How sliding windows work in most of our modern sunrooms.
hvsunrooms.com
#sunrooms #hudsonvalley #fourseasons #hudsonvalleyny #faq #sunroomfaq #slidingwindow
hvsunrooms.com
#sunrooms #hudsonvalley #fourseasons #hudsonvalleyny #faq #sunroomfaq #slidingwindow
September 1, 2026 at 10:31 AM
How sliding windows work in most of our modern sunrooms.
hvsunrooms.com
#sunrooms #hudsonvalley #fourseasons #hudsonvalleyny #faq #sunroomfaq #slidingwindow
hvsunrooms.com
#sunrooms #hudsonvalley #fourseasons #hudsonvalleyny #faq #sunroomfaq #slidingwindow
Bioinformatics trick, repurposed: you don't feed a whole gene sequence through at once, you slide a small window along it, overlapping each step.
Turns out that AI fixes context degradation too. To use this visit
prayogashaala.com/slidingwindow/
#AIliteracy #PromptEngineering
Turns out that AI fixes context degradation too. To use this visit
prayogashaala.com/slidingwindow/
#AIliteracy #PromptEngineering
August 28, 2026 at 1:40 PM
Bioinformatics trick, repurposed: you don't feed a whole gene sequence through at once, you slide a small window along it, overlapping each step.
Turns out that AI fixes context degradation too. To use this visit
prayogashaala.com/slidingwindow/
#AIliteracy #PromptEngineering
Turns out that AI fixes context degradation too. To use this visit
prayogashaala.com/slidingwindow/
#AIliteracy #PromptEngineering
ident <- function(w) w
x <- c(5,12,13,3,4,5)
slidingWindow(x,3,ident)
[,1] [,2] [,3]
[1,] 5 12 13
[2,] 12 13 3
[3,] 13 3 4
[4,] 3 4 5
3/3
December 8, 2024 at 5:44 AM
ident <- function(w) w
x <- c(5,12,13,3,4,5)
slidingWindow(x,3,ident)
[,1] [,2] [,3]
[1,] 5 12 13
[2,] 12 13 3
[3,] 13 3 4
[4,] 3 4 5
3/3
slidingWindow <- function(x,windowWidth,f,matTransp=TRUE) {
n <- length(x)
tmp <- sapply(1:(n-windowWidth+1),
function(j) { f(x[j:(j+windowWidth-1)]) })
if (is.matrix(tmp) && matTransp) return(t(tmp))
tmp
}
2/
December 8, 2024 at 5:43 AM
slidingWindow <- function(x,windowWidth,f,matTransp=TRUE) {
n <- length(x)
tmp <- sapply(1:(n-windowWidth+1),
function(j) { f(x[j:(j+windowWidth-1)]) })
if (is.matrix(tmp) && matTransp) return(t(tmp))
tmp
}
2/
Smooth Operations Find the best sliding window for your bedroom. Precision-engineered rollers ensure our sliding window glass design for home remains silent and smooth for years. #SlidingWindow #lumanisystems
Gallery: www.lumanisystems.com/gallery.php
Services: www.lumanisystems.com/index.html
Gallery: www.lumanisystems.com/gallery.php
Services: www.lumanisystems.com/index.html
May 15, 2026 at 6:39 AM
Smooth Operations Find the best sliding window for your bedroom. Precision-engineered rollers ensure our sliding window glass design for home remains silent and smooth for years. #SlidingWindow #lumanisystems
Gallery: www.lumanisystems.com/gallery.php
Services: www.lumanisystems.com/index.html
Gallery: www.lumanisystems.com/gallery.php
Services: www.lumanisystems.com/index.html
Brute Force vs. Sliding Window
The brute force approach would check all possible substrings and resulting in O(n²)
The idea is to dynamically expand and contract a window while tracking seen characters, which solves the problem in O(n).
#leetcode
#slidingwindow
#complexity
#3
The brute force approach would check all possible substrings and resulting in O(n²)
The idea is to dynamically expand and contract a window while tracking seen characters, which solves the problem in O(n).
#leetcode
#slidingwindow
#complexity
#3
April 1, 2025 at 3:38 PM
Brute Force vs. Sliding Window
The brute force approach would check all possible substrings and resulting in O(n²)
The idea is to dynamically expand and contract a window while tracking seen characters, which solves the problem in O(n).
#leetcode
#slidingwindow
#complexity
#3
The brute force approach would check all possible substrings and resulting in O(n²)
The idea is to dynamically expand and contract a window while tracking seen characters, which solves the problem in O(n).
#leetcode
#slidingwindow
#complexity
#3
After going over the theory ☝️🏾, watch me implement a bunch of operations with the Gatherer API:
* map
* filter
* flatMapIf
* takeWhileIncluding
* limit
* increasing
* runningAverage
* fixedGroups
* slidingWindow
* sorted
* increasingSequences
* map
* filter
* flatMapIf
* takeWhileIncluding
* limit
* increasing
* runningAverage
* fixedGroups
* slidingWindow
* sorted
* increasingSequences
Implementing New Java Stream Operations
JEP 461 proposes `Stream::gather` and `Gatherer` - a new intermediate meta-operation that can be used to implement all kinds of specific operations, from exi...
www.youtube.com
November 2, 2023 at 7:26 AM
After going over the theory ☝️🏾, watch me implement a bunch of operations with the Gatherer API:
* map
* filter
* flatMapIf
* takeWhileIncluding
* limit
* increasing
* runningAverage
* fixedGroups
* slidingWindow
* sorted
* increasingSequences
* map
* filter
* flatMapIf
* takeWhileIncluding
* limit
* increasing
* runningAverage
* fixedGroups
* slidingWindow
* sorted
* increasingSequences
🎯 Journey to Big Tech #23 : Review Sliding window, PrefixSum, Trie algorithm
✅ Learned and Completed Trie algorithm
✅ Completed Slinding Window review
✅ Almost completed PrefixSum review
#algorithm #prefixsum #slidingwindow #trie
✅ Learned and Completed Trie algorithm
✅ Completed Slinding Window review
✅ Almost completed PrefixSum review
#algorithm #prefixsum #slidingwindow #trie
May 17, 2025 at 6:04 PM
🎯 Journey to Big Tech #23 : Review Sliding window, PrefixSum, Trie algorithm
✅ Learned and Completed Trie algorithm
✅ Completed Slinding Window review
✅ Almost completed PrefixSum review
#algorithm #prefixsum #slidingwindow #trie
✅ Learned and Completed Trie algorithm
✅ Completed Slinding Window review
✅ Almost completed PrefixSum review
#algorithm #prefixsum #slidingwindow #trie