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  • Algorithm for finding all paths in a NxN grid

    - by Periastron
    Imagine a robot sitting on the upper left hand corner of an NxN grid. The robot can only move in two directions: right and down. How many possible paths are there for the robot? I could find solution to this problem on Google, but I am not very clear with the explanations. I am trying to clearly understand the logic on how to solve this and implement in Java. Any help is appreciated. Update: This is an interview question. For now, I am trying to reach the bottom-right end and print the possible paths.

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  • What Math topics & resources to consider as beginner to indulge the book - Introduction to Algorithm

    - by sector7
    I'm a programmer who's beginning to appreciate the knowledge & usability of Algorithms in my work as I move forward with my skill-set. I don't want to take the short path by learning how to apply algorithms "as-is" but would rather like to know the foundation and fundamentals behind them. For that I need Math, at which I'm pretty "basic". I'm considering getting tuition's for that. What I would like is to have a concise syllabus/set of topics/book which I could hand over to my math tutor to get started. HIGHLY DESIRED: one book. the silver bullet. (fingers crossed!) PS: I've got some leads but want to hear you guys/gurus out: Discrete Math, Combinatorics, Graph theory, Calculus, Linear Algebra, and Number Theory. Looking forward to your answers. Thanks!

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  • How can I improve the performance of this algorithm

    - by Justin
    // Checks whether the array contains two elements whose sum is s. // Input: A list of numbers and an integer s // Output: return True if the answer is yes, else return False public static boolean calvalue (int[] numbers, int s){ for (int i=0; i< numbers.length; i++){ for (int j=i+1; j<numbers.length;j++){ if (numbers[i] < s){ if (numbers[i]+numbers[j] == s){ return true; } } } } return false; }

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  • Need an efficient algorithm solve this kind of complex structure

    - by Rizvan
    Problem Statement is : Given 2 Dimensional array, print output for example If 4 rows and 6 columns, output would be: 1 2 3 4 5 6 16 17 18 19 20 7 15 24 23 22 21 8 14 13 12 11 10 9 I tried it is looking like square within square but when I attempted this problem, I put so many while and if loops but didn't got exact answer. If row and columns increases how to handle it? This is not homework. I was learning solving complex structure so I need to understand it by some guidance.

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  • algorithm to find the three majority elements in an array

    - by Qiang Li
    Let's say there are three elements in a non-sorted array all of which appear more than one-fourth times of the total number of elements. What is the most efficient way to find these elements? Both for non-online and online versions of this question. Thank you! Edit The non-online version I was referring to is: this array is specified in full. The online version means the array elements are coming one at a time. I require the space in addition to time complexity to be tight. disclaimer: THIS IS NOT HOMEWORK! I consider this as research-level question.

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  • SQLAuthority News – Mark the Date: October 16, 2013 – Introducing NuoDB Blackbirds: THE Distributed Database

    - by Pinal Dave
    I am very excited to announce first on this blog about the release of NuoDB Blackbirds (NuoDB Release 2.0). NuoDB is my favorite application to work with data now a days. They are increasingly gaining market share as well as brining out new features with their every new release. I was very excited when I learned that NuoDB is releasing their flagship release of 2.0 on October 16, 2013. Interesting enough I will be in USA while this release happens and I will be watching it live during my day time. Even though if I had to stay up the entire night to just watch this release, I would do it. Here is the details of the announcements: Introducing NuoDB Blackbirds: THE Distributed Database Date: October 16, 2013 Time: 1:00 PM EDT Location: Online Registration Link What is the best DBMS architecture to handle today’s and tomorrow’s evolving needs? The days of shared disk are over. The times are “a-changin” and IT infrastructure has to change with them. Join NuoDB live for the introduction of our latest major product release, NuoDB Blackbirds, and take a look at why the NuoDB distributed database architecture is the only answer for customers like Fathom Voice, a leading provider of Voice Over IP (VoIP). NuoDB CEO, Barry Morris, welcomes Cameron Weeks, CEO of Fathom Voice to discuss how his company is using DBMS to break away from the pack and become the hottest player in VoIP. The webcast will include demonstrations of a single, logical database running in multiple geographies and a live Q&A. If due to any reason, you cannot watch it live, do not worry at all, just register at this Registration Link, as after the event you will get the link to watch the event on-demand. You can watch the launch event at any time if you have registered for the launch. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: NuoDB

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  • Test Data in a Distributed System

    - by Davin Tryon
    A question that has been vexing me lately has been about how to effectively test (end-to-end) features in a distributed system. Particuarly, how to effectively manage (through time) test data for feature testing. The system in question is a typical SOA setup. The composition is done in JavaScript when call to several REST APIs. Each service is built as an independent block. Each service has some kind of persistent storage (SQL Server in most cases). The main issue at the moment is how to approach test data when testing end-to-end features. Functional end-to-end testing occurs through the UI, and it is therefore necessary for test data to be set up before the test run (this could be manual or automated testing). As is typical in a distributed system, identifiers from one service are used as a link in another service. So, some level of synchronization needs to be present in the data to effectively test. What is the best way to manage and set up this data after a successful deployment to a test environment? For example, is it better to manage this test data inside each service? Or package it together with the testing suite? Does that testing suite exist as a separate project? I'm interested in design guidance about how to store and manage this test data as the application features evolve.

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  • Distributed Rendering in the UDK and Unity

    - by N0xus
    At the moment I'm looking at getting a game engine to run in a CAVE environment. So far, during my research I've seen a lot of people being able to get both Unity and the Unreal engine up and running in a CAVE (someone did get CryEngine to work in one, but there is little research data about it). As of yet, I have not cemented my final choice of engine for use in the next stage of my project. I've experience in both, so the learning curve will be gentle on both. And both of the engines offer stereoscopic rendering, either already inbuilt with ReadD (Unreal) or by doing it yourself (Unity). Both can also make use of other input devices as well, such as the kinect or other devices. So again, both engines are still on the table. For the last bit of my preliminary research, I was advised to see if either, or both engines could do distributed rendering. I was advised this, as the final game we make could go into a variety of differently sized CAVEs. The one I have access to is roughly 2.4m x 3m cubed, and have been duly informed that this one is a "baby" compared to others. So, finally onto my question: Can either the Unreal Engine, or Unity Engine make it possible for developers to allow distributed rendering? Either through in built devices, or by creating my own plugin / script?

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  • Can Goldberg algorithm in ocamlgraph be used to find Minimum Cost Flow graph?

    - by Tautrimas
    I'm looking for an implementation to the Minimum Cost Flow graph problem in OCaml. OCaml library ocamlgraph has Goldberg algorithm implementation. The paper called Efficient implementation of the Goldberg-Tarjan minimum-cost flow algorithm is noting that Goldberg-Tarjan algorithm can find minimum cost graph. Question is, does ocamlgraph algorithm also find the minimum cost? Library documentation only states, that it's suitable at least for the maximum flow problem. If not, does anybody have a good link to a nice any minimum cost optimization algorithm code? I will manually translate it into OCaml then. Forgive me, if I missed it on Wikipedia: there are too many algos on flow networks for the first day!

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  • Giving a Bomberman AI intelligent bomb placement

    - by Paul Manta
    I'm trying to implement an AI algorithm for Bomberman. Currently I have a working but not very smart rudimentary implementation (the current AI is overzealous in placing bombs). This is the first AI I've ever tried implementing and I'm a bit stuck. The more sophisticated algorithms I have in mind (the ones that I expect to make better decisions) are too convoluted to be good solutions. What general tips do you have for implementing a Bomberman AI? Are there radically different approaches for making the bot either more defensive or offensive? Edit: Current algorithm My current algorithm goes something like this (pseudo-code): 1) Try to place a bomb and then find a cell that is safe from all the bombs, including the one that you just placed. To find that cell, iterate over the four directions; if you can find any safe divergent cell and reach it in time (eg. if the direction is up or down, look for a cell that is found to the left or right of this path), then it's safe to place a bomb and move in that direction. 2) If you can't find and safe divergent cells, try NOT placing a bomb and look again. This time you'll only need to look for a safe cell in only one direction (you don't have to diverge from it). 3) If you still can't find a safe cell, don't do anything. for $(direction) in (up, down, left, right): place bomb at current location if (can find and reach divergent safe cell in current $(direction)): bomb = true move = $(direction) return for $(direction) in (up, down, left, right): do not place bomb at current location if (any safe cell in the current $(direction)): bomb = false move = $(direction) return else: bomb = false move = stay_put This algorithm makes the bot very trigger-happy (it'll place bombs very frequently). It doesn't kill itself, but it does have a habit of making itself vulnerable by going into dead ends where it can be blocked and killed by the other players. Do you have any suggestions on how I might improve this algorithm? Or maybe I should try something completely different? One of the problems with this algorithm is that it tends to leave the bot with very few (frequently just one) safe cells on which it can stand. This is because the bot leaves a trail of bombs behind it, as long as it doesn't kill itself. However, leaving a trail of bombs behind leaves few places where you can hide. If one of the other players or bots decide to place a bomb somewhere near you, it often happens that you have no place to hide and you die. I need a better way to decide when to place bombs.

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  • Dynamic Dijkstra

    - by Dani
    I need dynamic dijkstra algorithm that can update itself when edge's cost is changed without a full recalculation. Full recalculation is not an option. I've tryed to "brew" my own implemantion with no success. I've also tryed to find on the Internet but found nothing. A link to an article explaining the algorithm or even it's name will be good. Edit: Thanks everyone for answering. I managed to make algorithm of my own that runs in O(V+E) time, if anyone wishes to know the algorithm just say so and I will post it.

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  • algorithm - How to sort a 0/1 array with 2n/3 comparisons?

    - by Jackson Tale
    In Algorithm Design Manual, there is such an excise 4-26 Consider the problem of sorting a sequence of n 0’s and 1’s using comparisons. For each comparison of two values x and y, the algorithm learns which of x < y, x = y, or x y holds. (a) Give an algorithm to sort in n - 1 comparisons in the worst case. Show that your algorithm is optimal. (b) Give an algorithm to sort in 2n/3 comparisons in the average case (assuming each of the n inputs is 0 or 1 with equal probability). Show that your algorithm is optimal. For (a), I think it is fairly easy. I can choose a[n-1] as pivot, then do something like in quicksort partition, scan 0 to n - 2, find the middle point where left side is all 0 and right side is all 1, this take n - 1 comparisons. But for (b), I can't get a clue. It says "each of the n inputs is 0 or 1 with equal probability", so I guess I can assume the numbers of 0 and 1 equal? But how can I get a result which is related to 1/3? divide the whole array into 3 groups? Thanks

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  • Is there an efficient algorithm to distribute resources in a way that both avoids conflict and allows bias?

    - by Steve V.
    Background (Skip this if you only care about the algorithm) At the university where I work, one of the biggest hassles in our department is classroom scheduling. For illustration purposes and to lay out the scope of the problem, here's how we do scheduling now: Professors give us a list of the classes they're teaching with the time slots they'd prefer to teach, ranked in order of priority (most desired to least desired). Administration gives us a list of the rooms we may assign along with the times those rooms are available for our department's use. We start assigning professors to rooms trying (at first) to take into account the preferences of the various professors. Inevitably, conflicts arise, professors start asking for changes, and the plan falls to pieces somewhere around professor number 30, at which point we start assigning rooms basically wherever we can fit them in, crumpled pieces of paper are everywhere, and nobody's happy. (If you've ever wondered why your class was at 9.30 in the morning on Thursday but 4 pm every other day, now you know) I have been asked to quietly investigate whether software could do this more optimally. The Actual Question Is there an algorithm to efficiently schedule a set of resources such that the following criteria are met: The algorithm must never assign two professors to the same room at the same time. The task is not complete until every professor has been assigned a room / time. The algorithm need not worry about having too many professors for the amount of time slots available. (We're not that well funded.) As much as is possible the algorithm should respect the scheduling preferences of the individual professors. I feel like I can't be the first one to ask this. Is there a efficient algorithm for this, or is this the sort of problem that can only be brute-forced?

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  • Communication Between Different Technologies in a Distributed Application

    - by sjtaheri
    I had to a incorporate several legacy applications and services in a network-distributed application. The existing services and applications are written using different languages and technologies, including: java, C#.Net and C++; all running on MS Windows machines. Now I'm wondering about the communication mechanism between them. What is the simple and standard way? Thanks! PS. communications include simple message sending and remote method invocations.

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  • SQL SERVER – Shard No More – An Innovative Look at Distributed Peer-to-peer SQL Database

    - by pinaldave
    There is no doubt that SQL databases play an important role in modern applications. In an ideal world, a single database can handle hundreds of incoming connections from multiple clients and scale to accommodate the related transactions. However the world is not ideal and databases are often a cause of major headaches when applications need to scale to accommodate more connections, transactions, or both. In order to overcome scaling issues, application developers often resort to administrative acrobatics, also known as database sharding. Sharding helps to improve application performance and throughput by splitting the database into two or more shards. Unfortunately, this practice also requires application developers to code transactional consistency into their applications. Getting transactional consistency across multiple SQL database shards can prove to be very difficult. Sharding requires developers to think about things like rollbacks, constraints, and referential integrity across tables within their applications when these types of concerns are best handled by the database. It also makes other common operations such as joins, searches, and memory management very difficult. In short, the very solution implemented to overcome throughput issues becomes a bottleneck in and of itself. What if database sharding was no longer required to scale your application? Let me explain. For the past several months I have been following and writing about NuoDB, a hot new SQL database technology out of Cambridge, MA. NuoDB is officially out of beta and they have recently released their first release candidate so I decided to dig into the database in a little more detail. Their architecture is very interesting and exciting because it completely eliminates the need to shard a database to achieve higher throughput. Each NuoDB database consists of at least three or more processes that enable a single database to run across multiple hosts. These processes include a Broker, a Transaction Engine and a Storage Manager.  Brokers are responsible for connecting client applications to Transaction Engines and maintain a global view of the network to keep track of the multiple Transaction Engines available at any time. Transaction Engines are in-memory processes that client applications connect to for processing SQL transactions. Storage Managers are responsible for persisting data to disk and serving up records to the Transaction Managers if they don’t exist in memory. The secret to NuoDB’s approach to solving the sharding problem is that it is a truly distributed, peer-to-peer, SQL database. Each of its processes can be deployed across multiple hosts. When client applications need to connect to a Transaction Engine, the Broker will automatically route the request to the most available process. Since multiple Transaction Engines and Storage Managers running across multiple host machines represent a single logical database, you never have to resort to sharding to get the throughput your application requires. NuoDB is a new pioneer in the SQL database world. They are making database scalability simple by eliminating the need for acrobatics such as sharding, and they are also making general administration of the database simpler as well.  Their distributed database appears to you as a user like a single SQL Server database.  With their RC1 release they have also provided a web based administrative console that they call NuoConsole. This tool makes it extremely easy to deploy and manage NuoDB processes across one or multiple hosts with the click of a mouse button. See for yourself by downloading NuoDB here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: CodeProject, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology Tagged: NuoDB

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  • Whats the difference between Paxos and W+R>=N in Cassandra?

    - by user1128016
    Dynamo-like databases (e.g. Cassandra) provide ability to enforce consistency by means of quorum, i.e. a number of synchronously written replicas (W) and a number of replicas to read (R) should be chosen in such a way that W+RN where N is a replication factor. On the other hand, PAXOS-based systems like Zookeeper are also used as a consistent fault-tolerant storage. What is the difference between these two approaches? Does PAXOS provide guarantees that are not provided by W+RN schema?

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  • Discussion of a Distributed Data Storage implementation

    - by fegol
    I want to implement a distributed data storage using a client/server architecture. Each data item will be stored persistently in disk in one of several remote servers. The client uses a library to update and query the data, shielding the client from its actual location. This should allow a client to associate keys (String) to values(byte[]), much as a Map does. The system must ensure that the amount of data stored in each server is approximately the same. The set of servers is known beforehand by other servers and clients. Both the client and the server will be written in Java, using sockets, threads, and files. I open this topic with the objective of discussing the best way to implement this idea, assuming simplicity, what are the issues of this implementation, performance measurements and discussion of the limitations.

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  • Azure Futures - Distributed Computing and Number Crunching

    - by JoshReuben
    "the biggest Azure customers today are the ones using HPC on-premises at the current time" - http://www.zdnet.com/blog/microsoft/windows-azure-futures-turning-the-cloud-into-a-supercomputer/8592?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+zdnet%2Fmicrosoft+%28ZDNet+All+About+Microsoft%29&utm_content=Google+Reader   Orleans Framework for cloud computing - http://research.microsoft.com/en-us/projects/orleans     HPC on Azure - http://www.zdnet.com/blog/microsoft/microsoft-finalizes-its-latest-supercomputing-operating-system-release/7414   Dryad is Microsoft’s competitor to Google MapReduce and Apache Hadoop  - http://www.zdnet.com/blog/microsoft/microsoft-takes-a-step-toward-commercializing-its-dryad-distributed-computing-technologies/8255?tag=mantle_skin;content   SQL Server Analysis Services DataMining in the cloud - http://www.sqlmag.com/article/reporting2/azure-data-mining-in-the-cloud.aspx

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  • Distributed Computing - Hybrid Systems Considerations

    When the Cloud was new, it was often presented as an 'all or nothing' solution. Nowadays, the canny Systems Architect will exploit the best advantages of 'cloud' distributed computing in the right place, and use in-house services where most appropriate. So what are the issues that govern these architectural decisions? What can SQL Monitor 3.2 monitor?Whatever you think is most important. Use custom metrics to monitor and alert on data that's most important for your environment. Find out more.

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