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  • How should I change my Graph structure (very slow insertion)?

    - by Nazgulled
    Hi, This program I'm doing is about a social network, which means there are users and their profiles. The profiles structure is UserProfile. Now, there are various possible Graph implementations and I don't think I'm using the best one. I have a Graph structure and inside, there's a pointer to a linked list of type Vertex. Each Vertex element has a value, a pointer to the next Vertex and a pointer to a linked list of type Edge. Each Edge element has a value (so I can define weights and whatever it's needed), a pointer to the next Edge and a pointer to the Vertex owner. I have a 2 sample files with data to process (in CSV style) and insert into the Graph. The first one is the user data (one user per line); the second one is the user relations (for the graph). The first file is quickly inserted into the graph cause I always insert at the head and there's like ~18000 users. The second file takes ages but I still insert the edges at the head. The file has about ~520000 lines of user relations and takes between 13-15mins to insert into the Graph. I made a quick test and reading the data is pretty quickly, instantaneously really. The problem is in the insertion. This problem exists because I have a Graph implemented with linked lists for the vertices. Every time I need to insert a relation, I need to lookup for 2 vertices, so I can link them together. This is the problem... Doing this for ~520000 relations, takes a while. How should I solve this? Solution 1) Some people recommended me to implement the Graph (the vertices part) as an array instead of a linked list. This way I have direct access to every vertex and the insertion is probably going to drop considerably. But, I don't like the idea of allocating an array with [18000] elements. How practically is this? My sample data has ~18000, but what if I need much less or much more? The linked list approach has that flexibility, I can have whatever size I want as long as there's memory for it. But the array doesn't, how am I going to handle such situation? What are your suggestions? Using linked lists is good for space complexity but bad for time complexity. And using an array is good for time complexity but bad for space complexity. Any thoughts about this solution? Solution 2) This project also demands that I have some sort of data structures that allows quick lookup based on a name index and an ID index. For this I decided to use Hash Tables. My tables are implemented with separate chaining as collision resolution and when a load factor of 0.70 is reach, I normally recreate the table. I base the next table size on this http://planetmath.org/encyclopedia/GoodHashTablePrimes.html. Currently, both Hash Tables hold a pointer to the UserProfile instead of duplication the user profile itself. That would be stupid, changing data would require 3 changes and it's really dumb to do it that way. So I just save the pointer to the UserProfile. The same user profile pointer is also saved as value in each Graph Vertex. So, I have 3 data structures, one Graph and two Hash Tables and every single one of them point to the same exact UserProfile. The Graph structure will serve the purpose of finding the shortest path and stuff like that while the Hash Tables serve as quick index by name and ID. What I'm thinking to solve my Graph problem is to, instead of having the Hash Tables value point to the UserProfile, I point it to the corresponding Vertex. It's still a pointer, no more and no less space is used, I just change what I point to. Like this, I can easily and quickly lookup for each Vertex I need and link them together. This will insert the ~520000 relations pretty quickly. I thought of this solution because I already have the Hash Tables and I need to have them, then, why not take advantage of them for indexing the Graph vertices instead of the user profile? It's basically the same thing, I can still access the UserProfile pretty quickly, just go to the Vertex and then to the UserProfile. But, do you see any cons on this second solution against the first one? Or only pros that overpower the pros and cons on the first solution? Other Solution) If you have any other solution, I'm all ears. But please explain the pros and cons of that solution over the previous 2. I really don't have much time to be wasting with this right now, I need to move on with this project, so, if I'm doing to do such a change, I need to understand exactly what to change and if that's really the way to go. Hopefully no one fell asleep reading this and closed the browser, sorry for the big testament. But I really need to decide what to do about this and I really need to make a change. P.S: When answering my proposed solutions, please enumerate them as I did so I know exactly what are you talking about and don't confuse my self more than I already am.

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  • Time complexity to fill hash table (homework)?

    - by Heathcliff
    This is a homework question, but I think there's something missing from it. It asks: Provide a sequence of m keys to fill a hash table implemented with linear probing, such that the time to fill it is minimum. And then Provide another sequence of m keys, but such that the time fill it is maximum. Repeat these two questions if the hash table implements quadratic probing I can only assume that the hash table has size m, both because it's the only number given and because we have been using that letter to address a hash table size before when describing the load factor. But I can't think of any sequence to do the first without knowing the hash function that hashes the sequence into the table. If it is a bad hash function, such that, for instance, it hashes every entry to the same index, then both the minimum and maximum time to fill it will take O(n) time, regardless of what the sequence looks like. And in the average case, where I assume the hash function is OK, how am I suppossed to know how long it will take for that hash function to fill the table? Aren't these questions linked to the hash function stronger than they are to the sequence that is hashed? As for the second question, I can assume that, regardless of the hash function, a sequence of size m with the same key repeated m-times will provide the maximum time, because it will cause linear probing from the second entry on. I think that will take O(n) time. Is that correct? Thanks

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  • ERROR: Not enough space?

    - by dsmoljanovic
    Now this is a very unspecific question. I'm trying to figure out what this message would mean. Here is the story behind it: I'm installing Oracle enterprise manager cloud control (12c r3) on Solaris 10 (5/09). Installer opens up, i enter all needed information and at the last step click Install. It immediately crashes with only "ERROR: Not enough space" written in log and console and nothing else. Now, this could be java error or Solaris error? I'm thinking it's happening either when it starts to copy files or when it tries to launch a process that would do that. What space is it referring to? disk (have ehough), swap (also), memory (yep)... Any ideas are helpful. Edit: i found this exception in the oraInventory logs: oracle.sysman.oii.oiic.OiicInstallAPIException: Not enough space at oracle.sysman.oii.oiic.OiicAPIInstaller.initInstallSession(OiicAPIInstaller.java:2165) at oracle.sysman.oii.oiic.OiicAPIInstaller.initOUIAPISession(OiicAPIInstaller.java:790) at oracle.sysman.install.oneclick.EMGCOUIInstaller.prepareForInstall(EMGCOUIInstaller.java:676) at oracle.sysman.install.oneclick.EMGCSummaryDlgonNext$1.run(EMGCSummaryDlgonNext.java:243) at java.lang.Thread.run(Thread.java:662) at oracle.sysman.install.oneclick.EMGCSummaryDlgonNext.actionsOnClickofNext(EMGCSummaryDlgonNext.java:1067) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at oracle.sysman.install.oneclick.EMGCUtil.performonClickOfNextForClass(EMGCUtil.java:399) at oracle.sysman.install.oneclick.EMGCUtil.performPageLevelValidationsForSilentInstall(EMGCUtil.java:367) at oracle.sysman.install.oneclick.EMGCInstaller.prepareForSilentInstall(EMGCInstaller.java:1459) at oracle.sysman.install.oneclick.EMGCInstaller.main(EMGCInstaller.java:1553) disk status: bash-3.00$ df -h /tmp Filesystem size used avail capacity Mounted on swap 8.1G 2.7G 5.4G 33% /tmp bash-3.00$ df -h /u01 Filesystem size used avail capacity Mounted on / 275G 28G 244G 11% / swap: root@gs12emcc # swap -s total: 18306040k bytes allocated + 3837808k reserved = 22143848k used, 5712664k available

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  • O(N log N) Complexity - Similar to linear?

    - by gav
    Hey All, So I think I'm going to get buried for asking such a trivial but I'm a little confused about something. I have implemented quicksort in Java and C and I was doing some basic comparissons. The graph came out as two straight lines, with the C being 4ms faster than the Java counterpart over 100,000 random integers. The code for my tests can be found here; android-benchmarks I wasn't sure what an (n log n) line would look like but I didn't think it would be straight. I just wanted to check that this is the expected result and that I shouldn't try to find an error in my code. I stuck the formula into excel and for base 10 it seems to be a straight line with a kink at the start. Is this because the difference between log(n) and log(n+1) increases linearly? Thanks, Gav

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  • Complexity of subset product

    - by threenplusone
    I have a set of numbers produced using the following formula with integers 0 < x < a. f(x) = f(x-1)^2 % a For example starting at 2 with a = 649. {2, 4, 16, 256, 636, 169, 5, 25, 649, 576, 137, ...} I am after a subset of these numbers that when multiplied together equals 1 mod N. I believe this problem by itself to be NP-complete (based on similaries to Subset-Sum problem). However starting with any integer (x) gives the same solution pattern. Eg. a = 649 {2, 4, 16, 256, 636, 169, 5, 25, 649, 576, 137, ...} = 16 * 5 * 576 = 1 % 649 {3, 9, 81, 71, 498, 86, 257, 500, 135, 53, 213, ...} = 81 * 257 * 53 = 1 % 649 {4, 16, 256, 636, 169, 5, 25, 649, 576, 137, 597, ...} = 256 * 25 * 137 = 1 % 649 I am wondering if this additional fact makes this problem solvable faster? Or if anyone has run into this problem previously or has any advice?

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  • Unicode paragraph end/line break breaking space / non breaking space aware text editor

    - by martinr
    I want one of those to write my blog articles with. I'm tired of manually converting breaks from rough notes to either paragraphs or line breaks for release as HTML, and tired of converting spaces to breaking or non-breaking ones. There are standard Unicode code points for the difference - what editor lets me use almost plain ASCII text but with builtin support and understanding for Unicode paragraph and non-breaking space characters? And ideally will let me save straight to either plain text UTF8 or to a file of plain HTML paragraphs?

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  • Unicode paragraph end/line break breaking space / non breaking space aware text editor

    - by martinr
    I want one of those to write my blog articles with. I'm tired of manually converting breaks from rough notes to either paragraphs or line breaks for release as HTML, and tired of converting spaces to breaking or non-breaking ones. There are standard Unicode code points for the difference - what editor lets me use almost plain ASCII text but with builtin support and understanding for Unicode paragraph and non-breaking space characters? And ideally will let me save straight to either plain text UTF8 or to a file of plain HTML paragraphs?

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  • A Guided Tour of Complexity

    - by JoshReuben
    I just re-read Complexity – A Guided Tour by Melanie Mitchell , protégé of Douglas Hofstadter ( author of “Gödel, Escher, Bach”) http://www.amazon.com/Complexity-Guided-Tour-Melanie-Mitchell/dp/0199798109/ref=sr_1_1?ie=UTF8&qid=1339744329&sr=8-1 here are some notes and links:   Evolved from Cybernetics, General Systems Theory, Synergetics some interesting transdisciplinary fields to investigate: Chaos Theory - http://en.wikipedia.org/wiki/Chaos_theory – small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for chaotic systems, rendering long-term prediction impossible. System Dynamics / Cybernetics - http://en.wikipedia.org/wiki/System_Dynamics – study of how feedback changes system behavior Network Theory - http://en.wikipedia.org/wiki/Network_theory – leverage Graph Theory to analyze symmetric  / asymmetric relations between discrete objects Algebraic Topology - http://en.wikipedia.org/wiki/Algebraic_topology – leverage abstract algebra to analyze topological spaces There are limits to deterministic systems & to computation. Chaos Theory definitely applies to training an ANN (artificial neural network) – different weights will emerge depending upon the random selection of the training set. In recursive Non-Linear systems http://en.wikipedia.org/wiki/Nonlinear_system – output is not directly inferable from input. E.g. a Logistic map: Xt+1 = R Xt(1-Xt) Different types of bifurcations, attractor states and oscillations may occur – e.g. a Lorenz Attractor http://en.wikipedia.org/wiki/Lorenz_system Feigenbaum Constants http://en.wikipedia.org/wiki/Feigenbaum_constants express ratios in a bifurcation diagram for a non-linear map – the convergent limit of R (the rate of period-doubling bifurcations) is 4.6692016 Maxwell’s Demon - http://en.wikipedia.org/wiki/Maxwell%27s_demon - the Second Law of Thermodynamics has only a statistical certainty – the universe (and thus information) tends towards entropy. While any computation can theoretically be done without expending energy, with finite memory, the act of erasing memory is permanent and increases entropy. Life & thought is a counter-example to the universe’s tendency towards entropy. Leo Szilard and later Claude Shannon came up with the Information Theory of Entropy - http://en.wikipedia.org/wiki/Entropy_(information_theory) whereby Shannon entropy quantifies the expected value of a message’s information in bits in order to determine channel capacity and leverage Coding Theory (compression analysis). Ludwig Boltzmann came up with Statistical Mechanics - http://en.wikipedia.org/wiki/Statistical_mechanics – whereby our Newtonian perception of continuous reality is a probabilistic and statistical aggregate of many discrete quantum microstates. This is relevant for Quantum Information Theory http://en.wikipedia.org/wiki/Quantum_information and the Physics of Information - http://en.wikipedia.org/wiki/Physical_information. Hilbert’s Problems http://en.wikipedia.org/wiki/Hilbert's_problems pondered whether mathematics is complete, consistent, and decidable (the Decision Problem – http://en.wikipedia.org/wiki/Entscheidungsproblem – is there always an algorithm that can determine whether a statement is true).  Godel’s Incompleteness Theorems http://en.wikipedia.org/wiki/G%C3%B6del's_incompleteness_theorems  proved that mathematics cannot be both complete and consistent (e.g. “This statement is not provable”). Turing through the use of Turing Machines (http://en.wikipedia.org/wiki/Turing_machine symbol processors that can prove mathematical statements) and Universal Turing Machines (http://en.wikipedia.org/wiki/Universal_Turing_machine Turing Machines that can emulate other any Turing Machine via accepting programs as well as data as input symbols) that computation is limited by demonstrating the Halting Problem http://en.wikipedia.org/wiki/Halting_problem (is is not possible to know when a program will complete – you cannot build an infinite loop detector). You may be used to thinking of 1 / 2 / 3 dimensional systems, but Fractal http://en.wikipedia.org/wiki/Fractal systems are defined by self-similarity & have non-integer Hausdorff Dimensions !!!  http://en.wikipedia.org/wiki/List_of_fractals_by_Hausdorff_dimension – the fractal dimension quantifies the number of copies of a self similar object at each level of detail – eg Koch Snowflake - http://en.wikipedia.org/wiki/Koch_snowflake Definitions of complexity: size, Shannon entropy, Algorithmic Information Content (http://en.wikipedia.org/wiki/Algorithmic_information_theory - size of shortest program that can generate a description of an object) Logical depth (amount of info processed), thermodynamic depth (resources required). Complexity is statistical and fractal. John Von Neumann’s other machine was the Self-Reproducing Automaton http://en.wikipedia.org/wiki/Self-replicating_machine  . Cellular Automata http://en.wikipedia.org/wiki/Cellular_automaton are alternative form of Universal Turing machine to traditional Von Neumann machines where grid cells are locally synchronized with their neighbors according to a rule. Conway’s Game of Life http://en.wikipedia.org/wiki/Conway's_Game_of_Life demonstrates various emergent constructs such as “Glider Guns” and “Spaceships”. Cellular Automatons are not practical because logical ops require a large number of cells – wasteful & inefficient. There are no compilers or general program languages available for Cellular Automatons (as far as I am aware). Random Boolean Networks http://en.wikipedia.org/wiki/Boolean_network are extensions of cellular automata where nodes are connected at random (not to spatial neighbors) and each node has its own rule –> they demonstrate the emergence of complex  & self organized behavior. Stephen Wolfram’s (creator of Mathematica, so give him the benefit of the doubt) New Kind of Science http://en.wikipedia.org/wiki/A_New_Kind_of_Science proposes the universe may be a discrete Finite State Automata http://en.wikipedia.org/wiki/Finite-state_machine whereby reality emerges from simple rules. I am 2/3 through this book. It is feasible that the universe is quantum discrete at the plank scale and that it computes itself – Digital Physics: http://en.wikipedia.org/wiki/Digital_physics – a simulated reality? Anyway, all behavior is supposedly derived from simple algorithmic rules & falls into 4 patterns: uniform , nested / cyclical, random (Rule 30 http://en.wikipedia.org/wiki/Rule_30) & mixed (Rule 110 - http://en.wikipedia.org/wiki/Rule_110 localized structures – it is this that is interesting). interaction between colliding propagating signal inputs is then information processing. Wolfram proposes the Principle of Computational Equivalence - http://mathworld.wolfram.com/PrincipleofComputationalEquivalence.html - all processes that are not obviously simple can be viewed as computations of equivalent sophistication. Meaning in information may emerge from analogy & conceptual slippages – see the CopyCat program: http://cognitrn.psych.indiana.edu/rgoldsto/courses/concepts/copycat.pdf Scale Free Networks http://en.wikipedia.org/wiki/Scale-free_network have a distribution governed by a Power Law (http://en.wikipedia.org/wiki/Power_law - much more common than Normal Distribution). They are characterized by hubs (resilience to random deletion of nodes), heterogeneity of degree values, self similarity, & small world structure. They grow via preferential attachment http://en.wikipedia.org/wiki/Preferential_attachment – tipping points triggered by positive feedback loops. 2 theories of cascading system failures in complex systems are Self-Organized Criticality http://en.wikipedia.org/wiki/Self-organized_criticality and Highly Optimized Tolerance http://en.wikipedia.org/wiki/Highly_optimized_tolerance. Computational Mechanics http://en.wikipedia.org/wiki/Computational_mechanics – use of computational methods to study phenomena governed by the principles of mechanics. This book is a great intuition pump, but does not cover the more mathematical subject of Computational Complexity Theory – http://en.wikipedia.org/wiki/Computational_complexity_theory I am currently reading this book on this subject: http://www.amazon.com/Computational-Complexity-Christos-H-Papadimitriou/dp/0201530821/ref=pd_sim_b_1   stay tuned for that review!

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  • Hard Disk Space Changes

    - by Write.
    I am currently running on Windows 7 x64, and have observe that my hard disk space is acting a little weird. Currently, my harddisk has 3 partitions, C:, D:, E:. Previously, before I delete a huge folder (30gb of data) from my D: drive, my C: drive has about 1gb left, while my E: drive has about 5 gb left. After deleting the 30gb of data (from D: drive), my space in D: drive has been recovered (but not sure if it's fully recovered), my C: drive which only had about 1gb left increased to 3. While my E: drive which had 5gb left dropped to 1. I was wondering if it has something to do with the fragmentations and whatsoever I always hear about in harddisk. Has anyone encountered similar issues or have an explanation to why it could be happening?

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  • How to increase virtual hard drive space

    - by Chris
    I have a Microsoft Virutal PC hard drive (.vhd format) that's maxed out it's 16 gig hard drive space. What would be the best way to increase this diskspace? Booting into the machine (windows xp professional) and using the disk management snap in, I can see that the virtual drive has approximately 40 more unused gigs of space. Trying to use diskpart, I find out that Windows XP can't extend the boot partition. So I'm at an empass, any suggestions on how to increase the partion or to increase the actual virtual hard drive would be great. Note: The virtual hard drive is running on Windows 7 using XP mode.

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  • Why is my partition claiming to be out of space?

    - by Dr C
    My file system claims to only have 4.5 GB left. While my OS (a folder with in file system) still has 75.2 GB left. I put something near 130 GB on my Ubuntu partition, it should have enough space. I confirmed that I can put things in OS that exceed the space in available file systems, but that makes no sense, OS is listed as a folder inside of file system, why would it have more space than it's parent folder? What is going on? Here is the output of df: Filesystem 1K-blocks Used Available Use% Mounted on /dev/sda5 113773200 103741440 4252408 97% / udev 2004600 4 2004596 1% /dev tmpfs 804756 848 803908 1% /run none 5120 0 5120 0% /run/lock none 2011884 436 2011448 1% /run/shm /dev/sda2 127526908 54045584 73481324 43% /media/OS /dev/sda3 39144708 89016 39055692 1% /media/DATA`

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  • Missing disk space in Windows XP

    - by Jørn Schou-Rode
    On my mother's Lenovo laptop, Windows XP claims that the hard drive is almost full. According to the properties window, 52.7 out of 55.2 GB is in use: By deleting temp files from Internet Explorer, System Restore, Recycle bin, Windows Update, System Cleanup, I managed to free up about one GB. That's still 50 GB in use, which still is a lot more than I expected. Hence, I gave good old WinDirStat a spin, and here's the output: It might be hard to read here, but the first line says that the total amount of disk space in use on drive C is 24.3 GB. So Windows claims usage of 52.7 GB and WinDirStat can only account for 24.3 GB. Where is the other half of that disk space being used? I hope someone has an answer, or some tricks or tips to do further research. UPDATE: The laptop in question has an SSD hard drive. I am aware that these disk (at least the earlier ones) have a limited life-time. Could the symptoms described be caused by wear and tear on the SSD?

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  • Missing hard drive total space in Windows

    - by bluedot951
    I have an HP Pavilion DM4 with a 750 GB hard drive. A few days ago, I installed Windows 8 on it, so I am now dual booting Win7 and Win8 (and I also have a 100 MB system reserved partition). I noticed that I am only able to see 700 GB of hard disk space (169 for Win 8 and 529 for Win 7). I booted of an Ubuntu 11.04 LiveCD and in the disk utility it said that my Win 8 partition is 182 GB and my Win 7 partition is 568 GB, correctly adding up to 750 GB. I would like to reclaim the missing space in its respective partitions. Any advice on how to go about doing this?

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  • Get Python to raise MemoryError instead of eating all my disk space

    - by asmeurer
    If I run a Python program with a memory leak, I would normally expect the program to eventually die with MemoryError. But instead, what happens is that all the virtual memory is used until my disk runs out of space. I am running Mac OS X 10.8 on a retina MacBook Pro. My computer generally has between 10GB to 20GB free. Mac OS X is smart enough to not die completely when the disk runs out of space (rather, it gives me a dialog letting me force quit my GUI programs). Is there a way to make Python just die when it runs out of real memory, or some reasonable amount of virtual memory? This is what happens on Linux, as far as I can tell. I guess Mac OS X is more generous than Linux with virtual memory (the fact that I have an SSD might be part of this; I don't know just how smart OS X is with this stuff). Maybe there's a way to tell the Mac OS X kernel to never use so much virtual memory that leaves less than, say, 5 GB free on the hard drive?

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  • 6 Ways to Free Up Hard Drive Space Used by Windows System Files

    - by Chris Hoffman
    We’ve previously covered the standard ways to free up space on Windows. But if you have a small solid-state drive and really want more hard space, there are geekier ways to reclaim hard drive space. Not all of these tips are recommended — in fact, if you have more than enough hard drive space, following these tips may actually be a bad idea. There’s a tradeoff to changing all of these settings. Erase Windows Update Uninstall Files Windows allows you to uninstall patches you install from Windows Update. This is helpful if an update ever causes a problem — but how often do you need to uninstall an update, anyway? And will you really ever need to uninstall updates you’ve installed several years ago? These uninstall files are probably just wasting space on your hard drive. A recent update released for Windows 7 allows you to erase Windows Update files from the Windows Disk Cleanup tool. Open Disk Cleanup, click Clean up system files, check the Windows Update Cleanup option, and click OK. If you don’t see this option, run Windows Update and install the available updates. Remove the Recovery Partition Windows computers generally come with recovery partitions that allow you to reset your computer back to its factory default state without juggling discs. The recovery partition allows you to reinstall Windows or use the Refresh and Reset your PC features. These partitions take up a lot of space as they need to contain a complete system image. On Microsoft’s Surface Pro, the recovery partition takes up about 8-10 GB. On other computers, it may be even larger as it needs to contain all the bloatware the manufacturer included. Windows 8 makes it easy to copy the recovery partition to removable media and remove it from your hard drive. If you do this, you’ll need to insert the removable media whenever you want to refresh or reset your PC. On older Windows 7 computers, you could delete the recovery partition using a partition manager — but ensure you have recovery media ready if you ever need to install Windows. If you prefer to install Windows from scratch instead of using your manufacturer’s recovery partition, you can just insert a standard Window disc if you ever want to reinstall Windows. Disable the Hibernation File Windows creates a hidden hibernation file at C:\hiberfil.sys. Whenever you hibernate the computer, Windows saves the contents of your RAM to the hibernation file and shuts down the computer. When it boots up again, it reads the contents of the file into memory and restores your computer to the state it was in. As this file needs to contain much of the contents of your RAM, it’s 75% of the size of your installed RAM. If you have 12 GB of memory, that means this file takes about 9 GB of space. On a laptop, you probably don’t want to disable hibernation. However, if you have a desktop with a small solid-state drive, you may want to disable hibernation to recover the space. When you disable hibernation, Windows will delete the hibernation file. You can’t move this file off the system drive, as it needs to be on C:\ so Windows can read it at boot. Note that this file and the paging file are marked as “protected operating system files” and aren’t visible by default. Shrink the Paging File The Windows paging file, also known as the page file, is a file Windows uses if your computer’s available RAM ever fills up. Windows will then “page out” data to disk, ensuring there’s always available memory for applications — even if there isn’t enough physical RAM. The paging file is located at C:\pagefile.sys by default. You can shrink it or disable it if you’re really crunched for space, but we don’t recommend disabling it as that can cause problems if your computer ever needs some paging space. On our computer with 12 GB of RAM, the paging file takes up 12 GB of hard drive space by default. If you have a lot of RAM, you can certainly decrease the size — we’d probably be fine with 2 GB or even less. However, this depends on the programs you use and how much memory they require. The paging file can also be moved to another drive — for example, you could move it from a small SSD to a slower, larger hard drive. It will be slower if Windows ever needs to use the paging file, but it won’t use important SSD space. Configure System Restore Windows seems to use about 10 GB of hard drive space for “System Protection” by default. This space is used for System Restore snapshots, allowing you to restore previous versions of system files if you ever run into a system problem. If you need to free up space, you could reduce the amount of space allocated to system restore or even disable it entirely. Of course, if you disable it entirely, you’ll be unable to use system restore if you ever need it. You’d have to reinstall Windows, perform a Refresh or Reset, or fix any problems manually. Tweak Your Windows Installer Disc Want to really start stripping down Windows, ripping out components that are installed by default? You can do this with a tool designed for modifying Windows installer discs, such as WinReducer for Windows 8 or RT Se7en Lite for Windows 7. These tools allow you to create a customized installation disc, slipstreaming in updates and configuring default options. You can also use them to remove components from the Windows disc, shrinking the size of the resulting Windows installation. This isn’t recommended as you could cause problems with your Windows installation by removing important features. But it’s certainly an option if you want to make Windows as tiny as possible. Most Windows users can benefit from removing Windows Update uninstallation files, so it’s good to see that Microsoft finally gave Windows 7 users the ability to quickly and easily erase these files. However, if you have more than enough hard drive space, you should probably leave well enough alone and let Windows manage the rest of these settings on its own. Image Credit: Yutaka Tsutano on Flickr     

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  • Linear time and quadratic time

    - by jasonline
    I'm just not sure... If you have a code that can be executed in either of the following complexities: (1) A sequence of O(n), like for example: two O(n) in sequence (2) O(n²) The preferred version would be the one that can be executed in linear time. Would there be a time such that the sequence of O(n) would be too much and that O(n²) would be preferred? In other words, is the statement C x O(n) < O(n²) always true for any constant C? If no, what are the factors that would affect the condition such that it would be better to choose the O(n²) complexity?

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  • Hard Drive missing drive space

    - by Chance Robertson
    I have a 500 GB hard drive which I previously attached to my Mac. I detached the drive without going through the eject procedure. When I did this a message showed up, which of course I did not read. I could not use the drive until I formatted again. Now, when I attach the drive it says it is formatted NTFS and has 280.39 of 500 GB free. When I open the drive in Windows Explorer, Finder, or in Linux, is only shows a handful of files totaling 54 MB. How can I find out what is taking up all the space.

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  • This company buries Ashes on Space for $3000

    - by Gopinath
    Does Space burials sounds crazy to you? Then you may not be a big fan of science fictions or a Japanese. According to a study conducted by NASA many science fiction fans prefer their final rights to be held on space and you can read more details about the research over here on NASA website. The other people who fancy about space burials are Japanese Buddhists. For those who are not aware of Space burials, it’s a procedure in which a small sample of the cremated ashes of the deceased are launched into space using spacecraft. The spacecraft will remain in orbit around the Earth or other planets  for decades and eventually burning up in the atmosphere. Celestis, an US based company, is pioneer in memorial spaceflight business and so far they have conducted a total of 10 space burials. Few of the famous people buried in space are Gene Roddenberry(creator of Star Trek),  Gerard K. O’Neill (space physicist), Clyde Tombaugh (astronomer and discoverer of Pluto)  and complete list is available on this Wikipedia page In the coming months Celestis have planned for a  launch of its latest memorial spacecraft and you can send your loved one’s remains for just $3000. Once they put the ashes on space they will also let you track the location of the spacecraft in orbit using a real time feed. Story via BBC and cc image credit: flickr/gsfc

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  • Windows 7 - mysteriously missing free HDD space

    - by sYnfo
    I have Windows7 installed on 50GB (Oops, it should have been 45GB, sorry) partition, and every now and then it gets full, and I have to resize that partition. I always thought it is quite normal. But it happened again today and this time, I'm sure it is not normal, because since last resizing (35GB 45GB) I did not install any new apps or whatever. Also, sum of sizes off all, including hidden & system, root folders and files is ~18GB, yet windows is indicating that all 50GB are used up... Any idea what is going on? EDIT: Great tools everyone! (SourceForge appears to be offline at the moment, I'll check WinDirStat later) Alas, non of them solved my problem just yet... Screenshot from SpaceSniffer: On the right there is some kind of "Unknows Space", any idea what that could be? EDIT2: After those two apps failing to help much I didn't expect it, but WinDirStat actually helped. It showed that those missing 27GB are in my Temp folder (Well, that should have been my first guess anyway). There I found hundreds of ~100MB files, named like HTT????.tmp. After some googling it appears to be a problem with ESET NOD32 antivirus and it's ThreatSense feature. Thank you all for help! :)

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  • disk space keeps filling up on EC2 instance with no apperent files/directories

    - by sasher
    How come os shows 6.5G used but I see only 3.6G in files/directories? Running as root on an Amazon Linux AMI (seems like Centos), lots of free memory available, no swapping going on, no apparent file descriptors issue. The only thing I can think of is a log file that was deleted while applications append to it. Disk space usage is slowly but continuously rising towards full capacity (~1k/min with very small decreases from time to time) Any explanation? Solution? du --max-depth=1 -h / 1.2G /usr 4.0K /cgroup 22M /lib64 11M /sbin 19M /etc 52K /dev 2.1G /var 4.0K /media 0 /sys 4.0K /selinux du: cannot access /proc/14024/task/14024/fd/4': No such file or directory du: cannot access<br/> /proc/14024/task/14024/fdinfo/4': No such file or directory du: cannot access /proc/14024/fd/4': No such file or directory du: cannot<br/> access/proc/14024/fdinfo/4': No such file or directory 0 /proc 18M /home 4.0K /logs 8.1M /bin 16K /lost+found 12M /tmp 4.0K /srv 35M /boot 79M /lib 56K /root 67M /opt 4.0K /local 4.0K /mnt 3.6G / df -h Filesystem Size Used Avail Use% Mounted on /dev/xvda1 7.9G 6.5G 1.4G 84% / tmpfs 3.7G 0 3.7G 0% /dev/shm sysctl fs.file-nr fs.file-nr = 864 0 761182

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  • Form, function and complexity in rule processing

    - by Charles Young
    Tim Bass posted on ‘Orwellian Event Processing’. I was involved in a heated exchange in the comments, and he has more recently published a post entitled ‘Disadvantages of Rule-Based Systems (Part 1)’. Whatever the rights and wrongs of our exchange, it clearly failed to generate any agreement or understanding of our different positions. I don't particularly want to promote further argument of that kind, but I do want to take the opportunity of offering a different perspective on rule-processing and an explanation of my comments. For me, the ‘red rag’ lay in Tim’s claim that “...rules alone are highly inefficient for most classes of (not simple) problems” and a later paragraph that appears to equate the simplicity of form (‘IF-THEN-ELSE’) with simplicity of function.   It is not the first time Tim has expressed these views and not the first time I have responded to his assertions.   Indeed, Tim has a long history of commenting on the subject of complex event processing (CEP) and, less often, rule processing in ‘robust’ terms, often asserting that very many other people’s opinions on this subject are mistaken.   In turn, I am of the opinion that, certainly in terms of rule processing, which is an area in which I have a specific interest and knowledge, he is often mistaken. There is no simple answer to the fundamental question ‘what is a rule?’ We use the word in a very fluid fashion in English. Likewise, the term ‘rule processing’, as used widely in IT, is equally difficult to define simplistically. The best way to envisage the term is as a ‘centre of gravity’ within a wider domain. That domain contains many other ‘centres of gravity’, including CEP, statistical analytics, neural networks, natural language processing and so much more. Whole communities tend to gravitate towards and build themselves around some of these centres. The term 'rule processing' is associated with many different technology types, various software products, different architectural patterns, the functional capability of many applications and services, etc. There is considerable variation amongst these different technologies, techniques and products. Very broadly, a common theme is their ability to manage certain types of processing and problem solving through declarative, or semi-declarative, statements of propositional logic bound to action-based consequences. It is generally important to be able to decouple these statements from other parts of an overall system or architecture so that they can be managed and deployed independently.  As a centre of gravity, ‘rule processing’ is no island. It exists in the context of a domain of discourse that is, itself, highly interconnected and continuous.   Rule processing does not, for example, exist in splendid isolation to natural language processing.   On the contrary, an on-going theme of rule processing is to find better ways to express rules in natural language and map these to executable forms.   Rule processing does not exist in splendid isolation to CEP.   On the contrary, an event processing agent can reasonably be considered as a rule engine (a theme in ‘Power of Events’ by David Luckham).   Rule processing does not live in splendid isolation to statistical approaches such as Bayesian analytics. On the contrary, rule processing and statistical analytics are highly synergistic.   Rule processing does not even live in splendid isolation to neural networks. For example, significant research has centred on finding ways to translate trained nets into explicit rule sets in order to support forms of validation and facilitate insight into the knowledge stored in those nets. What about simplicity of form?   Many rule processing technologies do indeed use a very simple form (‘If...Then’, ‘When...Do’, etc.)   However, it is a fundamental mistake to equate simplicity of form with simplicity of function.   It is absolutely mistaken to suggest that simplicity of form is a barrier to the efficient handling of complexity.   There are countless real-world examples which serve to disprove that notion.   Indeed, simplicity of form is often the key to handling complexity. Does rule processing offer a ‘one size fits all’. No, of course not.   No serious commentator suggests it does.   Does the design and management of large knowledge bases, expressed as rules, become difficult?   Yes, it can do, but that is true of any large knowledge base, regardless of the form in which knowledge is expressed.   The measure of complexity is not a function of rule set size or rule form.  It tends to be correlated more strongly with the size of the ‘problem space’ (‘search space’) which is something quite different.   Analysis of the problem space and the algorithms we use to search through that space are, of course, the very things we use to derive objective measures of the complexity of a given problem. This is basic computer science and common practice. Sailing a Dreadnaught through the sea of information technology and lobbing shells at some of the islands we encounter along the way does no one any good.   Building bridges and causeways between islands so that the inhabitants can collaborate in open discourse offers hope of real progress.

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  • Splitting Graph into distinct polygons in O(E) complexity

    - by Arthur Wulf White
    If you have seen my last question: trapped inside a Graph : Find paths along edges that do not cross any edges How do you split an entire graph into distinct shapes 'trapped' inside the graph(like the ones described in my last question) with good complexity? What I am doing now is iterating over all edges and then starting to traverse while always taking the rightmost turn. This does split the graph into distinct shapes. Then I eliminate all the excess shapes (that are repeats of previous shapes) and return the result. The complexity of this algorithm is O(E^2). I am wondering if I could do it in O(E) by removing edges I already traversed previously. My current implementation of that returns unexpected results.

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  • Not enough space left in the hard drive. How to proceed?

    - by jimbobjgr
    Where do I begin... I can hardly do anything on Ubuntu 12.04. I am very close to removing and returning to Windows. First I could not load it because the graphics appeared to be running low but somehow that stopped happening and I could log on. Now I can not download anything or I get this message Cannot write: No space left on device. I tried trouble shooting this issue but every time I try and fix the problem I am blocked by this message E: Write error - write (28: No space left on device) E: Can't mmap an empty file E: Failed to truncate file - ftruncate (9: Bad file descriptor) E: The package lists or status file could not be parsed or opened. $ OLD=$(ls -tr /boot/vmlinuz-* | head -n -2 | cut -d- -f2- | awk '{print "linux-image-" $0}') Ubuntu is also running incredibly slow and I cant get anything done! Please help this is driving me mad!

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  • [codeigniter] extra white space

    - by Wiika
    Hi all, i getting extra space at the beginning of page ( output ), the thing is i didn't edit any file, i just uploaded the codeigniter framework to my server, and in the welcome page i get that space , in localhost i don't get it, i changed all files to utf8, checked if there is any space before ( there is no ? ) did someone had to deal with this issue before ?

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