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  • Search Engine Optimization For Beginners

    Learning about the SEO techniques can be scary and a bit overwhelming to say the least. If you do not know anything about SEO now is the time to learn, before trying to do it with just a little bit of knowledge, you will fail if you do it that way.

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  • 7 Steps to Search Engine Optimization

    Internet Marketing is a new media and latest trend to advertising which moving away from conventional advertising like print media, electronic media and etc. Internet marketing is a holistic and effective approach on internet to reach wider and more defined target marketing.

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  • Search Engine Optimization

    The best way a company can inform its public about itself is through its website. Most corporations and firms today have a website to their name. The internet has proved itself to be an open market for all kinds of products; the only problem being the trouble of attracting internet users.

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  • Search Engine Optimization Terms

    By the time you complete this multiple lesson tutorial, you'll know just what it takes to score top search engine positions for your Web sites. You'll understand how search engines crawl the Web, how they rank Web sites, and how they find previously undiscovered sites. You'll master the important HTML tags that are your key to getting your sites on a search engine's radar, and you'll see why it's important to amass as many potential keywords as possible.

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  • What is SEO (Search Engine Optimization)?

    SEO in its most basic form is a series of steps taken to make a web site search engine friendly and have it show up in the search engines. At a more advanced level, SEO can be implemented to allow the web site in question to rank high in the search engines, preferably in the first few positions.

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  • Oracle Database 12c ?????(??10?29?)

    - by user763299
    ?????/??: ????????? Oracle Database 12c ?????,??????????????????????????????????,?????????? Oracle ????,???? Oracle ???????????????,???? Database 12c ??????????,??????????????????????????? ????????,???????????? Database 12c ???????????????: ? Oracle SQL Developer ?????????? ? Oracle SQL Developer ??????? ?? Oracle Enterprise Manager ?????????? ??? 2013?10?29? ??? ???????: ?? 13391606778 010-64418595-6056 Email:[email protected] ???? 09:00-09:15 ?? 09:15-10:15 ????:Oracle Database 12c ?? ???? Oracle Database 12c ???????????,???????????????????????????? 10:15-11:15 Oracle????????? 11:15-11:30 ?? 11:30-12:15 ????????? Oracle Database 12c ?? Oracle ?????????????????????????????? 12:15-12:30 ?? 12:30-13:30 ?? 13:30-14:15 ????:? Oracle SQL Developer ????????? ????????????????? - ?????????????? - ??????????? - ???????? 14:15-15:15 ????:? Oracle SQL Developer ???Data Redaction Data Redaction?????????????????: - ??Redaction?? - ??Redaction?? - ????Redaction?? - ??Redaction??????? - ??Redaction?? - ??Redaction?? 15:15-16:00 ????:?? Oracle Enterprise Manager Express ?????????? ??????: - ?? Oracle Enterprise Manager Express - ?? Oracle Enterprise Manager Express ??????? 16:00 ?? ??????????????,??????????????????????? ???? © 2013,??????/????????????? ???? | ????????? | ????

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  • ???????/???30????!Active Directory+Oracle Database

    - by Yusuke.Yamamoto
    ????? ??:2010/09/08 ??:??????/?? Oracle Database 11g ???Active Directory ????????????????????????????????????????????????????????? Active Directory ??Active Directory ? Oracle Database ???Active Directory ? Oracle Database ????????????? ????????? ????????????????? http://otndnld.oracle.co.jp/ondemand/otn-seminar/movie/AD_Oracle_09081500.wmv http://www.oracle.com/technetwork/jp/content/20100908-ad-oracle-244715-ja.pdf

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  • Which of these methods provides for the fastest page loading?

    - by chromedude
    I am building a database in MySQL that will be accessed by PHP scripts. I have a table that is the activity stream. This includes everything that goes on on the website (following of many different things, liking, upvoting etc.). From this activity stream I am going to run an algorithm for each user depending on their activity and display relevant activity. Should I create another table that stores the activity for each user once the algorithm has been run on the activity or should I run the algorithm on the activity table every time the user accesses the site? UPDATE:(this is what is above except rephrased hopefully in an easier to understand way) I have a database table called activity. This table creates a new row every time an action is performed by a user on the website. Every time a user logs in I am going to run an algorithm on the new rows (since the users last login) in the table (activity) that apply to them. For example if the user is following a user who upvoted a post in the activity stream that post will be displayed when the user logs in. I want the ability for the user to be able to access previous content applying to them. Would it be easiest to create another table that saved the rows that have already been run over with the algorithm except attached to individual users names? (a row can apply to multiple different users)

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  • Speeding up a group by date query on a big table in postgres

    - by zaius
    I've got a table with around 20 million rows. For arguments sake, lets say there are two columns in the table - an id and a timestamp. I'm trying to get a count of the number of items per day. Here's what I have at the moment. SELECT DATE(timestamp) AS day, COUNT(*) FROM actions WHERE DATE(timestamp) >= '20100101' AND DATE(timestamp) < '20110101' GROUP BY day; Without any indices, this takes about a 30s to run on my machine. Here's the explain analyze output: GroupAggregate (cost=675462.78..676813.42 rows=46532 width=8) (actual time=24467.404..32417.643 rows=346 loops=1) -> Sort (cost=675462.78..675680.34 rows=87021 width=8) (actual time=24466.730..29071.438 rows=17321121 loops=1) Sort Key: (date("timestamp")) Sort Method: external merge Disk: 372496kB -> Seq Scan on actions (cost=0.00..667133.11 rows=87021 width=8) (actual time=1.981..12368.186 rows=17321121 loops=1) Filter: ((date("timestamp") >= '2010-01-01'::date) AND (date("timestamp") < '2011-01-01'::date)) Total runtime: 32447.762 ms Since I'm seeing a sequential scan, I tried to index on the date aggregate CREATE INDEX ON actions (DATE(timestamp)); Which cuts the speed by about 50%. HashAggregate (cost=796710.64..796716.19 rows=370 width=8) (actual time=17038.503..17038.590 rows=346 loops=1) -> Seq Scan on actions (cost=0.00..710202.27 rows=17301674 width=8) (actual time=1.745..12080.877 rows=17321121 loops=1) Filter: ((date("timestamp") >= '2010-01-01'::date) AND (date("timestamp") < '2011-01-01'::date)) Total runtime: 17038.663 ms I'm new to this whole query-optimization business, and I have no idea what to do next. Any clues how I could get this query running faster?

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  • Why is WPO(whole-program optimization) not doing any improvements in my program size? (FPC 2.4.0)

    - by Gregory Smith
    I use FPC 2.4.0 for WinXP(binary from the official page), also tryed with same version but compiled from source on my comp. I put something like this: I:\pascal\fpc-2.4.0.source\fpc-2.4.0\compiler\ppc386 -FWserver-1.wpo -OWsymbolliveness -CX -XX -Xs- -al -Os -oServer1.o Server I:\pascal\fpc-2.4.0.source\fpc-2.4.0\compiler\ppc386 -FWserver-2.wpo -OWsymbolliveness -Fwserver-1.wpo -Owsymbolliveness -CX -XX -Xs- -al -Os -oServer2.o Server ..(up to 100 times) but always same .wpo files, and same .o sizes(.s, assembly files change intermittently) I also not(through compiler messages), that not used variables are still alive. Also tryed -OWall -owall What am i doing wrong?

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  • Pure Java open-source libraries for portfolio selection (= constrained, non-linear optimization)?

    - by __roland__
    Does anyone know or has experience with a pure Java library to select portfolios or do some similar kinds of quadratic programming with constraints? There seems to be a lot of tools, as already discussed elsewhere - but what I would like to use is a pure Java implementation. Since I want to call the library from within another open-source software with a BSD-ish license I would prefer LGPL over GPL. Any help is appreciated. If you don't know such libraries, which is the most simple algorithm you would suggest to implement? It has to cope with an inequality constraint (all x_i = 0) and an equality constraint (sum of all x_i = 1).

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  • Some optimization about the code (computing ranks of a vector)?

    - by user1748356
    The following code is a function (performance-critical) to compute tied ranks of a vector: mergeSort(x,inds,ci); //a sort function to sort vector x of length ci, also returns keys (inds) of x. int tj=0; double xi=x[0]; for (int j = 1; j < ci; ++j) { if (x[j] > xi) { double rankvalue = 0.5 * (j - 1 + tj); for (int k = tj; k < j; ++k) { ranks[inds[k]]=rankvalue; }; tj = j; xi = x[j]; }; }; double rankvalue = 0.5 * (ci - 1 + tj); for (int k = tj; k < ci; ++k) { ranks[inds[k]]=rankvalue; }; The problem is, the supposed performance bottleneck mergeSort(), which is O(NlogN) is several times faster than the other part of codes (which is O(N)), which suggests there is room for huge improvment with the other part of the codes, any advices?

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  • R: Are there any alternatives to loops for subsetting from an optimization standpoint?

    - by Adam
    A recurring analysis paradigm I encounter in my research is the need to subset based on all different group id values, performing statistical analysis on each group in turn, and putting the results in an output matrix for further processing/summarizing. How I typically do this in R is something like the following: data.mat <- read.csv("...") groupids <- unique(data.mat$ID) #Assume there are then 100 unique groups results <- matrix(rep("NA",300),ncol=3,nrow=100) for(i in 1:100) { tempmat <- subset(data.mat,ID==groupids[i]) #Run various stats on tempmat (correlations, regressions, etc), checking to #make sure this specific group doesn't have NAs in the variables I'm using #and assign results to x, y, and z, for example. results[i,1] <- x results[i,2] <- y results[i,3] <- z } This ends up working for me, but depending on the size of the data and the number of groups I'm working with, this can take up to three days. Besides branching out into parallel processing, is there any "trick" for making something like this run faster? For instance, converting the loops into something else (something like an apply with a function containing the stats I want to run inside the loop), or eliminating the need to actually assign the subset of data to a variable?

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  • R optimization: How can I avoid a for loop in this situation?

    - by chrisamiller
    I'm trying to do a simple genomic track intersection in R, and running into major performance problems, probably related to my use of for loops. In this situation, I have pre-defined windows at intervals of 100bp and I'm trying to calculate how much of each window is covered by the annotations in mylist. Graphically, it looks something like this: 0 100 200 300 400 500 600 windows: |-----|-----|-----|-----|-----|-----| mylist: |-| |-----------| So I wrote some code to do just that, but it's fairly slow and has become a bottleneck in my code: ##window for each 100-bp segment windows <- numeric(6) ##second track mylist = vector("list") mylist[[1]] = c(1,20) mylist[[2]] = c(120,320) ##do the intersection for(i in 1:length(mylist)){ st <- floor(mylist[[i]][1]/100)+1 sp <- floor(mylist[[i]][2]/100)+1 for(j in st:sp){ b <- max((j-1)*100, mylist[[i]][1]) e <- min(j*100, mylist[[i]][2]) windows[j] <- windows[j] + e - b + 1 } } print(windows) [1] 20 81 101 21 0 0 Naturally, this is being used on data sets that are much larger than the example I provide here. Through some profiling, I can see that the bottleneck is in the for loops, but my clumsy attempt to vectorize it using *apply functions resulted in code that runs an order of magnitude more slowly. I suppose I could write something in C, but I'd like to avoid that if possible. Can anyone suggest another approach that will speed this calculation up?

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