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• Top 5 Mobile Apps To Keep Track Of Cricket Scores [ICC World Cup]

  - by Gopinath

  The ICC World Cup 2011 has started with a bang today and the first match between India vs Bangladesh was a cracker. India trashed Bangladesh with a huge margin, thanks to Sehwag for scoring an entertaining 175 runs in 140 runs. At the moment it’s very clear that whole India is gripped with cricket fever and so the rest of fans across the globe. Couple of days ago we blogged about how to watch live streaming of ICC cricket world cup online for free as well as top 10 websites to keep track live scores on your computers. What about tracking live cricket scores on mobiles phones? Here is our guide to top mobile apps available for Symbian(Nokia), Android, iOS and Windows mobiles. By the way, we are covering free apps alone in this post. Why to waste money when free apps are available? SnapTu – Symbian Mobile App SnapTu is a multi feature application that lets you to track live cricket scores, read latest news and check stats published on cric info. SnapTu has tie up with Cric Info and accessing all of CricInfo website on your mobile is very easy. Along with live scores, SnapTu also lets you access your Facebook, Twitter and Picassa on your mobile. This is my favourite application to track cricket on Symbian mobiles. Download SnapTu for your mobiles here Yahoo! Cricket – Symbian & iOS App Yahoo! Cricket Scores is another dedicated application to catch up with live scores and news on your Nokia mobiles and iPhones. This application is developed by Yahoo!, the web giant as well as the official partner of ICC. Features of the app at a glance Cricket: Get a summary page with latest scores, upcoming matches and details of the recent matches News: View sections devoted to the latest news, interviews and photos Statistics: Find the latest team and player stats Download Yahoo! Cricket For Symbian Phones   Download Yahoo! Cricket For iOS ESPN CricInfo – Android and iOS App Is there any site that is better than CricInfo to catch up with latest cricket news and live scores? I say No. ESPN CricInfo is the best website available on the web to get up to the minute  cricket information with in-depth analysis from cricket experts. The live commentary provided by CricInfo site is equally enjoyable as watching live cricket on TV. CricInfo guys have their official applications for Android mobiles and iOS devices and you accessing ball by ball updates on these application is joy. Download ESPN Crick Info App: Android Version, iPhone Version NDTV Cricket – Android, iOS and Blackberry App NDTV Cricket App is developed by NDTV, the most popular English TV news channel in India. This application provides live coverage of international and domestic cricket (Test, ODI & T20) along with latest News, Photos, Videos and Stats. This application is available for iOS devices(iPhones, iPads, iPod Touch), Android mobiles and Blackberry devices. Download NDTV Cricket for iOS here & here    Download NDTV Apps For Rest of OSs ECB Cricket – Symbian, iOS & Android App If you are an UK citizen then  this may be the right application to download for getting live cricket score updates as well as latest news about England Cricket Board. ECB Cricket is an official application of England Cricket Board Download ECB Cricket : Android Version, iPhone Version, Symbian Version Are there any better apps that we missed to feature in this list? This article titled,Top 5 Mobile Apps To Keep Track Of Cricket Scores [ICC World Cup], was originally published at Tech Dreams. Grab our rss feed or fan us on Facebook to get updates from us.

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• Lucene multiple indexes : Normalize document scores??

  - by Roey

  Hi All. Suppose I've got multiple lucene indexes (not replicas) on several PC's. I query each index and then merge the results. Is there any way to normalize the document scores so that I could sort by score (relevance)? I mean, the scores for document A from index A would not be comparable with document B from index B, unless I do some sort of normalization.... not so? Thanks Roey

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• Store scores for players and produce a high score list

  - by zrvan

  This question is derived from an interview question that I got for a job I was declined. I have asked for code review for my solution at the dedicated Stack Exchange site. But I hope this question is sufficiently rephrased and asked with a different motivation not to be a duplicate of the other question. Consider the following scenario: You should store player scores in the server back end of a game. The server is written in Java. Every score should be registered, that is, one player may have any number of scores for any number of levels. A high score list should be produced with the fifteen top scores for a given level, but only one score per user (to the effect that even if player X has the two highest scores for level Y, only the first position is counted and player Z has the second place). No information should be persisted and only Java 1.7+ standard libraries should be used. No third party libraries or frameworks are acceptable. With the number of players as the primary factor, what would be the best data structure in terms of scalability and concurrency? How would you access the structure to register a single score given a level and a player id? How would you access the structure to compile the high score list?

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• R Question. Numeric variable vs. Non-numeric and "names" function

  - by Michael

  > scores=cbind(UNCA.score, A.score, B.score, U.m.A, U.m.B) > names(scores)=c('UNCA.scores', 'A.scores', 'B.scores','UNCA.minus.A', 'UNCA.minus.B') > names(scores) [1] "UNCA.scores" "A.scores" "B.scores" "UNCA.minus.A" "UNCA.minus.B" > summary(UNCA.scores) X6.69230769230769 Min. : 4.154 1st Qu.: 7.333 Median : 8.308 Mean : 8.451 3rd Qu.: 9.538 Max. :12.000 > is.numeric(UNCA.scores) [1] FALSE > is.numeric(scores[,1]) [1] TRUE My question is, what is the difference between UNCA.scores and scores[,1]? UNCA.scores is the first column in the data.frame 'scores', but they are not the same thing, since one is numeric and the other isn't. If UNCA.scores is just a label here how can I make it be equivalent to 'scores[,1]? Thanks!

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• How do I check user's unlocked achievement and leaderboard scores via GPG plugin

  - by noob

  I need to load user's achievement and their scores from leaderboard in my game. But the Social.LoadScore() and Social.LoadAchievements() both returns a 0 size array in callback. When I checked the implementation in Google Play Gaming's PlayGamePlatform.cs, both the method has this summary - Not implemented yet. Calls the callback with an empty list. So my question is How do I get this data in Unity? Has anyone tried any other method to get the data?

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• XNA Easy Storage XBOX 360 High Scores

  - by user1003211

  To followup from a previous query - I need some help with the implementation of easystorage high scores, which is bringing up some errors on the xbox. I get the prompt screen, a savedevice is selected and a file are all created! However the file remains empty, (I've tried prepopulating but still get errors). The full portions of the scoring code can be found here: http://pastebin.com/74v897Yt The current issue in particular is in LoadHighScores() - "There is an error in XML document (0, 0)." under line data = (HighScoreData)serializer.Deserialize(stream); I'm not sure whether this line is correct either: HighScoreData data = new HighScoreData(); public static HighScoreData LoadHighScores(string container, string filename) { HighScoreData data = new HighScoreData(); if (Global.SaveDevice.FileExists(container, filename)) { Global.SaveDevice.Load(container, filename, stream => { File.Open(Global.fileName_options, FileMode.OpenOrCreate, FileAccess.Read); try { // Read the data from the file XmlSerializer serializer = new XmlSerializer(typeof(HighScoreData)); data = (HighScoreData)serializer.Deserialize(stream); } finally { // Close the file stream.Close(); // stream.Dispose(); } }); } return (data); } I call: PromptMe(); when the Start button is pressed at the beginning. I call: if (Global.SaveDevice.IsReady){entries = LoadHighScores(HighScoresContainer, HighScoresFilename);} during the menu screen to try and display the highscore screen. I call: SaveHighScore(); when game ends. I've tried altering the struct code to a class but still no luck. Any help greatly appreciated.

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• How relevant are Brainbench scores when evaluating candidates?

  - by Newtopian

  I've seen many companies using certification services such as Brainbench when evaluating candidates. Most times they use it as a secondary screen prior to interview or as a validation to choose between candidates. What is your experience with Brainbench scores? Did you try the tests yourself, and if so do you feel the score is meaningful enough to be used as part of a hiring process? Difficult choice. Consensus seems to be that BB cert are not very good as a certification. The biggest argument was around the fact that some of the questions are too precise to form a good evaluation. this view can probably be tempered somewhat but still, to hold someone's future solely on the results of this evaluation would be irresponsible. That said, I still think it is possible to use them properly to gain additional objective knowledge on a candidate's level of expertise provided the test is done in a controlled environment ensuring that all taking it stand on equal footing. Thus I went with the answer that best reflected this view keeping in mind that it is still just an hour long 50ish multiple choice question to evaluate skills and knowledge that take years to acquire. To be taken with a grain of salt ! In short, The tests have value but weather or not they are worth the money is another debate. Thanks all for your time.

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• /users/tags should contain scores

  - by Sean Patrick Floyd

  I am implementing some simple JavaScript/bookmarklet based apps that show some reputation info, including the score in the User's top tags (roughly based on this previous bookmarklet of mine). Now I can get a user's top tags (using the API), and I can also get the per-tag score if the user is logged in, by dynamically parsing the tag's top users page. But it costs me one AJAX request per tag and I have to download 10+k to extract a single numeric value. It would save a lot of traffic if the tags in <api>/users/<userid>/tags had a score field. The data seems to be there, after all the top users pages use it, so it would just be a question of exposing the data. Suggested structure: "tags": [ { "name": { "description": "name of the tag", "values": "string", "optional": false, "suggested_buffer_size": 25 }, "score": { "description": "tag score, sum of up votes for answers on non-wiki questions", "values": "32-bit signed integer", "optional": false }, "count": { "description": "tag count, exact meaning depends on context", "values": "32-bit signed integer", "optional": false }, "restricted_to": { "description": "user types that can make use of this tag, lack of this field indicates it is useable by all", "values": "one of anonymous, unregistered, registered, or moderator", "optional": true }, "fulfills_required": { "description": "indicates whether this tag is one of those that is required to be on a post", "values": "boolean", "optional": false }, "user_id": { "description": "user associated with this tag, depends on context", "values": "32-bit signed integer", "optional": true } } ]

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• Pac-Man Hiding Spot Makes High Scores a Snap

  - by Jason Fitzpatrick

  This interesting bug (feature?) in the original Pac-Man game makes it easy to hide from the ghosts, ensuring a long-lived and well-fed Pac-Man. Check out the video above to see the black hole you can park Pac-Man in to avoid assault by the ghosts. There’s two big caveats with this trick: first, it only works in the original game (spin offs and modern adaptations won’t necessarily have it but the original machine and MAME implementations of it will). Second, it doesn’t work if the ghosts see you park yourself there; you need to slip into the spot our of their direct line of sight. Still craving more Pac-Man goodness? Check out these cheat maps that map out all the patterns you need to follow to sneak through every level unmolested by ghosts. [via Neatorama] How To Be Your Own Personal Clone Army (With a Little Photoshop) How To Properly Scan a Photograph (And Get An Even Better Image) The HTG Guide to Hiding Your Data in a TrueCrypt Hidden Volume

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• EU Digital Agenda scores 85/100

  - by trond-arne.undheim

  If the Digital Agenda was a bottle of wine and I were wine critic Robert Parker, I would say the Digital Agenda has "a great bouquet, many good elements, with astringent, dry and puckering mouth feel that will not please everyone, but still displaying some finesse. A somewhat controlled effort with no surprises and a few noticeable flaws in the delivery. Noticeably shorter aftertaste than advertised by the producers. Score: 85/100. Enjoy now". The EU Digital Agenda states that "standards are vital for interoperability" and has a whole chapter on interoperability and standards. With this strong emphasis, there is hope the EU's outdated standardization system finally is headed for reform. It has been 23 years since the legal framework of standardisation was completed by Council Decision 87/95/EEC8 in the Information and Communications Technology (ICT) sector. Standardization is market driven. For several decades the IT industry has been developing standards and specifications in global open standards development organisations (fora/consortia), many of which have transparency procedures and practices far superior to the European Standards Organizations. The Digital Agenda rightly states: "reflecting the rise and growing importance of ICT standards developed by certain global fora and consortia". Some fora/consortia, of course, are distorted, influenced by single vendors, have poor track record, and need constant vigilance, but they are the minority. Therefore, the recognition needs to be accompanied by eligibility criteria focused on openness. Will the EU reform its ICT standardization by the end of 2010? Possibly, and only if DG Enterprise takes on board that Information and Communications Technologies (ICTs) have driven half of the productivity growth in Europe over the past 15 years, a prominent fact in the EU's excellent Digital Competitiveness report 2010 published on Monday 17 May. It is ok to single out the ICT sector. It simply is the most important sector right now as it fuels growth in all other sectors. Let's not wait for the entire standardization package which may take another few years. Europe does not have time. The Digital Agenda is an umbrella strategy with deliveries from a host of actors across the Commission. For instance, the EU promises to issue "guidance on transparent ex-ante disclosure rules for essential intellectual property rights and licensing terms and conditions in the context of standard setting", by 2011 in the Horisontal Guidelines now out for public consultation by DG COMP and to some extent by DG ENTR's standardization policy reform. This is important. The EU will issue procurement guidance as interoperability frameworks are put into practice. This is a joint responsibility of several DGs, and is likely to suffer coordination problems, controversy and delays. We have seen plenty of the latter already and I have commented on the Commission's own interoperability elsewhere, with mixed luck. :( Yesterday, I watched the cartoonesque Korean western film The Good, the Bad and the Weird. In the movie (and I meant in the movie only), a bandit, a thief, and a bounty hunter, all excellent at whatever they do, fight for a treasure map. Whether that is a good analogy for the situation within the Commission, others are better judges of than I. However, as a movie fanatic, I still await the final shoot-out, and, as in the film, the only certainty is that "life is about chasing and being chased". The missed opportunity (in this case not following up the push from Member States to better define open standards based interoperability) is a casualty of the chaos ensued in the European Wild West (and I mean that in the most endearing sense, and my excuses beforehand to actors who possibly justifiably cannot bear being compared to fictional movie characters). Instead of exposing the ongoing fight, the EU opted for the legalistic use of the term "standards" throughout the document. This is a term that--to the EU-- excludes most standards used by the IT industry world wide. So, while it, for a moment, meant "weapon down", it will not lead to lasting peace. The Digital Agenda calls for the Member States to "Implement commitments on interoperability and standards in the Malmö and Granada Declarations by 2013". This is a far cry from the actual Ministerial Declarations which called upon the Commission to help them with this implementation by recognizing and further defining open standards based interoperability. Unless there is more forthcoming from the Commission, the market's judgement will be: you simply fall short. Generally, I think the EU focus now should be "from policy to practice" and the Digital Agenda does indeed stop short of tackling some highly practical issues. There is need for progress beyond the Digital Agenda. Here are some suggestions that would help Europe re-take global leadership on openness, public sector reform, and economic growth: A strong European software strategy centred around open standards based interoperability by 2011. An ambitious new eCommission strategy for 2011-15 focused on migration to open standards by 2015. Aligning the IT portfolio across the Commission into one Digital Agenda DG by 2012. Focusing all best practice exchange in eGovernment on one social networking site, epractice.eu (full disclosure: I had a role in getting that site up and running) Prioritizing public sector needs in global standardization over European standardization by 2014.

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• How to test email spam scores with amavis?

  - by CaptSaltyJack

  I'd like a way to test a spam message to see its spam scores that SpamAssassin gives it. The SA db files (bayes_toks, etc) reside in /var/lib/amavis/.spamassassin. I've been testing emails by doing this: sudo su amavis -c 'spamassassin -t msgfile' Though this yields some strange results, such as: Content analysis details: (3.7 points, 5.0 required) pts rule name description ---- ---------------------- -------------------------------------------------- 3.5 BAYES_99 BODY: Bayes spam probability is 99 to 100% [score: 1.0000] -0.0 NO_RELAYS Informational: message was not relayed via SMTP 0.0 LONG_TERM_PRICE BODY: LONG_TERM_PRICE 0.2 BAYES_999 BODY: Bayes spam probability is 99.9 to 100% [score: 1.0000] -0.0 NO_RECEIVED Informational: message has no Received headers 0.2 is an awfully low scores for BAYES_999! But this is the first time I've used amavis, previously I've always just used spamassassin directly as a content filter in postfix, but apparently running amavis/spamassassin is more efficient. So, with amavis in the picture, how can I run a test on a message to see its spam score breakdown? Another email I ran a test on got this result: 2.0 BAYES_80 BODY: Bayes spam probability is 80 to 95% [score: 0.8487] Doesn't make sense, that BAYES_80 can yield a higher score than BAYES_999. Help!

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• [IOS SDK] retrieving scores from game center

  - by Sam

  I got this code from apple's developer site. How do i process the score information to be viewed in a like a UITableView or something? (void) retrieveTopTenScores { GKLeaderboard *leaderboardRequest = [[GKLeaderboard alloc] init]; if (leaderboardRequest != nil) { leaderboardRequest.playerScope = GKLeaderboardPlayerScopeGlobal; leaderboardRequest.timeScope = GKLeaderboardTimeScopeAllTime; leaderboardRequest.range = NSMakeRange(1,10); [leaderboardRequest loadScoresWithCompletionHandler: ^(NSArray *scores, NSError *error) { if (error != nil) { // handle the error. } if (scores != nil) { // process the score information. } }]; } }

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• Best way to display a "High Scores" Results

  - by George

  First, I would to thank everyone for all the help they provide via this website. It has gotten me to the point of almost being able to release my first iPhone app! Okay, so the last part I have is this: I have a game that allows users to save their high scores. I update a plist file which contains the users Name, Level, and score. Now I want to create a screen that will display the top 20 high scores. What would be the best way to do this? At first I thought possibly creating an HTML file with this info but am not even sure if that is possible. I would need to read the plist file, and then write it out as HTML. Is this possible? To write a file out as HTML? Or an even better question, is there a better way? Thanks in advance for any and all help! Geo...

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• computing z-scores for 2D matrices in scipy/numpy in Python

  - by user248237

  How can I compute the z-score for matrices in Python? Suppose I have the array: a = array([[ 1, 2, 3], [ 30, 35, 36], [2000, 6000, 8000]]) and I want to compute the z-score for each row. The solution I came up with is: array([zs(item) for item in a]) where zs is in scipy.stats.stats. Is there a better built-in vectorized way to do this? Also, is it always good to z-score numbers before using hierarchical clustering with euclidean or seuclidean distance? Can anyone discuss the relative advantages/disadvantages? thanks.

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• Updating or inserting high scores in SQL

  - by Roger Gilbrat

  I've been racking my brain over this for the past few days and I'm not sure it's possible, but figured I ask here. Is it possible for a single SQL statement to update a high score if your score is greater or insert it if your first score? My Score table has a UserID, Level and Score columns and I like it to follow the following logic: If your new score is greater than your last score for this Level, then replace it. If you don't have a score for this Level then add it. If your score for this Level is less than your highest score for this Level then do nothing. Is this possible in a single SQL statement or do I have to use two, one to see if you have a new high score and if so, replace it? Each UserID would have only one score in the table for each Level. I'm using MySQL.

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• Combined Likelihood Models

  - by Lukas Vermeer

  In a series of posts on this blog we have already described a flexible approach to recording events, a technique to create analytical models for reporting, a method that uses the same principles to generate extremely powerful facet based predictions and a waterfall strategy that can be used to blend multiple (possibly facet based) models for increased accuracy. This latest, and also last, addition to this sequence of increasing modeling complexity will illustrate an advanced approach to amalgamate models, taking us to a whole new level of predictive modeling and analytical insights; combination models predicting likelihoods using multiple child models. The method described here is far from trivial. We therefore would not recommend you apply these techniques in an initial implementation of Oracle Real-Time Decisions. In most cases, basic RTD models or the approaches described before will provide more than enough predictive accuracy and analytical insight. The following is intended as an example of how more advanced models could be constructed if implementation results warrant the increased implementation and design effort. Keep implemented statistics simple! Combining likelihoods Because facet based predictions are based on metadata attributes of the choices selected, it is possible to generate such predictions for more than one attribute of a choice. We can predict the likelihood of acceptance for a particular product based on the product category (e.g. ‘toys’), as well as based on the color of the product (e.g. ‘pink’). Of course, these two predictions may be completely different (the customer may well prefer toys, but dislike pink products) and we will have to somehow combine these two separate predictions to determine an overall likelihood of acceptance for the choice. Perhaps the simplest way to combine multiple predicted likelihoods into one is to calculate the average (or perhaps maximum or minimum) likelihood. However, this would completely forgo the fact that some facets may have a far more pronounced effect on the overall likelihood than others (e.g. customers may consider the product category more important than its color). We could opt for calculating some sort of weighted average, but this would require us to specify up front the relative importance of the different facets involved. This approach would also be unresponsive to changing consumer behavior in these preferences (e.g. product price bracket may become more important to consumers as a result of economic shifts). Preferably, we would want Oracle Real-Time Decisions to learn, act upon and tell us about, the correlations between the different facet models and the overall likelihood of acceptance. This additional level of predictive modeling, where a single supermodel (no pun intended) combines the output of several (facet based) models into a single prediction, is what we call a combined likelihood model. Facet Based Scores As an example, we have implemented three different facet based models (as described earlier) in a simple RTD inline service. These models will allow us to generate predictions for likelihood of acceptance for each product based on three different metadata fields: Category, Price Bracket and Product Color. We will use an Analytical Scores entity to store these different scores so we can easily pass them between different functions. A simple function, creatively named Compute Analytical Scores, will compute for each choice the different facet scores and return an Analytical Scores entity that is stored on the choice itself. For each score, a choice attribute referring to this entity is also added to be returned to the client to facilitate testing. One Offer To Predict Them All In order to combine the different facet based predictions into one single likelihood for each product, we will need a supermodel which can predict the likelihood of acceptance, based on the outcomes of the facet models. This model will not need to consider any of the attributes of the session, because they are already represented in the outcomes of the underlying facet models. For the same reason, the supermodel will not need to learn separately for each product, because the specific combination of facets for this product are also already represented in the output of the underlying models. In other words, instead of learning how session attributes influence acceptance of a particular product, we will learn how the outcomes of facet based models for a particular product influence acceptance at a higher level. We will therefore be using a single All Offers choice to represent all offers in our combined likelihood predictions. This choice has no attribute values configured, no scores and not a single eligibility rule; nor is it ever intended to be returned to a client. The All Offers choice is to be used exclusively by the Combined Likelihood Acceptance model to predict the likelihood of acceptance for all choices; based solely on the output of the facet based models defined earlier. The Switcheroo In Oracle Real-Time Decisions, models can only learn based on attributes stored on the session. Therefore, just before generating a combined prediction for a given choice, we will temporarily copy the facet based scores—stored on the choice earlier as an Analytical Scores entity—to the session. The code for the Predict Combined Likelihood Event function is outlined below. // set session attribute to contain facet based scores. // (this is the only input for the combined model) session().setAnalyticalScores(choice.getAnalyticalScores); // predict likelihood of acceptance for All Offers choice. CombinedLikelihoodChoice c = CombinedLikelihood.getChoice("AllOffers"); Double la = CombinedLikelihoodAcceptance.getChoiceEventLikelihoods(c, "Accepted"); // clear session attribute of facet based scores. session().setAnalyticalScores(null); // return likelihood. return la; This sleight of hand will allow the Combined Likelihood Acceptance model to predict the likelihood of acceptance for the All Offers choice using these choice specific scores. After the prediction is made, we will clear the Analytical Scores session attribute to ensure it does not pollute any of the other (facet) models. To guarantee our combined likelihood model will learn based on the facet based scores—and is not distracted by the other session attributes—we will configure the model to exclude any other inputs, save for the instance of the Analytical Scores session attribute, on the model attributes tab. Recording Events In order for the combined likelihood model to learn correctly, we must ensure that the Analytical Scores session attribute is set correctly at the moment RTD records any events related to a particular choice. We apply essentially the same switching technique as before in a Record Combined Likelihood Event function. // set session attribute to contain facet based scores // (this is the only input for the combined model). session().setAnalyticalScores(choice.getAnalyticalScores); // record input event against All Offers choice. CombinedLikelihood.getChoice("AllOffers").recordEvent(event); // force learn at this moment using the Internal Dock entry point. Application.getPredictor().learn(InternalLearn.modelArray, session(), session(), Application.currentTimeMillis()); // clear session attribute of facet based scores. session().setAnalyticalScores(null); In this example, Internal Learn is a special informant configured as the learn location for the combined likelihood model. The informant itself has no particular configuration and does nothing in itself; it is used only to force the model to learn at the exact instant we have set the Analytical Scores session attribute to the correct values. Reporting Results After running a few thousand (artificially skewed) simulated sessions on our ILS, the Decision Center reporting shows some interesting results. In this case, these results reflect perfectly the bias we ourselves had introduced in our tests. In practice, we would obviously use a wider range of customer attributes and expect to see some more unexpected outcomes. The facetted model for categories has clearly picked up on the that fact our simulated youngsters have little interest in purchasing the one red-hot vehicle our ILS had on offer. Also, it would seem that customer age is an excellent predictor for the acceptance of pink products. Looking at the key drivers for the All Offers choice we can see the relative importance of the different facets to the prediction of overall likelihood. The comparative importance of the category facet for overall prediction might, in part, be explained by the clear preference of younger customers for toys over other product types; as evident from the report on the predictiveness of customer age for offer category acceptance. Conclusion Oracle Real-Time Decisions' flexible decisioning framework allows for the construction of exceptionally elaborate prediction models that facilitate powerful targeting, but nonetheless provide insightful reporting. Although few customers will have a direct need for such a sophisticated solution architecture, it is encouraging to see that this lies within the realm of the possible with RTD; and this with limited configuration and customization required. There are obviously numerous other ways in which the predictive and reporting capabilities of Oracle Real-Time Decisions can be expanded upon to tailor to individual customers needs. We will not be able to elaborate on them all on this blog; and finding the right approach for any given problem is often more difficult than implementing the solution. Nevertheless, we hope that these last few posts have given you enough of an understanding of the power of the RTD framework and its models; so that you can take some of these ideas and improve upon your own strategy. As always, if you have any questions about the above—or any Oracle Real-Time Decisions design challenges you might face—please do not hesitate to contact us; via the comments below, social media or directly at Oracle. We are completely multi-channel and would be more than glad to help. :-)

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• Java: How to check the random letters from a-z, out of 10 letters minimum 2 letter should be a vowel

  - by kalandar

  I am writing a program to validate the following scenarios: Scenario 1: I am using the Random class from java.util. The random class will generate 10 letters from a-z and within 10 letter, minimum 2 letters must be a vowels. Scenario 2: When the player 1 and player 2 form a word from A-Z, he will score some points. There will be a score for each letter. I have already assigned the values for A-Z. At the end of the game, the system should display a scores for player 1 and player 2. How do i do it? Please help. I will post my code here. Thanks a lot. =========================================== import java.util.Random; import java.util.Scanner; public class FindYourWords { public static void main(String[] args) { Random rand = new Random(); Scanner userInput = new Scanner(System.in); //==================Player object=============================================== Player playerOne = new Player(); playerOne.wordScore = 0; playerOne.choice = "blah"; playerOne.turn = true; Player playerTwo = new Player(); playerTwo.wordScore = 0; playerTwo.choice = "blah"; playerTwo.turn = false; //================== Alphabet ================================================== String[] newChars = { "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z" }; //values of the 26 alphabets to be used int [] letterScore = {1,3,3,2,1,4,2,4,1,8,5,1,3,1,1,3,10,1,1,1,1,4,4,8,4,10}; // to assign score to the player1 and player 2 String[] vowel = { "a", "e", "i", "o", "u" }; // values for vowels int vow=0; System.out.println("FINDYOURWORDS\n"); int[] arrayRandom = new int[10]; //int array for word limiter String[] randomLetter = new String[10]; //storing the letters in newChars into this array //=============================================================================== boolean cont = true; while (cont) { if (playerOne.turn) { System.out.print("Letters of Player 1: "); } else if (!playerOne.turn) { System.out.print("Letters of Player 2: "); } for (int i = 0; i < arrayRandom.length; i++) { //running through the array limiter int r = rand.nextInt(newChars.length); //assigning random nums to the array of letters randomLetter[i] = newChars[r]; System.out.print(randomLetter[i]+ " "); } //input section for player System.out.println(""); System.out.println("Enter your word (or '@' to pass or '!' to quit): "); if (playerOne.turn) { playerOne.choice = userInput.next(); System.out.println(playerOne.turn); playerOne.turn = false; } else if (!playerOne.turn){ playerTwo.choice = userInput.next(); System.out.println(playerOne.turn); playerOne.turn = true; } //System.out.println(choice); String[] wordList = FileUtil.readDictFromFile("words.txt"); //Still dunno what this is for if (playerOne.choice.equals("@")) { playerOne.turn = false; } else if (playerTwo.choice.equals("@")) { playerOne.turn = true; } else if (playerOne.choice.equals("!")) { cont = false; } for (int i = 0; i < wordList.length; i++) { //System.out.println(wordList[i]); if (playerOne.choice.equalsIgnoreCase(wordList[i]) || playerTwo.choice.equalsIgnoreCase(wordList[i])){ } } } }}

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• How can I post scores to Facebook from a LibGDX android game?

  - by Vishal Kumar

  I am using LibGDX to create an android game. I am not making the HTML backend of the game. I just want it to be on the Android Google Play store. Is it possible to post the scores to Facebook? And if so, how can I do it. I searched and found the solutions only for web-based games. For LibGDX, there is a tutorial for Scoreloop. So, I am worried whether there is a way to do so. Any Suggestion will be welcome.

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• How do I pass tests with higher scores? [closed]

  - by user1867842

  How do I pass a test of programming knowledge for a higher score on oDesk.com? I have passed php and javascript tests but I have passed them with low scores and barley passing. This doesn't look too appealing for clients and I'm afraid that is the reason I am not being hired for a job. I know I am capable of doing web work and such. But I haven't been accepted for an interview or anything. Any idea how to study for something like this ?

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• Can I improve my AdWords quality scores with better landing pages?

  - by Eric

  I noticed that I have some keywords in my AdWords that are totally applicable to my site but the quality score of the keyword is 4 or 5. I'd like to get it up higher by creating custom versions of my site's home page (landing page) targeted specifically for people searching on those keywords. So for example, if we pretend my site sells pet food, my current home page has the phrase "dog food." I have a specific AdWords campaign for people searching on cat food (with cat food-specific ads). I'm thinking about changing the URL on those ads to something like http://mysite.com/cat.html, so a different home page comes up with the phrase "cat food." My thinking is that will help Google see that this new landing page is appropriate for the keywords and will raise my quality score for the "cat food" keywords. (Note that none of what I'm doing is shady or misleading; nobody would disagree that all of the keywords and ads I've created are perfect and appropriate for what my site offers.) Question: is what I describe the correct way to raise poor quality scores on keywords, and will it help?

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• Cocos2d score resetting is messing up (long post warning)

  - by Jhon Doe

  The score is not resetting right at all,I am trying to make a high score counter where every time you passed previous high score it will update.However, right now it is resetting during the game. For example if I had high score of 2 during the game it will take 3 points just to put it up to 3 as high score instead of keep going up until it is game over. I have came to the conclusion that I need to reset it in gameoverlayer so it won't reset during game. I have been trying to to do this but no luck. hello world ./h #import "cocos2d.h" // HelloWorldLayer @interface HelloWorldLayer : CCLayer { int _score; int _oldScore; CCLabelTTF *_scoreLabel; } @property (nonatomic, assign) CCLabelTTF *scoreLabel; hello world init ./m _score = [[NSUserDefaults standardUserDefaults] integerForKey:@"score"]; _oldScore = -1; self.scoreLabel = [CCLabelTTF labelWithString:@"" dimensions:CGSizeMake(100, 50) alignment:UITextAlignmentRight fontName:@"Marker Felt" fontSize:32]; _scoreLabel.position = ccp(winSize.width - _scoreLabel.contentSize.width, _scoreLabel.contentSize.height); _scoreLabel.color = ccc3(255,0,0); [self addChild:_scoreLabel z:1]; hello world implement ./m - (void)update:(ccTime)dt { NSMutableArray *projectilesToDelete = [[NSMutableArray alloc] init]; CGRect projectileRect = CGRectMake( projectile.position.x - (projectile.contentSize.width/2), projectile.position.y - (projectile.contentSize.height/2), projectile.contentSize.width, projectile.contentSize.height); BOOL monsterHit = FALSE; NSMutableArray *targetsToDelete = [[NSMutableArray alloc] init]; for (CCSprite *target in _targets) { CGRect targetRect = CGRectMake( target.position.x - (target.contentSize.width/2), target.position.y - (target.contentSize.height/2), target.contentSize.width, target.contentSize.height); if (CGRectIntersectsRect(projectileRect, targetRect)) { CCParticleFire* explosion = [[CCParticleFire alloc] initWithTotalParticles:200]; explosion.texture =[[CCTextureCache sharedTextureCache] addImage:@"sun.png"]; explosion.autoRemoveOnFinish = YES; explosion.startSize = 20.0f; explosion.speed = 70.0f; explosion.anchorPoint = ccp(0.5f,0.5f); explosion.position = target.position; explosion.duration = 1.0f; [self addChild:explosion z:11]; [explosion release]; monsterHit = TRUE; Monster *monster = (Monster *)target; monster.hp--; if (monster.hp <= 0) { [targetsToDelete addObject:target]; [[SimpleAudioEngine sharedEngine] playEffect:@"splash.wav"]; _score ++; } break; } } for (CCSprite *target in targetsToDelete) { [_targets removeObject:target]; [self removeChild:target cleanup:YES]; } if (targetsToDelete.count > 0) { [ projectilesToDelete addObject:projectile]; } [targetsToDelete release]; if (_score > _oldScore) { _oldScore = _score; [_scoreLabel setString:[NSString stringWithFormat:@"score%d", _score]]; [[NSUserDefaults standardUserDefaults] setInteger:_oldScore forKey:@"score"]; _score = 0; } } - (void)update:(ccTime)dt { NSMutableArray *projectilesToDelete = [[NSMutableArray alloc] init]; CGRect projectileRect = CGRectMake( projectile.position.x - (projectile.contentSize.width/2), projectile.position.y - (projectile.contentSize.height/2), projectile.contentSize.width, projectile.contentSize.height); BOOL monsterHit = FALSE; NSMutableArray *targetsToDelete = [[NSMutableArray alloc] init]; for (CCSprite *target in _targets) { CGRect targetRect = CGRectMake( target.position.x - (target.contentSize.width/2), target.position.y - (target.contentSize.height/2), target.contentSize.width, target.contentSize.height); if (CGRectIntersectsRect(projectileRect, targetRect)) { CCParticleFire* explosion = [[CCParticleFire alloc] initWithTotalParticles:200]; explosion.texture =[[CCTextureCache sharedTextureCache] addImage:@"sun.png"]; explosion.autoRemoveOnFinish = YES; explosion.startSize = 20.0f; explosion.speed = 70.0f; explosion.anchorPoint = ccp(0.5f,0.5f); explosion.position = target.position; explosion.duration = 1.0f; [self addChild:explosion z:11]; [explosion release]; monsterHit = TRUE; Monster *monster = (Monster *)target; monster.hp--; if (monster.hp <= 0) { [targetsToDelete addObject:target]; [[SimpleAudioEngine sharedEngine] playEffect:@"splash.wav"]; _score ++; } break; } } for (CCSprite *target in targetsToDelete) { [_targets removeObject:target]; [self removeChild:target cleanup:YES]; } if (targetsToDelete.count > 0) { [projectilesToDelete addObject:projectile]; } [targetsToDelete release]; if (_score > _oldScore) { _oldScore = _score; [_scoreLabel setString:[NSString stringWithFormat:@"score%d", _score]]; [[NSUserDefaults standardUserDefaults] setInteger:_oldScore forKey:@"score"]; _score = 0; } The game overlayer .h file game over @interface GameOverLayer : CCLayerColor { CCLabelTTF *_label; CCSprite * background; int _score; int _oldScore; } @property (nonatomic, retain) CCLabelTTF *label; @end @interface GameOverScene : CCScene { GameOverLayer *_layer; } @property (nonatomic, retain) GameOverLayer *layer; @end .m file gameover #import "GameOverLayer.h" #import "HelloWorldLayer.h" #import "MainMenuScene.h" @implementation GameOverScene @synthesize layer = _layer; - (id)init { if ((self = [super init])) { self.layer = [GameOverLayer node]; [self addChild:_layer]; } return self; } - (void)dealloc { [_layer release]; _layer = nil; [super dealloc]; } @end @implementation GameOverLayer @synthesize label = _label; -(id) init { if( (self=[super initWithColor:ccc4(0,0,0,0)] )) { CGSize winSize = [[CCDirector sharedDirector] winSize]; self.label = [CCLabelTTF labelWithString:@"" fontName:@"Arial" fontSize:32]; _label.color = ccc3(225,0,0); _label.position = ccp(winSize.width/2, winSize.height/2); [self addChild:_label]; [self runAction:[CCSequence actions: [CCDelayTime actionWithDuration:3], [CCCallFunc actionWithTarget:self selector:@selector(gameOverDone)], nil]]; _score=0; }

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• Create a dataset: extract features from text documents (TF-IDF)

  - by BigG

  I've to create a dataset from some text files, writing them as vectors of features. Something like this: doc1: 1,0.45 6,0.001 94,0.1 ... doc2: 3,0.5 98,0.2 ... ... each position of the vector represent a word, and the score is given by something like TF-IDF. Do you know some library/tool/whatever for this? (java is better)

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• Architecture strategies for a complex competition scoring system

  - by mikewassmer

  Competition description: There are about 10 teams competing against each other over a 6-week period. Each team's total score (out of a 1000 total available points) is based on the total of its scores in about 25,000 different scoring elements. Most scoring elements are worth a small fraction of a point and there will about 10 X 25,000 = 250,000 total raw input data points. The points for some scoring elements are awarded at frequent regular time intervals during the competition. The points for other scoring elements are awarded at either irregular time intervals or at just one moment in time. There are about 20 different types of scoring elements. Each of the 20 types of scoring elements has a different set of inputs, a different algorithm for calculating the earned score from the raw inputs, and a different number of total available points. The simplest algorithms require one input and one simple calculation. The most complex algorithms consist of hundreds or thousands of raw inputs and a more complicated calculation. Some types of raw inputs are automatically generated. Other types of raw inputs are manually entered. All raw inputs are subject to possible manual retroactive adjustments by competition officials. Primary requirements: The scoring system UI for competitors and other competition followers will show current and historical total team scores, team standings, team scores by scoring element, raw input data (at several levels of aggregation, e.g. daily, weekly, etc.), and other metrics. There will be charts, tables, and other widgets for displaying historical raw data inputs and scores. There will be a quasi-real-time dashboard that will show current scores and raw data inputs. Aggregate scores should be updated/refreshed whenever new raw data inputs arrive or existing raw data inputs are adjusted. There will be a "scorekeeper UI" for manually entering new inputs, manually adjusting existing inputs, and manually adjusting calculated scores. Decisions: Should the scoring calculations be performed on the database layer (T-SQL/SQL Server, in my case) or on the application layer (C#/ASP.NET MVC, in my case)? What are some recommended approaches for calculating updated total team scores whenever new raw inputs arrives? Calculating each of the teams' total scores from scratch every time a new input arrives will probably slow the system to a crawl. I've considered some kind of "diff" approach, but that approach may pose problems for ad-hoc queries and some aggegates. I'm trying draw some sports analogies, but it's tough because most games consist of no more than 20 or 30 scoring elements per game (I'm thinking of a high-scoring baseball game; football and soccer have fewer scoring events per game). Perhaps a financial balance sheet analogy makes more sense because financial "bottom line" calcs may be calculated from 250,000 or more transactions. Should I be making heavy use of caching for this application? Are there any obvious approaches or similar case studies that I may be overlooking?

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• What's the best way to normalize scores for ranking things?

  - by beagleguy

  hi all, I'm curious how to do normalizing of numbers for a ranking algorithm let's say I want to rank a link based on importance and I have two columns to work with so a table would look like url | comments | views now I want to rank comments higher than views so I would first think to do comments*3 or something to weight it, however if there is a large view number like 40,000 and only 4 comments then the comments weight gets dropped out. So I'm thinking I have to normalize those scores down to a more equal playing field before I can weight them. Any ideas or pointers to how that's usually done? thanks

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• Is there an RSS where I can get info about World Cup Scores?

  - by Jhonny D. Cano -Leftware-

  I'm lookin' for a rss source where I can get the info of the World Cup goals for informing my intranet users, anybody knows of a good one? thanks

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