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  • Reduce weight in healthy way - Day 3

    - by krnites
    So I am on Day 3 and what I did today was totally opposite of what I should have done. It seems I will take ever to loose what I had aim for. Today I had ate more than 5000 Calorie, had soda drinks and very oily indian food. On my Day 2 post some one commented that with the number that I have I will loose 1 lbs in a week, but my friends it seems I will gain 5 lbs in a week. I have to straighten my act and really focus on what I want to achieve. I am going to hit the gym and going to burn atleast 500 calorie today.Piece of advice - don't eat fried, oily  and junk food.  Try to have as much as vegetables in your food. I understand its not possible as being a normal person and not a diet freak I know its impossible to be away from Taco or burger and not drink Coke, but to achieve something you have to loose something.

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  • Chain-Sys Uses Oracle Business Accelerators to Reduce Implementation Costs by 25%

    - by LanaProut
    Normal 0 false false false EN-US X-NONE X-NONE Find out how Oracle Business Accelerators for Oracle E-Business Suite and Chain-Sys's appLOAD tool reduced implementation costs by 25% for a major Indian power and infrastructure company. Click here to listen to the 11 minute AppCast. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}

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  • How to reduce MDX code redundancy in SQL Server Analysis Services (SSAS)

    To query an Analysis Services cube, MDX is used as the query language. In most business settings, one would find a set of queries that are common across a number of user query requirements. To cater to this, even with a modest size IT team, there is a good chance that the same queries are developed redundantly either within a SSAS MDX script or repetitively in an ad-hoc manner in client applications. In this tip we would look at how to reuse queries without redeveloping them over and over.

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  • Helping to Reduce Page Compression Failures Rate

    - by Vasil Dimov
    When InnoDB compresses a page it needs the result to fit into its predetermined compressed page size (specified with KEY_BLOCK_SIZE). When the result does not fit we call that a compression failure. In this case InnoDB needs to split up the page and try to compress again. That said, compression failures are bad for performance and should be minimized.Whether the result of the compression will fit largely depends on the data being compressed and some tables and/or indexes may contain more compressible data than others. And so it would be nice if the compression failure rate, along with other compression stats, could be monitored on a per table or even on a per index basis, wouldn't it?This is where the new INFORMATION_SCHEMA table in MySQL 5.6 kicks in. INFORMATION_SCHEMA.INNODB_CMP_PER_INDEX provides exactly this helpful information. It contains the following fields: +-----------------+--------------+------+ | Field | Type | Null | +-----------------+--------------+------+ | database_name | varchar(192) | NO | | table_name | varchar(192) | NO | | index_name | varchar(192) | NO | | compress_ops | int(11) | NO | | compress_ops_ok | int(11) | NO | | compress_time | int(11) | NO | | uncompress_ops | int(11) | NO | | uncompress_time | int(11) | NO | +-----------------+--------------+------+ similarly to INFORMATION_SCHEMA.INNODB_CMP, but this time the data is grouped by "database_name,table_name,index_name" instead of by "page_size".So a query like SELECT database_name, table_name, index_name, compress_ops - compress_ops_ok AS failures FROM information_schema.innodb_cmp_per_index ORDER BY failures DESC; would reveal the most problematic tables and indexes that have the highest compression failure rate.From there on the way to improving performance would be to try to increase the compressed page size or change the structure of the table/indexes or the data being stored and see if it will have a positive impact on performance.

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  • The need to reduce mesh count

    - by OJW
    In Panda3d, I load a model and place 10000 references to it in the scene-graph. It runs at (say) 2Hz. I load a 3d model containing 10000 copies of that exact same object, and it runs at (say) 60Hz. As does using the flattenStrong() command which is effectively the same thing but at runtime. So the question is: is this behaviour a peculiarity of Panda3d, or is it a fundamental law which applies to all games engines?

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  • 5 Ways to Reduce the Google Sandbox Effect

    The most used and most popular search engine is Google all over the World Wide Web. Google is very much strict with the SEO practices every website is using. Google sandbox is known as the effect after a website is put into test if it followed the policy and guidelines of Google.

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  • 5 Ways to Reduce the Google Sandbox Effect

    The most used and most popular search engine is Google all over the World Wide Web. Google is very much strict with the SEO practices every website is using. Google sandbox is known as the effect after a website is put into test if it followed the policy and guidelines of Google.

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  • Reduce size of MP4

    - by testing
    I have a MP4 file with a lengh of 22:44. Here are the details: Video: width: 720 px height: 404 px data bitrate: 1022 kBit/s overall bitrate: 1182 kBit/s fps: 24 codec: H264 - MPEG4 AVC (part 10) (avc1) Audio: bitrate: 159 kBit/s stereo sample rate: 48 kHz codec: MPEG AAC Audio (mp4a) I thought I can reduce the current filesize (about 200 MB) by reducing the width and the height (420 x 236). I tried different programs: Handbrake, Format Factory, Next Video Converter and Super. The first three didn't worked as expected: Handbrake has a bug by setting the width and the height, the next two doesn't allow the fine setting of the videosize (only presets of width and height). Super seems to be the best, but I didn't found a setting which reduces the file size. I reduced the width and the height but only got 20 MB less. Now I tried the xth setting and I still get a too high file size. I want to reduce the filesize to 100 MB or less. The ouput format should be FLV or MP4, because I need this for flowplayer. Which settings of SUPER or which program should I use to reduce the file size? Of course the video should still be viewable.

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  • reduce image size in bytes without resize and quality lose in c#

    - by SR Dusad
    Hi I m using C#.NET 4.0 I have an jpeg image and i want to reduce its size in bytes .I don't want to change the image size in manner of height and width and not want to lose image quality.Some bit of reduce quality is not an issue. I try to make it a thumbnail image but it reduce the size according to height and width. I can't found any solution. Any type help will be appreciated..

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  • JavaFX - reduce() function to show how to pass functions as parameters

    - by Helper Method
    At the moment I'm writing a JavaFX guide for Java developers. In order to show how to pass a function to another funtion i adopted the reduce() function found in Effective Java: function reduce(seq: Integer[], f: function(: Integer, : Integer): Integer, init: Integer) { var result = init; for (i in seq) { result = f(i, result); } result } def nums = [1 .. 10]; println(reduce(nums, function(a: Integer, b: Integer) { a + b }, 0)); // prints 55 println(reduce(nums, function(a: Integer, b: Integer) { a * b }, 0)); // prints 3628800 Now I wonder if this example is not to hard for someone starting to learn JavaFX. The tutorial is targeted to programmers with a solid understanding of Java, yet I'm not quite sure about the usefulness of the example. Any ideas?

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  • Unexpected result from reduce function

    - by StackedCrooked
    I would like to get the smallest element from a vector. For this I use combine the reduce and min functions. However, when providing my own implementation of min I get unexpected results: user=> (reduce (fn [x y] (< x y) x y) [1 2 3 2 1 0 1 2]) 2 user=> (reduce min [1 2 3 2 1 0 1 2 3]) 0 The reduce with standard min returns 0 as expected. However, when I provide my own implementation it returns 2. What am I doing wrong?

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  • Need Explanation of couchdb reduce function

    - by Alan
    From http://wiki.apache.org/couchdb/Introduction_to_CouchDB_views The couchdb reduce function is defined as function (key, values, rereduce) { return sum(values); } key will be an array whose elements are arrays of the form [key,id] values will be an array of the values emitted for the respective elements in keys i.e. reduce([ [key1,id1], [key2,id2], [key3,id3] ], [value1,value2,value3], false) I am having trouble understanding when/why the array of keys would contain different key values. If the array of keys does contain different key values, how would I deal with it? As an example, assume that my database contains movements between accounts of the form. {"amount":100, "CreditAccount":"account_number", "DebitAccount":"account_number"} I want a view that gives the balance of an account. My map function does: emit( doc.CreditAccount, doc.amount ) emit( doc.DebitAccount, -doc.amount ) My reduce function does: return sum(values); I seem to get the expected results, however I can't reconcile this with the possibility that my reduce function gets different key values. Is my reduce function supposed to group key values first? What kind of result would I return in that case?

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  • reduce memory footprint of java virtual machine

    - by Lorenzo Boccaccia
    I've a citrix server where multiple users use a multiple java application. Is there a way to reduce the memory footprint of the jvm itself? The max heap is already set fairly low (64MB), as the permgen (32MB) space and we're to the point that the jvm itself uses way more memory than the application itself (the committed area is around 350MB) I'm looking for a way to reduce the jvm ram usage or to make the all the applications run within the same jvm or any other way of sharing common pages between running jvm (if possible) or try switch to switch to a jvm if a jvm exists having optimizations relative to this scenario currently using windows 2003 server and sun java virtual machine 1.6

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  • Hadoop reduce task gets hung

    - by user806098
    I set up a hadoop cluster with 4 nodes, When running a map-reduce task, the map task finishes quickly, while the reduce task hangs at 27% percent. I checked the log, it's that the reduce task fails to fetch map output from map nodes. The job tracker log of master shows messages like this: 2011-06-27 19:55:14,748 INFO org.apache.hadoop.mapred.JobTracker: Adding task (REDUCE) 'attempt_201106271953_0001_r_000000_0' to tip task_201106271953_0001_r_000000, for tracker 'tracker_web30.bbn.com.cn:localhost/127.0.0.1:56476' And the name node log of master shows messages like this: 2011-06-27 14:00:52,898 INFO org.apache.hadoop.ipc.Server: IPC Server handler 4 on 54310, call register(DatanodeRegistration(202.106.199.39:50010, storageID=DS-1989397900-202.106.199.39-50010-1308723051262, infoPort=50075, ipcPort=50020)) from 192.168.225.19:16129: error: java.io.IOException: verifyNodeRegistration: unknown datanode 202.106.199.3 9:50010 However, neither the "web30.bbn.com.cn" or 202.106.199.39, 202.106.199.3 is the slave node. I think such ip/domains appear because hadoop fails to resolve a node(first in the Intranet DNS server), then it goes to a higher-level DNS server, later to the top, still fails, then the "junk" ip/domains are returned. But I checked my config, it goes like this: /etc/hosts: 127.0.0.1 localhost.localdomain localhost ::1 localhost6.localdomain6 localhost6 192.168.225.16 master 192.168.225.66 slave1 192.168.225.20 slave5 192.168.225.17 slave17 conf/core-site.xml: hadoop.tmp.dir /root/hadoop_tmp/hadoop_${user.name} fs.default.name hdfs://master:54310 io.sort.mb 1024 hdfs-site.xml: dfs.replication 3 masters: master slaves: master slave1 slave5 slave17 Also, all firewalls(iptables) are turned off, and ssh between each 2 nodes is ok. so I don't know where exact the error comes from. Please help. Thanks a lot.

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  • Python/YACC: Resolving a shift/reduce conflict

    - by Rosarch
    I'm using PLY. Here is one of my states from parser.out: state 3 (5) course_data -> course . (6) course_data -> course . course_list_tail (3) or_phrase -> course . OR_CONJ COURSE_NUMBER (7) course_list_tail -> . , COURSE_NUMBER (8) course_list_tail -> . , COURSE_NUMBER course_list_tail ! shift/reduce conflict for OR_CONJ resolved as shift $end reduce using rule 5 (course_data -> course .) OR_CONJ shift and go to state 7 , shift and go to state 8 ! OR_CONJ [ reduce using rule 5 (course_data -> course .) ] course_list_tail shift and go to state 9 I want to resolve this as: if OR_CONJ is followed by COURSE_NUMBER: shift and go to state 7 else: reduce using rule 5 (course_data -> course .) How can I fix my parser file to reflect this? Do I need to handle a syntax error by backtracking and trying a different rule?

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  • Will An External Audio Interface Reduce CPU Load?

    - by Yar
    I am considering buying a very-low-latency audio interface like this one. One question is if it will reduce CPU load (I'm at about 60%+ and my Macbook has 2.4ghz and 4gigs ram) during intensive audio processing. If the answer is "yes," how will it compare to a different, cheaper firewire audio interface? My thought is that offloading the processing is always the same gain, regardless.

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  • Does BitLocker reduce write reliability?

    - by Unsigned
    For the purposes of this question, BitLocker refers to the BitLocker-to-go variety on a disk with write-caching disabled. NTFS supports metadata journaling, which, although not completely failsafe, does mitigate certain types of potential filesystem errors. Assuming an NTFS volume is protected with BitLocker, does this reduce the failure tolerance? Would a power failure during a write to an NTFS volume, that's protected with BitLocker, be more prone to corruption than on an unencrypted NTFS volume?

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  • Mongo Map Reduce first time

    - by James
    Hello guys, First time Map/Reduce user here, and using MongoDB. I have a lot of page visit data which I'd like to make some sense of by using Map/Reduce. Below is basically what I want to do, but as a total beginner a Map/Reduce, I think this is above my knowledge! Find all visits to current page where external = true within the last 30 days (unix timestamp, I deal with the date ranges in PHP and then the array, not mongo date) Group all visits by referral location For each referral location, calculate how many then went to visit a page which has a certain word in the [tags]. I'm using the normal Mongo PHP extension if that has an impact.

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