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  • What algorithms are suitable for this simple machine learning problem?

    - by user213060
    I have a what I think is a simple machine learning question. Here is the basic problem: I am repeatedly given a new object and a list of descriptions about the object. For example: new_object: 'bob' new_object_descriptions: ['tall','old','funny']. I then have to use some kind of machine learning to find previously handled objects that had similar descriptions, for example, past_similar_objects: ['frank','steve','joe']. Next, I have an algorithm that can directly measure whether these objects are indeed similar to bob, for example, correct_objects: ['steve','joe']. The classifier is then given this feedback training of successful matches. Then this loop repeats with a new object. a Here's the pseudo-code: Classifier=new_classifier() while True: new_object,new_object_descriptions = get_new_object_and_descriptions() past_similar_objects = Classifier.classify(new_object,new_object_descriptions) correct_objects = calc_successful_matches(new_object,past_similar_objects) Classifier.train_successful_matches(object,correct_objects) But, there are some stipulations that may limit what classifier can be used: There will be millions of objects put into this classifier so classification and training needs to scale well to millions of object types and still be fast. I believe this disqualifies something like a spam classifier that is optimal for just two types: spam or not spam. (Update: I could probably narrow this to thousands of objects instead of millions, if that is a problem.) Again, I prefer speed when millions of objects are being classified, over accuracy. What are decent, fast machine learning algorithms for this purpose?

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  • Help with Neuroph neural network

    - by user359708
    For my graduate research I am creating a neural network that trains to recognize images. I am going much more complex than just taking a grid of RGB values, downsampling, and and sending them to the input of the network, like many examples do. I actually use over 100 independently trained neural networks that detect features, such as lines, shading patterns, etc. Much more like the human eye, and it works really well so far! The problem is I have quite a bit of training data. I show it over 100 examples of what a car looks like. Then 100 examples of what a person looks like. Then over 100 of what a dog looks like, etc. This is quite a bit of training data! Currently I am running at about one week to train the network. This is kind of killing my progress, as I need to adjust and retrain. I am using Neuroph, as the low-level neural network API. I am running a dual-quadcore machine(16 cores with hyperthreading), so this should be fast. My processor percent is at only 5%. Are there any tricks on Neuroph performance? Or Java peroformance in general? Suggestions? I am a cognitive psych doctoral student, and I am decent as a programmer, but do not know a great deal about performance programming.

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  • PHP Hashtable array optimisation.

    - by hiprakhar
    I made a PHP app which was taking about ~0.0070sec for execution. Now, I added a hashtable array with about 2000 values. Suddenly the time for execution has gone up to ~0.0700 secs. Almost 10 times the previous value. I tried commenting out the part where I was searching inside the hashtable array (but array was still left defined). Still, the execution time remains about ~0.0500secs. Array is something like: $subjectinfo = array( 'TPT753' => 'Industrial Training', 'TPT801' => 'High Polymeric Engineering', 'TPT802' => 'Corrosion Engineering', 'TPT803' => 'Decorative ,Industrial And High Performance Coatings', 'TPT851' => 'Project'); Is there any way to optimize this part? I cannot use Database as I am running this app on Google app engine which is still not supporting JDO database for php. Some more code from the app: function getsubjectinfo($name) { $subjectinfo = array( 'TPT753' => 'Industrial Training', 'TPT801' => 'High Polymeric Engineering', 'TPT802' => 'Corrosion Engineering', 'TPT803' => 'Decorative ,Industrial And High Performance Coatings', 'TPT851' => 'Project'); $name = str_replace("-", "", $name); $name = str_replace(" ", "", $name); if (isset($subjectinfo["$name"])) return "(".$subjectinfo["$name"].")"; else return ""; } Then I am using the following statement 2-3 times in the app: echo $key." ".$this->getsubjectinfo($key)

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  • Fast Lightweight Image Comparisson Metric Algorithm

    - by gav
    Hi All, I am developing an application for the Android platform which contains 1000+ image filters that have been 'evolved'. When a user selects a photo I want to present the most relevant filters first. This 'relevance' should be dependent on previous use cases. I have already developed tools that register when a filtered image is saved; this combination of filter and image can be seen as the training data for my system. The issue is that the comparison must occur between selecting an image and the next screen coming up. From a UI point of view I need the whole process to take less that 4 seconds; select an image- obtain a metric to use for similarity - check against use cases - return 6 closest matches. I figure with 4 seconds I can use animations and progress dialogs to keep the user happy. Due to platform contraints I am fairly limited in the computational expense of the algorithm. I have implemented a technique adapted from various online tutorials for running C code on the G1 and hence this language is available Specific Constraints; Qualcomm® MSM7201A™, 528 MHz Processor 320 x 480 Pixel bitmap in 32 bit ARGB ~ 2 seconds computational time for the native method to get the metric ~ 2 seconds to compare the metric of the current image with training data This is an academic project so all ideas are welcome, anything you can think of or have heard about would be of interest to me. My ideas; I want to keep the complexity down (O(n*m)?) by using pixel data only rather than a neighbourhood function I was looking at using the Colour historgram/Greyscale histogram/Texture/Entropy of the image, combining them to make the measure. There will be an obvious loss of information but I need the resultant metric to be substantially smaller than the memory footprint of the image (~0.512 MB) As I said, any ideas to direct my research would be fantastic. Kind regards, Gavin

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  • Getting my foot in the SCADA door, how?

    - by bibby
    I keep hearing that I should learn SCADA and its PLC language to upgrade my career. While I enjoy currently being a web and mobile development privateer, the prospects of working for a municipality or industrial entity has its appeals (since I am trying to grow a family). Over the years, I've tought myself to skillfully use php, javascript, java, perl, awk, bash. Surely, these language skills can tranfer somewhat to SCADA's logic controller language. Without any formal training in CS (music major!) other than at the workplace, I wouldn't have been able to pick up those languages and run with them had it not been for their open documentation and free-to-install or already-installed interpreters/compilers. I can't see that this is true with SCADA, and I'm hoping that I'm wrong. Ideally, I'd like to be able to apply for a job that requires [A,B,C] and suggest that they hire me because I already know [A & B]; that they wouldn't have to do a ground-up training with someone that's never programmed before. So, finally, the question; How do I "learn" SCADA? Are there sites and docs? What's going to help me get my foot in the door? Any insight is appreciated. Thanks!

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  • Deep Zoom in Ajax - Possible? Any examples out there?

    - by Phil
    I have an idea to implement a deep zoom type interface hosted in a browser for sports training data (speed, distance, heart rate etc.) However, rather than images I actually want to zoom into a hierarchy of information. For example, the initial display would contain a grid of years - hover over 2008, for example, and spin the mouse wheel (or click) will zoom into that year but during the zoom I want 2008 to fade out and be replaced with a calendar of months. Again zoom into a month and the months are replaced with the months calendar, zoom into a day and you finally see a chart with the training data plotted on it. All the time only dates with actual data would be highlighted in some fashion. My question is whether this would even be possible and whether anyone has seen examples of this already. I'm imagining that most of the time the next level of information could be cached in the browser (in fact, because this is calendar-based, I can calculate most of that and cache the dates to be highlighted.) I could also zoom into an empty chart whilst an Ajax thread is fetching the data to display. I've never tried anything like this before and I'm especially interested in whether DHTML would be capable of this sort of zoom (I suspect not and I would have to resort to Silverlight) and whether the Ajax execution would be uninterrupted whilst the browser rendering thread is kept busy zooming.

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  • Naive Bayesian classification (spam filtering) - Doubt in one calculation? Which one is right? Plz c

    - by Microkernel
    Hi guys, I am implementing Naive Bayesian classifier for spam filtering. I have doubt on some calculation. Please clarify me what to do. Here is my question. In this method, you have to calculate P(S|W) - Probability that Message is spam given word W occurs in it. P(W|S) - Probability that word W occurs in a spam message. P(W|H) - Probability that word W occurs in a Ham message. So to calculate P(W|S), should I do (1) (Number of times W occuring in spam)/(total number of times W occurs in all the messages) OR (2) (Number of times word W occurs in Spam)/(Total number of words in the spam message) So, to calculate P(W|S), should I do (1) or (2)? (I thought it to be (2), but I am not sure, so plz clarify me) I am refering http://en.wikipedia.org/wiki/Bayesian_spam_filtering for the info by the way. I got to complete the implementation by this weekend :( Thanks and regards, MicroKernel :) @sth: Hmm... Shouldn't repeated occurrence of word 'W' increase a message's spam score? In the your approach it wouldn't, right?. Lets take a scenario and discuss... Lets say, we have 100 training messages, out of which 50 are spam and 50 are Ham. and say word_count of each message = 100. And lets say, in spam messages word W occurs 5 times in each message and word W occurs 1 time in Ham message. So total number of times W occuring in all the spam message = 5*50 = 250 times. And total number of times W occuring in all Ham messages = 1*50 = 50 times. Total occurance of W in all of the training messages = (250+50) = 300 times. So, in this scenario, how do u calculate P(W|S) and P(W|H) ? Naturally we should expect, P(W|S) P(W|H)??? right. Please share your thought...

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  • Software Company Library

    - by dbemerlin
    Hi. A few days ago i had the idea to create a company library since my company has no training and many developers still develop as they did when they learned it 5 years ago. My hope is that they can lend books, read them and hopefully learn something from them (for example: object oriented programming or unit testing, which noone here knows how to use). After asking around most agreed that it was a good idea, so i brought my books, made a simple printed sheet with "Book A belongs to B" and "Developer A took the Book on dd.mm.yyyy" to get it started. Now i want to get some ideas for Books that i could add to the shelf (sadly from my own money since 100€/month for training is too much money for this multi-million euro company). We develop mostly PHP & MySQL so books specific to this topic would be preferred but i think if people learn other languages they might get ideas on how to develop better with the current language so other books are ok, too. Which books would you recommend? PS: Personally i'd like to add some Project Management books, too, as it's a topic i'm interested in, eventhough i'm just a junior developer (We've got Peopleware already, great book btw).

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  • Partitioning data set in r based on multiple classes of observations

    - by Danny
    I'm trying to partition a data set that I have in R, 2/3 for training and 1/3 for testing. I have one classification variable, and seven numerical variables. Each observation is classified as either A, B, C, or D. For simplicity's sake, let's say that the classification variable, cl, is A for the first 100 observations, B for observations 101 to 200, C till 300, and D till 400. I'm trying to get a partition that has 2/3 of the observations for each of A, B, C, and D (as opposed to simply getting 2/3 of the observations for the entire data set since it will likely not have equal amounts of each classification). When I try to sample from a subset of the data, such as sample(subset(data, cl=='A')), the columns are reordered instead of the rows. To summarize, my goal is to have 67 random observations from each of A, B, C, and D as my training data, and store the remaining 33 observations for each of A, B, C, and D as testing data. I have found a very similar question to mine, but it did not factor in multiple variables. I feel silly asking this question because it seems so simple, but I'm stumped. Also, this is my first question on this site, so I apologize in advance for any faux pas on my part.

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  • How to generate a monotone MART ROC in R?

    - by user1521587
    I am using R and applying MART (Alg. for multiple additive regression trees) on a training set to build prediction models. When I look at the ROC curve, it is not monotone. I would be grateful if someone can help me with how I should fix this. I am guessing the issue is that initially, MART generates n trees and if these trees are not the same for all the models I am building, the results will not be comparable. Here are the steps I take: 1) Fix the false-negative cost, c_fn. Let cost = c(0, 1, c_fn, 0). 2) use the following line to build the mart model: mart(x, y, lx, martmode='class', niter=2000, cost.mtx=cost) where x is the matrix of training set variables, y is the observation matrix, lx is the matrix which specifies which of the variables in x is numerical, which one categorical. 3) I predict the test set observations using the mart model found in step 2 using this line: y_pred = martpred(x_test, probs=T) 4) I compute the false-positive and false-negative errors as follows: t = 1/(1+c_fn) %threshold based on Bayes optimal rule where c_fp=1 and c_fn. p_0 = length(which(y_test==1))/dim(y_test)[1] p_01 = sum(1*(y_pred[,2]t & y_test==0))/dim(y_test)[1] p_11 = sum(1*(y_pred[,2]t & y_test==1))/dim(y_test)[1] p_fp = p_01/(1-p_0) p_tp = p_11/p_0 5) repeat step 1-4 for a new false-negative cost.

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  • How to implement a Linked List in Java?

    - by nbarraille
    Hello! I am trying to implement a simple HashTable in Java that uses a Linked List for collision resolution, which is pretty easy to do in C, but I don't know how to do it in Java, as you can't use pointers... First, I know that those structures are already implemented in Java, I'm not planning on using it, just training here... So I created an element, which is a string and a pointer to the next Element: public class Element{ private String s; private Element next; public Element(String s){ this.s = s; this.next = null; } public void setNext(Element e){ this.next = e; } public String getString(){ return this.s; } public Element getNext(){ return this.next; } @Override public String toString() { return "[" + s + "] => "; } } Of course, my HashTable has an array of Element to stock the data: public class CustomHashTable { private Element[] data; Here is my problem: For example I want to implement a method that adds an element AT THE END of the linked List (I know it would have been simpler and more efficient to insert the element at the beginning of the list, but again, this is only for training purposes). How do I do that without pointer? Here is my code (which could work if e was a pointer...): public void add(String s){ int index = hash(s) % data.length; System.out.println("Adding at index: " + index); Element e = this.data[index]; while(e != null){ e = e.getNext(); } e = new Element(s); } Thanks!

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  • Is Social Media The Vital Skill You Aren’t Tracking?

    - by HCM-Oracle
    By Mark Bennett - Originally featured in Talent Management Excellence The ever-increasing presence of the workforce on social media presents opportunities as well as risks for organizations. While on the one hand, we read about social media embarrassments happening to organizations, on the other we see that social media activities by workers and candidates can enhance a company’s brand and provide insight into what individuals are, or can become, influencers in the social media sphere. HR can play a key role in helping organizations make the most value out of the activities and presence of workers and candidates, while at the same time also helping to manage the risks that come with the permanence and viral nature of social media. What is Missing from Understanding Our Workforce? “If only HP knew what HP knows, we would be three-times more productive.”  Lew Platt, Former Chairman, President, CEO, Hewlett-Packard  What Lew Platt recognized was that organizations only have a partial understanding of what their workforce is capable of. This lack of understanding impacts the company in several negative ways: 1. A particular skill that the company needs to access in one part of the organization might exist somewhere else, but there is no record that the skill exists, so the need is unfulfilled. 2. As market conditions change rapidly, the company needs to know strategic options, but some options are missed entirely because the company doesn’t know that sufficient capability already exists to enable those options. 3. Employees may miss out on opportunities to demonstrate how their hidden skills could create new value to the company. Why don’t companies have that more complete picture of their workforce capabilities – that is, not know what they know? One very good explanation is that companies put most of their efforts into rating their workforce according to the jobs and roles they are filling today. This is the essence of two important talent management processes: recruiting and performance appraisals.  In recruiting, a set of requirements is put together for a job, either explicitly or indirectly through a job description. During the recruiting process, much of the attention is paid towards whether the candidate has the qualifications, the skills, the experience and the cultural fit to be successful in the role. This makes a lot of sense.  In the performance appraisal process, an employee is measured on how well they performed the functions of their role and in an effort to help the employee do even better next time, they are also measured on proficiency in the competencies that are deemed to be key in doing that job. Again, the logic is impeccable.  But in both these cases, two adages come to mind: 1. What gets measured is what gets managed. 2. You only see what you are looking for. In other words, the fact that the current roles the workforce are performing are the basis for measuring which capabilities the workforce has, makes them the only capabilities to be measured. What was initially meant to be a positive, i.e. identify what is needed to perform well and measure it, in order that it can be managed, comes with the unintended negative consequence of overshadowing the other capabilities the workforce has. This also comes with an employee engagement price, for the measurements and management of workforce capabilities is to typically focus on where the workforce comes up short. Again, it makes sense to do this, since improving a capability that appears to result in improved performance benefits, both the individual through improved performance ratings and the company through improved productivity. But this is based on the assumption that the capabilities identified and their required proficiencies are the only attributes of the individual that matter. Anything else the individual brings that results in high performance, while resulting in a desired performance outcome, often goes unrecognized or underappreciated at best. As social media begins to occupy a more important part in current and future roles in organizations, businesses must incorporate social media savvy and innovation into job descriptions and expectations. These new measures could provide insight into how well someone can use social media tools to influence communities and decision makers; keep abreast of trends in fast-moving industries; present a positive brand image for the organization around thought leadership, customer focus, social responsibility; and coordinate and collaborate with partners. These measures should demonstrate the “social capital” the individual has invested in and developed over time. Without this dimension, “short cut” methods may generate a narrow set of positive metrics that do not have real, long-lasting benefits to the organization. How Workforce Reputation Management Helps HR Harness Social Media With hundreds of petabytes of social media data flowing across Facebook, LinkedIn and Twitter, businesses are tapping technology solutions to effectively leverage social for HR. Workforce reputation management technology helps organizations discover, mobilize and retain talent by providing insight into the social reputation and influence of the workforce while also helping organizations monitor employee social media policy compliance and mitigate social media risk.  There are three major ways that workforce reputation management technology can play a strategic role to support HR: 1. Improve Awareness and Decisions on Talent Many organizations measure the skills and competencies that they know they need today, but are unaware of what other skills and competencies their workforce has that could be essential tomorrow. How about whether your workforce has the reputation and influence to make their skills and competencies more effective? Many organizations don’t have insight into the social media “reach” their workforce has, which is becoming more critical to business performance. These features help organizations, managers, and employees improve many talent processes and decision making, including the following: Hiring and Assignments. People and teams with higher reputations are considered more valuable and effective workers. Someone with high reputation who refers a candidate also can have high credibility as a source for hires.   Training and Development. Reputation trend analysis can impact program decisions regarding training offerings by showing how reputation and influence across the workforce changes in concert with training. Worker reputation impacts development plans and goal choices by helping the individual see which development efforts result in improved reputation and influence.   Finding Hidden Talent. Managers can discover hidden talent and skills amongst employees based on a combination of social profile information and social media reputation. Employees can improve their personal brand and accelerate their career development.  2. Talent Search and Discovery The right technology helps organizations find information on people that might otherwise be hidden. By leveraging access to candidate and worker social profiles as well as their social relationships, workforce reputation management provides companies with a more complete picture of what their knowledge, skills, and attributes are and what they can in turn access. This more complete information helps to find the right talent both outside the organization as well as the right, perhaps previously hidden talent, within the organization to fill roles and staff projects, particularly those roles and projects that are required in reaction to fast-changing opportunities and circumstances. 3. Reputation Brings Credibility Workforce reputation management technology provides a clearer picture of how candidates and workers are viewed by their peers and communities across a wide range of social reputation and influence metrics. This information is less subject to individual bias and can impact critical decision-making. Knowing the individual’s reputation and influence enables the organization to predict how well their capabilities and behaviors will have a positive effect on desired business outcomes. Many roles that have the highest impact on overall business performance are dependent on the individual’s influence and reputation. In addition, reputation and influence measures offer a very tangible source of feedback for workers, providing them with insight that helps them develop themselves and their careers and see the effectiveness of those efforts by tracking changes over time in their reputation and influence. The following are some examples of the different reputation and influence measures of the workforce that Workforce Reputation Management could gather and analyze: Generosity – How often the user reposts other’s posts. Influence – How often the user’s material is reposted by others.  Engagement – The ratio of recent posts with references (e.g. links to other posts) to the total number of posts.  Activity – How frequently the user posts. (e.g. number per day)  Impact – The size of the users’ social networks, which indicates their ability to reach unique followers, friends, or users.   Clout – The number of references and citations of the user’s material in others’ posts.  The Vital Ingredient of Workforce Reputation Management: Employee Participation “Nothing about me, without me.” Valerie Billingham, “Through the Patient’s Eyes”, Salzburg Seminar Session 356, 1998 Since data resides primarily in social media, a question arises: what manner is used to collect that data? While much of social media activity is publicly accessible (as many who wished otherwise have learned to their chagrin), the social norms of social media have developed to put some restrictions on what is acceptable behavior and by whom. Disregarding these norms risks a repercussion firestorm. One of the more recognized norms is that while individuals can follow and engage with other individual’s public social activity (e.g. Twitter updates) fairly freely, the more an organization does this unprompted and without getting permission from the individual beforehand, the more likely the organization risks a totally opposite outcome from the one desired. Instead, the organization must look for permission from the individual, which can be met with resistance. That resistance comes from not knowing how the information will be used, how it will be shared with others, and not receiving enough benefit in return for granting permission. As the quote above about patient concerns and rights succinctly states, no one likes not feeling in control of the information about themselves, or the uncertainty about where it will be used. This is well understood in consumer social media (i.e. permission-based marketing) and is applicable to workforce reputation management. However, asking permission leaves open the very real possibility that no one, or so few, will grant permission, resulting in a small set of data with little usefulness for the company. Connecting Individual Motivation to Organization Needs So what is it that makes an individual decide to grant an organization access to the data it wants? It is when the individual’s own motivations are in alignment with the organization’s objectives. In the case of workforce reputation management, when the individual is motivated by a desire for increased visibility and career growth opportunities to advertise their skills and level of influence and reputation, they are aligned with the organizations’ objectives; to fill resource needs or strategically build better awareness of what skills are present in the workforce, as well as levels of influence and reputation. Individuals can see the benefit of granting access permission to the company through multiple means. One is through simple social awareness; they begin to discover that peers who are getting more career opportunities are those who are signed up for workforce reputation management. Another is where companies take the message directly to the individual; we think you would benefit from signing up with our workforce reputation management solution. Another, more strategic approach is to make reputation management part of a larger Career Development effort by the company; providing a wide set of tools to help the workforce find ways to plan and take action to achieve their career aspirations in the organization. An effective mechanism, that facilitates connecting the visibility and career growth motivations of the workforce with the larger context of the organization’s business objectives, is to use game mechanics to help individuals transform their career goals into concrete, actionable steps, such as signing up for reputation management. This works in favor of companies looking to use workforce reputation because the workforce is more apt to see how it fits into achieving their overall career goals, as well as seeing how other participation brings additional benefits.  Once an individual has signed up with reputation management, not only have they made themselves more visible within the organization and increased their career growth opportunities, they have also enabled a tool that they can use to better understand how their actions and behaviors impact their influence and reputation. Since they will be able to see their reputation and influence measurements change over time, they will gain better insight into how reputation and influence impacts their effectiveness in a role, as well as how their behaviors and skill levels in turn affect their influence and reputation. This insight can trigger much more directed, and effective, efforts by the individual to improve their ability to perform at a higher level and become more productive. The increased sense of autonomy the individual experiences, in linking the insight they gain to the actions and behavior changes they make, greatly enhances their engagement with their role as well as their career prospects within the company. Workforce reputation management takes the wide range of disparate data about the workforce being produced across various social media platforms and transforms it into accessible, relevant, and actionable information that helps the organization achieve its desired business objectives. Social media holds untapped insights about your talent, brand and business, and workforce reputation management can help unlock them. Imagine - if you could find the hidden secrets of your businesses, how much more productive and efficient would your organization be? Mark Bennett is a Director of Product Strategy at Oracle. Mark focuses on setting the strategic vision and direction for tools that help organizations understand, shape, and leverage the capabilities of their workforce to achieve business objectives, as well as help individuals work effectively to achieve their goals and navigate their own growth. His combination of a deep technical background in software design and development, coupled with a broad knowledge of business challenges and thinking in today’s globalized, rapidly changing, technology accelerated economy, has enabled him to identify and incorporate key innovations that are central to Oracle Fusion’s unique value proposition. Mark has over the course of his career been in charge of the design, development, and strategy of Talent Management products and the design and development of cutting edge software that is better equipped to handle the increasingly complex demands of users while also remaining easy to use. Follow him @mpbennett

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  • CodePlex Daily Summary for Wednesday, June 15, 2011

    CodePlex Daily Summary for Wednesday, June 15, 2011Popular ReleasesTerraria World Viewer: Version 1.2: Update June 15thNew User Interface Map drawing will not cause the program to freeze anymore Fixed the "Draw Symbols" (now called "Markers") checkbox not having any effectMVC Controls Toolkit: Mvc Controls Toolkit 1.1.5 RC: Added Extended Dropdown allows a prompt item to be inserted as first element. RequiredAttribute, if present, trggers if no element is chosen Client side javascript function to set/get the values of DateTimeInput, TypedTextBox, TypedEditDisplay, and to bind/unbind a "change" handler The selected page in the pager is applied the attribute selected-page="selected" that can be used in the definition of CSS rules to style the selected page items controls now interpret a null value as an empr...Umbraco CMS: Umbraco CMS 5.0 CTP 1: Umbraco 5 Community Technology Preview Umbraco 5 will be the next version of everyone's favourite, friendly ASP.NET CMS that already powers over 100,000 websites worldwide. Try out our first CTP of version 5 today! If you're new to Umbraco and would like to get a quick low-down on our popular and easy-to-learn approach to content management, check out our intro video here. What's in the v5 CTP box? This is a preview version of version 5 and includes support for the following familiar Umbr...Ribbon Browser for Microsoft Dynamics CRM 2011: Ribbon Browser (1.0.514.30): Initial releaseTerrariViewer: TerrariViewer v3.0 [Terraria Inventory Editor]: In this version, I did an overhaul of the GUI of the program. The only pop-up window you will receive now is a warning box for for when you click on the "Delete" button. Everything has been integrated into the tabs on the form. I added every item included with v1.0.4 of Terraria and added the option to set inventory/bank slots to "No Item". This WILL work with characters that have not been opened in v1.0.4patterns & practices: Project Silk: Project Silk Community Drop 11 - June 14, 2011: Changes from previous drop: Many code changes: please see the readme.mht for details. New "Client Data Management and Caching" chapter. Updated "Application Notifications" chapter. Updated "Architecture" chapter. Updated "jQuery UI Widget" chapter. Updated "Widget QuickStart" appendix and code. Guidance Chapters Ready for Review The Word documents for the chapters are included with the source code in addition to the CHM to help you provide feedback. The PDF is provided as a separat...Orchard Project: Orchard 1.2: Build: 1.2.41 Published: 6/14/2010 How to Install Orchard To install Orchard using Web PI, follow these instructions: http://www.orchardproject.net/docs/Installing-Orchard.ashx. Web PI will detect your hardware environment and install the application. Alternatively, to install the release manually, download the Orchard.Web.1.2.41.zip file. http://orchardproject.net/docs/Manually-installing-Orchard-zip-file.ashx The zip contents are pre-built and ready-to-run. Simply extract the contents o...PowerGUI Visual Studio Extension: PowerGUI VSX 1.3.4: Changes - Got rid of suppressed exceptions on assemblies loading at project startup - Fixed Issue #28535 "No Print Support" - Enabled IntelliSence commands wich are supported by ActiPro Syntax Editor control: ToggleBookmark, NextBookmark, PreviousBookmark, ShowMemberList - Added missing Import directives in PS Script project template - Fixed exception occurring on debug start - Fixed an issue: after creating a new PS project, a debugging session hung being run for the second timeSnippet Designer: Snippet Designer 1.4.0: Snippet Designer 1.4.0 for Visual Studio 2010 Change logSnippet Explorer ChangesReworked language filter UI to work better in the side bar. Added result count drop down which lets you choose how many results to see. Language filter and result count choices are persisted after Visual Studio is closed. Added file name to search criteria. Search is now case insensitive. Snippet Editor Changes Snippet Editor ChangesAdded menu option for the $end$ symbol which indicates where the c...SizeOnDisk: 1.0.9.0: Can handle Right-To-Left languages (issue 316) About box (issue 310) New language: Deutsch (thanks to kyoka) Fix: file and folder context menuDropBox Linker: DropBox Linker 1.1: Added different popup descriptions for actions (copy/append/update/remove) Added popup timeout control (with live preview) Added option to overwrite clipboard with the last link only Notification popup closes on user click Notification popup default timeout increased to 3 sec. Added codeplex link to about .NET Framework 4.0 Client Profile requiredWCF Community Site: WCF Express Interop Bindings 1.0: Welcome to the first release of the WCF Express Interop BindingsThis project provides a starter kit for WCF service developers wishing to connect with Java clients in WebSphere, WebLogic, Metro and Apache. It supports security, MTOM and RM features. For more information see the Landing page We welcome your feedback (Topic: Interop Bindings). Please submit any feature requests / bug fixes via the issue tracker. FeaturesVSIX Installer WCF Bindings for Oracle WebLogic, Oracle Metro, IBM WebS...Mobile Device Detection and Redirection: 1.0.4.1: Stable Release 51 Degrees.mobi Foundation is the best way to detect and redirect mobile devices and their capabilities on ASP.NET and is being used on thousands of websites worldwide. We’re highly confident in our software and we recommend all users update to this version. Changes to Version 1.0.4.1Changed the BlackberryHandler and BlackberryVersion6Handler to have equal CONFIDENCE values to ensure they both get a chance at detecting BlackBerry version 4&5 and version 6 devices. Prior to thi...Kouak - HTTP File Share Server: Kouak Beta 3 - Clean: Some critical bug solved and dependecy problems There's 3 package : - The first, contains the cli server and the graphical server. - The second, only the cli server - The third, only the graphical client. It's a beta release, so don't hesitate to emmit issue ;pRawr: Rawr 4.1.06: This is the Downloadable WPF version of Rawr!For web-based version see http://elitistjerks.com/rawr.php You can find the version notes at: http://rawr.codeplex.com/wikipage?title=VersionNotes Rawr AddonWe now have a Rawr Official Addon for in-game exporting and importing of character data hosted on Curse. The Addon does not perform calculations like Rawr, it simply shows your exported Rawr data in wow tooltips and lets you export your character to Rawr (including bag and bank items) like Char...AcDown????? - Anime&Comic Downloader: AcDown????? v3.0 Beta6: ??AcDown?????????????,?????????????,????、????。?????Acfun????? ????32??64? Windows XP/Vista/7 ????????????? ??:????????Windows XP???,?????????.NET Framework 2.0???(x86)?.NET Framework 2.0???(x64),?????"?????????"??? ??v3.0 Beta6 ?????(imanhua.com)????? ???? ?? ??"????","?????","?????","????"?????? "????"?????"????????"?? ??????????? ?????????????? ?????????????/???? ?? ????Windows 7???????????? ????????? ?? ????????????? ???????/??????????? ???????????? ?? ?? ?????(imanh...Pulse: Pulse Beta 2: - Added new wallpapers provider http://wallbase.cc. Supports english search, multiple keywords* - Improved font rendering in Options window - Added "Set wallpaper as logon background" option* - Fixed crashes if there is no internet connection - Fixed: Rewalls downloads empty images sometimes - Added filters* Note 1: wallbase provider supports only english search. Rewalls provider supports only russian search but Pulse automatically translates your english keyword into russian using Google Tr...WPF Application Framework (WAF): WPF Application Framework (WAF) 2.0.0.7: Version: 2.0.0.7 (Milestone 7): This release contains the source code of the WPF Application Framework (WAF) and the sample applications. Requirements .NET Framework 4.0 (The package contains a solution file for Visual Studio 2010) The unit test projects require Visual Studio 2010 Professional Remark The sample applications are using Microsoft’s IoC container MEF. However, the WPF Application Framework (WAF) doesn’t force you to use the same IoC container in your application. You can use ...SimplePlanner: v2.0b: For 2011-2012 Sem 1 ???2011-2012 ????Visual Studio 2010 Help Downloader: 1.0.0.3: Domain name support for proxy Cleanup old packages bug Writing to EventLog with UAC enabled bug Small fixes & RefactoringNew Projects360U: 360UAd Configuration + Rotator for Windows Phone: Ad Configuration and Rotator for Windows Phone is a set of classes and controls which allow you to remotely manage advertising providers used inside your Windows Phone application. Advertising providers can be plugged in on an 'as needed' so application only ship with the providers being used.CommerceShopSystem: CommerceShopSystemContour strikes again: Collection of extensions for the Umbraco Contour form builderFarseer Physics & GLEED2D Link: This project includes c# files usable to implement the Farseer Physics engine in a level created using GLEED2D.FolderComparer: This DLL holds an extension of the DirectoryInfo class. It contains a logic that helps compare the contents of two folders. HierList Hierarchial Outline ASP.NET Server Control ( using UL or OL and LI ): The HierList ASP WebControl generates a hierarchial list using the UL, OL, and LI html tags. Images Organizator: A C# .Net program that organizes all pictures in a folder by date.KiggDemo: i study kiggLavieOrnamentos: LavieOrnamentos is a MVC project written in C# for a standard business website. I plan to use it as a base for a bigger project, a standard business site framework targeting small companies that just want to display their products and latest news.Multiple Choice Training Application: This is an ASP.Net (VB.Net) Web based training application. This application can be configured to ask multiple choice questions for multiple groups, score based on percentage, create completion certificates and be completely managed via a web interface,Orchard Windows Authentication: This module allows Windows domain users to be authenticated in Orchard.Party Estimator: Party Estimator is a training project based on requirements from O'Reilly's _Head First C#_, and is not intended for widespread use. SharePoint Enforcer - Ensuring large sites comply with standards: SharePoint Enforcer is a utility that aids in governance of large SharePoint sites to ensure that the sites comply with various business rules that have been created to keep the site from growing out of control.SharePoint WarmUp Tool (Claims+FBA): This tools is for warming up (waking) SharPoint sites. It addresses the issue of a 403 forbidden error when the SharePoint web app is in claims mode and FBA. It uses Windows authentication to warm up the sites and bypasses the FBA login redirection causing the 403 forbidden error.Super Mario Limitless: Super Mario Limitless is an in-production Super Mario level engine. It allows you to play your own levels and worlds, play others' levels and worlds, and even play online. With limitless features, you'll spend hours playing and creating.VB.NET ASP.NET MVC 2 - Music Store: This project is a port using the VB language with ASP.NET MVC 2 of the MusicStore application that can be found at : http://mvcmusicstore.codeplex.com/ Veni, Vedi, Velcro...: A personal phone 7 social media app that shows basic elements of design, ad model, panorama etc.XMLServiceMonitor: A Windows service (VB.Net) that allows the monitoring of failure of Servers, Services, Applications, Scheduled Tasks and SQL Jobs. The service is configurable with simple XML files and sends out email notifications of failures.

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  • free open-source linux screenshot & ocr tool

    - by Gryllida
    I'm looking for a tool which would be able to capture a screen region, pass it to OCR and put the result into clipboard. "import ppm:- | gocr -i - | xclip -selection c" works, but gocr is unreliable: simple text on a webpage has errors. It is a clear font but the OCR tool always misses "r" and replaces it with underscore. "import ppm:- | ocrad -i - | xclip -selection c" says "ocrad: maxval 255 in ppm "P6" file." tesseract needs an image file and does not accept piping input to it. xfce4-screenshooter does not do OCR. ABBYY Screenshot Reader is proprietary. tessnet2 is freeware running on a proprietary platform. Google Docs can OCR screenshots in a batch. But my data is confidential and better not put online. Graphical interface solutions would be acceptable for this question, too. There is a number of existing SuperUser questions about OCR. They fall in several categories. Questions just about OCR without the "screenshot taking" part. Open Source OCR for linux Free OCR for Arabic text Looking for recommendations on OCR problem - tabular numeric data Which has better OCR applications: Ubuntu, or Mac/iPad, or Windows? How can I preform OCR from the command line? OCR solution on linux machine from command line (duplicate) Free OCR software OCR for Sanskrit ( OR devanagari) Copy image and paste to OCR (windows) File processing OCR instead of screenshot. Online OCR website for processing an entire pdf file at one time? Practical OCR solution for converting a large book to a digital format? How to extract text with OCR from a PDF on Linux? Batch-OCR many PDFs OCR Image based PDF Copy image and paste to OCR Extract OCR text from Evernote OCR in Word 2013 Replace (OCR) garbled text in PDF? Process files prior to running OCR. How can I make OCR recognize my documents' text better? Tesseract OCR recognition bilingual document. mistakes tolerance level setup OCR for low quality images How do I get the best quality screenshot for OCR (Optical Character Recognition) and what tool would be the best for screenshots? OCR training. Training Tesseract-OCR for english language fonts None of them answer this question.

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  • Garmin Ant Agent USB sticks is not working on Windows 8

    - by VinnyG
    I have a garmin gps training watch that connect with Ant agent (http://www8.garmin.com/support/download_details.jsp?id=3741) but in my new install of windows 8 the USB drivers are not working anymore I get a device problem, I downloaded the latest drivers but it did not work. I also try to install it manualy but no more luck. I made a request to Garmin support but if some has a solution until they fix it, let me know!

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  • Scope of Mainframe Technologies Today?

    - by Vaibhav Bajpai
    I have been recently allocated to training in Mainframe Technologies at my company (where I am currently working as a Trainee). I am slated to learn DB2, JCL, CICS, and Cobol during the programme. I am from a C++ background, and curious how the community here feels of these technologies. I am also curious to know, how mainframe computers fit into today's computing scenario where distributed computing has taken over almost completely.

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  • PyML 0.7.2 - How to prevent accuracy from dropping after storing/loading a classifier?

    - by Michael Aaron Safyan
    This is a followup from "Save PyML.classifiers.multi.OneAgainstRest(SVM()) object?". The solution to that question was close, but not quite right, (the SparseDataSet is broken, so attempting to save/load with that dataset container type will fail, no matter what. Also, PyML is inconsistent in terms of whether labels should be numbers or strings... it turns out that the oneAgainstRest function is actually not good enough, because the labels need to be strings and simultaneously convertible to floats, because there are places where it is assumed to be a string and elsewhere converted to float) and so after a great deal of hacking and such I was finally able to figure out a way to save and load my multi-class classifier without it blowing up with an error.... however, although it is no longer giving me an error message, it is still not quite right as the accuracy of the classifier drops significantly when it is saved and then reloaded (so I'm still missing a piece of the puzzle). I am currently using the following custom mutli-class classifier for training, saving, and loading: class SVM(object): def __init__(self,features_or_filename,labels=None,kernel=None): if isinstance(features_or_filename,str): filename=features_or_filename; if labels!=None: raise ValueError,"Labels must be None if loading from a file."; with open(os.path.join(filename,"uniquelabels.list"),"rb") as uniquelabelsfile: self.uniquelabels=sorted(list(set(pickle.load(uniquelabelsfile)))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; self.classifiers=[]; for classidx, classname in enumerate(self.uniquelabels): self.classifiers.append(PyML.classifiers.svm.loadSVM(os.path.join(filename,str(classname)+".pyml.svm"),datasetClass = PyML.VectorDataSet)); else: features=features_or_filename; if labels==None: raise ValueError,"Labels must not be None when training."; self.uniquelabels=sorted(list(set(labels))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; points = [[float(xij) for xij in xi] for xi in features]; self.classifiers=[PyML.SVM(kernel) for label in self.uniquelabels]; for i in xrange(len(self.uniquelabels)): currentlabel=self.uniquelabels[i]; currentlabels=['+1' if k==currentlabel else '-1' for k in labels]; currentdataset=PyML.VectorDataSet(points,L=currentlabels,positiveClass='+1'); self.classifiers[i].train(currentdataset,saveSpace=False); def accuracy(self,pts,labels): logger=logging.getLogger("ml"); correct=0; total=0; classindexes=[self.labeltoindex[label] for label in labels]; h=self.hypotheses(pts); for idx in xrange(len(pts)): if h[idx]==classindexes[idx]: logger.info("RIGHT: Actual \"%s\" == Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])); correct+=1; else: logger.info("WRONG: Actual \"%s\" != Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])) total+=1; return float(correct)/float(total); def prediction(self,pt): h=self.hypothesis(pt); if h!=None: return self.uniquelabels[h]; return h; def predictions(self,pts): h=self.hypotheses(self,pts); return [self.uniquelabels[x] if x!=None else None for x in h]; def hypothesis(self,pt): bestvalue=None; bestclass=None; dataset=PyML.VectorDataSet([pt]); for classidx, classifier in enumerate(self.classifiers): val=classifier.decisionFunc(dataset,0); if (bestvalue==None) or (val>bestvalue): bestvalue=val; bestclass=classidx; return bestclass; def hypotheses(self,pts): bestvalues=[None for pt in pts]; bestclasses=[None for pt in pts]; dataset=PyML.VectorDataSet(pts); for classidx, classifier in enumerate(self.classifiers): for ptidx in xrange(len(pts)): val=classifier.decisionFunc(dataset,ptidx); if (bestvalues[ptidx]==None) or (val>bestvalues[ptidx]): bestvalues[ptidx]=val; bestclasses[ptidx]=classidx; return bestclasses; def save(self,filename): if not os.path.exists(filename): os.makedirs(filename); with open(os.path.join(filename,"uniquelabels.list"),"wb") as uniquelabelsfile: pickle.dump(self.uniquelabels,uniquelabelsfile,pickle.HIGHEST_PROTOCOL); for classidx, classname in enumerate(self.uniquelabels): self.classifiers[classidx].save(os.path.join(filename,str(classname)+".pyml.svm")); I am using the latest version of PyML (0.7.2, although PyML.__version__ is 0.7.0). When I construct the classifier with a training dataset, the reported accuracy is ~0.87. When I then save it and reload it, the accuracy is less than 0.001. So, there is something here that I am clearly not persisting correctly, although what that may be is completely non-obvious to me. Would you happen to know what that is?

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  • How much does Dynamics NAV 2009 cost?

    - by GuyBehindtheGuy
    My company is evaluating becoming a Microsoft Dynamics Partner to do Dynamics installs. We'll probably start with NAV 2009, because it seems to be the easiest to develop for. However, we can't even find out what a typical Dynamics NAV 2009 license costs. This is pretty important for us to know so that we can start to identify our market before investing in training, etc. Does anyone know how much Dynamics NAV 2009 costs?

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  • SELinux vs. AppArmor vs. grsecurity

    - by Marco
    I have to set up a server that should be as secure as possible. Which security enhancement would you use and why, SELinux, AppArmor or grsecurity? Can you give me some tips, hints, pros/cons for those three? AFAIK: SELinux: most powerful but most complex AppArmor: simpler configuration / management than SELinux grsecurity: simple configuration due to auto training, more features than just access control

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  • Add shortcut SQL management studio 2008 to select top 1000 order by PK desc

    - by JP Hellemons
    Hello, when I right click a table I can select select top 1000 rows and edit top 200 rows I'd like to add an option select bottom 1000 rows I am pretty sure that I've seen it somewhere online how to do this. But I can't remember where... already found this: http://sqlserver-training.com/how-to-change-default-value-of-select-or-edit-top-rows-in-ssms-2008/- but it seems impossible to add a template query...

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  • PyML 0.7.2 - How to prevent accuracy from dropping after stroing/loading a classifier?

    - by Michael Aaron Safyan
    This is a followup from "Save PyML.classifiers.multi.OneAgainstRest(SVM()) object?". The solution to that question was close, but not quite right, (the SparseDataSet is broken, so attempting to save/load with that dataset container type will fail, no matter what. Also, PyML is inconsistent in terms of whether labels should be numbers or strings... it turns out that the oneAgainstRest function is actually not good enough, because the labels need to be strings and simultaneously convertible to floats, because there are places where it is assumed to be a string and elsewhere converted to float) and so after a great deal of hacking and such I was finally able to figure out a way to save and load my multi-class classifier without it blowing up with an error.... however, although it is no longer giving me an error message, it is still not quite right as the accuracy of the classifier drops significantly when it is saved and then reloaded (so I'm still missing a piece of the puzzle). I am currently using the following custom mutli-class classifier for training, saving, and loading: class SVM(object): def __init__(self,features_or_filename,labels=None,kernel=None): if isinstance(features_or_filename,str): filename=features_or_filename; if labels!=None: raise ValueError,"Labels must be None if loading from a file."; with open(os.path.join(filename,"uniquelabels.list"),"rb") as uniquelabelsfile: self.uniquelabels=sorted(list(set(pickle.load(uniquelabelsfile)))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; self.classifiers=[]; for classidx, classname in enumerate(self.uniquelabels): self.classifiers.append(PyML.classifiers.svm.loadSVM(os.path.join(filename,str(classname)+".pyml.svm"),datasetClass = PyML.VectorDataSet)); else: features=features_or_filename; if labels==None: raise ValueError,"Labels must not be None when training."; self.uniquelabels=sorted(list(set(labels))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; points = [[float(xij) for xij in xi] for xi in features]; self.classifiers=[PyML.SVM(kernel) for label in self.uniquelabels]; for i in xrange(len(self.uniquelabels)): currentlabel=self.uniquelabels[i]; currentlabels=['+1' if k==currentlabel else '-1' for k in labels]; currentdataset=PyML.VectorDataSet(points,L=currentlabels,positiveClass='+1'); self.classifiers[i].train(currentdataset,saveSpace=False); def accuracy(self,pts,labels): logger=logging.getLogger("ml"); correct=0; total=0; classindexes=[self.labeltoindex[label] for label in labels]; h=self.hypotheses(pts); for idx in xrange(len(pts)): if h[idx]==classindexes[idx]: logger.info("RIGHT: Actual \"%s\" == Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])); correct+=1; else: logger.info("WRONG: Actual \"%s\" != Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])) total+=1; return float(correct)/float(total); def prediction(self,pt): h=self.hypothesis(pt); if h!=None: return self.uniquelabels[h]; return h; def predictions(self,pts): h=self.hypotheses(self,pts); return [self.uniquelabels[x] if x!=None else None for x in h]; def hypothesis(self,pt): bestvalue=None; bestclass=None; dataset=PyML.VectorDataSet([pt]); for classidx, classifier in enumerate(self.classifiers): val=classifier.decisionFunc(dataset,0); if (bestvalue==None) or (val>bestvalue): bestvalue=val; bestclass=classidx; return bestclass; def hypotheses(self,pts): bestvalues=[None for pt in pts]; bestclasses=[None for pt in pts]; dataset=PyML.VectorDataSet(pts); for classidx, classifier in enumerate(self.classifiers): for ptidx in xrange(len(pts)): val=classifier.decisionFunc(dataset,ptidx); if (bestvalues[ptidx]==None) or (val>bestvalues[ptidx]): bestvalues[ptidx]=val; bestclasses[ptidx]=classidx; return bestclasses; def save(self,filename): if not os.path.exists(filename): os.makedirs(filename); with open(os.path.join(filename,"uniquelabels.list"),"wb") as uniquelabelsfile: pickle.dump(self.uniquelabels,uniquelabelsfile,pickle.HIGHEST_PROTOCOL); for classidx, classname in enumerate(self.uniquelabels): self.classifiers[classidx].save(os.path.join(filename,str(classname)+".pyml.svm")); I am using the latest version of PyML (0.7.2, although PyML.__version__ is 0.7.0). When I construct the classifier with a training dataset, the reported accuracy is ~0.87. When I then save it and reload it, the accuracy is less than 0.001. So, there is something here that I am clearly not persisting correctly, although what that may be is completely non-obvious to me. Would you happen to know what that is?

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  • what knid of usage " [MenuAction("apply", "global-menus/MenuTools/MenuToolsMyTools/Tool1", "Apply")]

    - by programmerist
    MenuAction,ButtonAction,... etc why i need this type usage. i really what it is [ButtonAction("apply", "global-toolbars/ToolbarMyTools/Tool1", "Apply")]. Can you give me some tips or advise or site link. i don't really know [Myclass]. is it AOP? [MenuAction("apply", "global-menus/MenuTools/MenuToolsMyTools/Tool1", "Apply")] // Declares a toolbar button action with action ID "apply" // TODO: Change the action path hint to your desired toolbar path, or // remove this attribute if you do not want to create a toolbar button for this tool [ButtonAction("apply", "global-toolbars/ToolbarMyTools/Tool1", "Apply")] // Specifies tooltip text for the "apply" action // TODO: Replace tooltip text [Tooltip("apply", "Place tooltip text here")] // Specifies icon resources to use for the "apply" action // TODO: Replace the icon resource names with your desired icon resources [IconSet("apply", IconScheme.Colour, "Icons.Tool1Small.png", "Icons.Tool1Medium.png", "Icons.Tool1Large.png")] // Specifies that the enablement of the "apply" action in the user-interface // is controlled by observing a boolean property named "Enabled", listening to // an event named "EnabledChanged" for changes to this property [EnabledStateObserver("apply", "Enabled", "EnabledChanged")]

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  • How to manage two separate testing teams using different test tracking tools

    - by newuser
    I have two independent testing teams currently testing the same application. One team is using ClearQuest, and the other is using Mantis. It has been a huge effort to manage all of the duplicate reported bugs. What options would improve this situation? My constraint is that the ClearQuest team will not change test reporting tools. The migration to ClearQuest also comes with a large training effort.

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  • Screenflow file type convert to AVI?

    - by Dave
    I've got a couple of large files 2 - 3GB each which were of a training course where the instructor used Screenflow on the Mac to record all his keypresses. I'm currently on a PC.. Problem: how to convert from .screenflow (and associated .scc files) to AVI or something a PC can play? Problem2: If I borrow a Mac can I d/load http://www.telestream.net/screen-flow/overview.htm (which I think was the package) and convert the files?

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