.get(ProviderMethod.java:106) at com.google.inject.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:48) at com.google.inject.InjectorImpl$4$1.call(InjectorImpl.java:758) at com.google.inject.InjectorImpl.callInContext(InjectorImpl.java:811) at com.google.inject.InjectorImpl$4.get(InjectorImpl.java:754) at com.google.inject.spi.ProviderLookup$1.get(ProviderLookup.java:89) at com.google.inject.spi.ProviderLookup$1.get(ProviderLookup.java:89) at com.google.inject.internal.ProviderMethod.get(ProviderMethod.java:95) at com.google.inject.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:48) at com.google.inject.SingleParameterInjector.inject(SingleParameterInjector.java:42) at com.google.inject.SingleParameterInjector.getAll(SingleParameterInjector.java:66) at com.google.inject.ConstructorInjector.construct(ConstructorInjector.java:84) at com.google.inject.ConstructorBindingImpl$Factory.get(ConstructorBindingImpl.java:111) at com.google.inject.FactoryProxy.get(FactoryProxy.java:56) at com.google.inject.SingleParameterInjector.inject(SingleParameterInjector.java:42) at com.google.inject.SingleParameterInjector.getAll(SingleParameterInjector.java:66) at com.google.inject.ConstructorInjector.construct(ConstructorInjector.java:84) at com.google.inject.ConstructorBindingImpl$Factory.get(ConstructorBindingImpl.java:111) at com.google.inject.FactoryProxy.get(FactoryProxy.java:56) at com.google.inject.ProviderToInternalFactoryAdapter$1.call(ProviderToInternalFactoryAdapter.java:45) at com.google.inject.InjectorImpl.callInContext(InjectorImpl.java:811) at com.google.inject.ProviderToInternalFactoryAdapter.get(ProviderToInternalFactoryAdapter.java:42) at com.google.inject.Scopes$1$1.get(Scopes.java:54) at com.google.inject.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:48) at com.google.inject.InjectorImpl$4$1.call(InjectorImpl.java:758) at com.google.inject.InjectorImpl.callInContext(InjectorImpl.java:811) at com.google.inject.InjectorImpl$4.get(InjectorImpl.java:754) at com.google.inject.spi.ProviderLookup$1.get(ProviderLookup.java:89) at com.google.inject.spi.ProviderLookup$1.get(ProviderLookup.java:89) at com.google.inject.internal.ProviderMethod.get(ProviderMethod.java:95) at com.google.inject.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:48) at com.google.inject.ProviderToInternalFactoryAdapter$1.call(ProviderToInternalFactoryAdapter.java:45) at com.google.inject.InjectorImpl.callInContext(InjectorImpl.java:811) at com.google.inject.ProviderToInternalFactoryAdapter.get(ProviderToInternalFactoryAdapter.java:42) at com.google.inject.Scopes$1$1.get(Scopes.java:54) at com.google.inject.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:48) at com.google.inject.SingleParameterInjector.inject(SingleParameterInjector.java:42) at com.google.inject.SingleParameterInjector.getAll(SingleParameterInjector.java:66) at com.google.inject.ConstructorInjector.construct(ConstructorInjector.java:84) at com.google.inject.ConstructorBindingImpl$Factory.get(ConstructorBindingImpl.java:111) at com.google.inject.FactoryProxy.get(FactoryProxy.java:56) at com.google.inject.ProviderToInternalFactoryAdapter$1.call(ProviderToInternalFactoryAdapter.java:45) at com.google.inject.InjectorImpl.callInContext(InjectorImpl.java:811) at com.google.inject.ProviderToInternalFactoryAdapter.get(ProviderToInternalFactoryAdapter.java:42) at com.google.inject.Scopes$1$1.get(Scopes.java:54) at com.google.inject.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:48) at com.google.inject.InjectorImpl$4$1.call(InjectorImpl.java:758) at com.google.inject.InjectorImpl.callInContext(InjectorImpl.java:804) at com.google.inject.InjectorImpl$4.get(InjectorImpl.java:754) ... 6 more Caused by: java.lang.reflect.InvocationTargetException at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at com.google.inject.internal.ProviderMethod.get(ProviderMethod.java:101) ... 54 more Caused by: com.mathworks.instutil.JNIException: java.lang.UnsatisfiedLinkError: Can't load library: /tmp/mathworks_7417/bin/glnxa64/libinstutil.so at com.mathworks.instutil.NativeUtility.loadNativeLibrary(NativeUtility.java:39) at com.mathworks.instutil.NativeUtility.(NativeUtility.java:24) at com.mathworks.instutil.DisplayPropertiesImpl.(DisplayPropertiesImpl.java:10) at com.mathworks.wizard.WizardModule.provideDisplayProperties(WizardModule.java:67) ... 59 more Caused by: java.lang.UnsatisfiedLinkError: Can't load library: /tmp/mathworks_7417/bin/glnxa64/libinstutil.so at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1842) at java.lang.Runtime.load0(Runtime.java:795) at java.lang.System.load(System.java:1061) at com.mathworks.instutil.NativeUtility.loadNativeLibrary(NativeUtility.java:37) ... 62 more Finished ` I have tried to 1- re-install java run-time 6 and then 7. 2- pass the java-path to the install with : -javadir 3- use the force to install on 32 bits as : sh install -glnx86 -v -javadir /usr/lib/jvm/java-7-openjdk-i386/jre But it seems none of them have worked so far. any ideas ??

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  • 409 CONFLICT : MAAS

    - by amir beygi
    I have some problem with my MAAS. juju bootstrap result: 2012-08-31 03:59:17,721 INFO Bootstrapping environment 'maas' (origin: distro type: maas)... Unexpected Error interacting with provider: 409 CONFLICT 2012-08-31 03:59:17,951 ERROR Unexpected Error interacting with provider: 409 CONFLICT Also i have 3 nodes in Commissioning status (delete node is disable and no start button) , DHCP seems working because LAN boot is working but boot but ends with : ALERT! /dev/disk/by-label/cloudimg-rootfs does not exist. Dropping to a shell! BusyBox.... (initramfs)

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  • What is your definition of a programmer?

    - by Amir Rezaei
    The definition of a programmer is not obvious. It has happened that I have asked questions in this forum where people believe it don’t belong here because it’s not programmer related. I thought this question may clarify the definition. What characteristics, roles and activities do you think defines a programmer? Is there a typical programmer? The technology changes so fast that it may be hard to be typical programmer. From wikipedia: A programmer, computer programmer or coder is someone who writes computer software. The term computer programmer can refer to a specialist in one area of computer programming or to a generalist who writes code for many kinds of software. One who practices or professes a formal approach to programming may also be known as a programmer analyst. A programmer's primary computer language (C, C++, Java, Lisp, Delphi etc.) is often prefixed to the above titles, and those who work in a web environment often prefix their titles with web. The term programmer can be used to refer to a software developer, software engineer, computer scientist, or software analyst. However, members of these professions typically possess other software engineering skills, beyond programming; for this reason, the term programmer is sometimes considered an insulting or derogatory oversimplification of these other professions. This has sparked much debate amongst developers, analysts, computer scientists, programmers, and outsiders who continue to be puzzled at the subtle differences in these occupations

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  • Talend Enterprise Data Integration overperforms on Oracle SPARC T4

    - by Amir Javanshir
    The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations. Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises. Several tests were performed, mainly focused on: Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor Overall throughput of the SPARC T4-1 server using multiple threads The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations. Multi-thread: Testing throughput on the Oracle T4-1 The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management. Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure: customerID;FirstName;LastName;StreetAddress;City;State;Zip;Cust_Status;Since_DT;Status_DT 1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008 2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008 3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008 4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007 […] The following graphs present the results of our tests: Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline. For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files. Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads. Single-thread: Testing the single thread performance Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache. Read File ? Filter ? Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB. Read File ? Load Database Table: Read file, insert into a single Oracle table. Average: Read file, compute the average of a numeric column, write the result in a new file. Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file. Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file. Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns. Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file. The following table and graph present the final results of the tests: Throughput unit is thousand lines per second processed (K lines/second). Improvement is the % of improvement between the T5140 and T4-1. Test T4-1 (Time s.) T5140 (Time s.) Improvement T4-1 (Throughput) T5140 (Throughput) Read/Filter/Write 125 806 645% 100 16 Read/Load Database 195 1111 570% 64 11 Average 96 557 580% 130 22 Division & Square Root 161 1054 655% 78 12 Oracle DB Dump 164 945 576% 76 13 Transform 159 1124 707% 79 11 Sort 251 1336 532% 50 9 The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs. Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application! "As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !" Cedric Carbone, Talend CTO.

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  • How will technological singularity affect programmers?

    - by Amir Rezaei
    I'm one of the believers that think that we will hit the technological singularity sooner or later. Then the question is if any profession will be unaffected by changes that will come. In the end it will be we programmers that will implement the first self-aware AI. How will technological singularity affect us programmer? What is your professional opinion regarding technological singularity? EDIT: By self-aware I refer to an entity that questions and seek answers, able to analyze and solve problem. Artificial neural network is branch in mathematics/statistics with many widely used algorithms. The algorithms are applied where recognition of data is needed. For example hidden Markov model is used for voice recognition. Another well-known area is business intelligence and data mining. Today algorithms are self-learning. That is a bit of AI what many never think of. Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make. Link to Ref.

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  • What are must have tools for web development?

    - by Amir Rezaei
    Which are must have tools for web development under windows? It can include tools such as design, coding etc. Update: Please post only one and the best tool in your opinion for each type of tools. For instance post only the name of the best design tool and not a list of them. Update: By tools I don't necessary mean small softwares. I didn't find this question, hope no one has already asked it.

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