Radix sort
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Radix sort is a non-comparative integer sorting algorithm that sorts data by grouping keys based on their individual digit positions and values, from least to most significant. It works by sorting the integers based on the ones place value first, then the tens place, hundreds place, and so on. The algorithm uses buckets to separate numbers into groups based on their digit values, then concatenates the buckets to sort the list.
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Radix Sort
The document describes Radix sort, a sorting algorithm that sorts numbers by their individual digits by making multiple passes through the data. It works by first sorting the numbers based on the units place value, then the tens place, and so on. This is more efficient than other general-purpose sorting algorithms for large data sets with uniformly distributed values. Radix sort runs in O(d(n+k)) time, where d is the number of digits, n is the number of elements, and k is the maximum value of a digit.
3.6 radix sort
Radix sort is a non-comparative sorting algorithm that sorts numeric keys by decomposing them into digits and sorting the digits individually. It works by representing keys as d-digit numbers in some base-k, then sorting the numbers by looking at one column of digits at a time from least to most significant. This requires d passes through the list, resulting in a time complexity of O(d(n+k)) where n is the number of keys and k is the maximum possible digit value, assuming d and k are constants. When d and k are O(n), the overall time complexity is O(n).
Radix sort
Radix sort is a non-comparative sorting algorithm that sorts data by grouping keys based on individual digit values. It uses bucket sort repeatedly on each digit place value, from least to most significant. This requires a number of passes equal to the maximum digit length. Each pass takes O(n+k) time, so the total time complexity is O(d(n+k)) where d is the digit length. Radix sort is very efficient and requires minimal space and data movement compared to other algorithms.
Radix and Shell sort
Shell sort is a sorting algorithm created by Donald Shell in 1959 that improves on insertion sort. It works by comparing elements that are farther apart within the array, making multiple passes with smaller increments to sort the array more efficiently than insertion sort. Radix sort is a non-comparative sorting algorithm that sorts integers by grouping keys based on the place value of their digits using counting or bucket sorts. It has linear time complexity, making it very fast for sorting integers compared to other algorithms. Both algorithms are useful for sorting integers but are limited to that data type.
Selection sort algorithm presentation, selection sort example using power point
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Radix Sort
The document describes Radix sort, a sorting algorithm that sorts numbers by their individual digits by making multiple passes through the data. It works by first sorting the numbers based on the units place value, then the tens place, and so on. This is more efficient than other general-purpose sorting algorithms for large data sets with uniformly distributed values. Radix sort runs in O(d(n+k)) time, where d is the number of digits, n is the number of elements, and k is the maximum value of a digit.
3.6 radix sort
Radix sort is a non-comparative sorting algorithm that sorts numeric keys by decomposing them into digits and sorting the digits individually. It works by representing keys as d-digit numbers in some base-k, then sorting the numbers by looking at one column of digits at a time from least to most significant. This requires d passes through the list, resulting in a time complexity of O(d(n+k)) where n is the number of keys and k is the maximum possible digit value, assuming d and k are constants. When d and k are O(n), the overall time complexity is O(n).
Radix sort
Radix sort is a non-comparative sorting algorithm that sorts data by grouping keys based on individual digit values. It uses bucket sort repeatedly on each digit place value, from least to most significant. This requires a number of passes equal to the maximum digit length. Each pass takes O(n+k) time, so the total time complexity is O(d(n+k)) where d is the digit length. Radix sort is very efficient and requires minimal space and data movement compared to other algorithms.
Radix and Shell sort
Shell sort is a sorting algorithm created by Donald Shell in 1959 that improves on insertion sort. It works by comparing elements that are farther apart within the array, making multiple passes with smaller increments to sort the array more efficiently than insertion sort. Radix sort is a non-comparative sorting algorithm that sorts integers by grouping keys based on the place value of their digits using counting or bucket sorts. It has linear time complexity, making it very fast for sorting integers compared to other algorithms. Both algorithms are useful for sorting integers but are limited to that data type.
Selection sort algorithm presentation, selection sort example using power point
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This document provides an overview of the Radix Sort algorithm presented by Ratul Hasan Shaon, Mostofa Rahat, and Jannatul Ferdaous. It begins by explaining that Radix Sort is a non-comparative sorting algorithm that groups keys based on their individual digit values at specific positions. The document then provides an example of Radix Sort using a 4 pass Least Significant Digit approach to sort a list of numbers. It analyzes the time complexity of Radix Sort and notes its applications in parallel computing.
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Quicksort is a divide and conquer algorithm that works by picking an element as a pivot and partitioning the array around it. It recursively sorts elements before and after the pivot. The average runtime is O(n log n) but it can be O(n^2) in the worst case if the pivot selection is poor. The algorithm involves picking a pivot element, partitioning the array around it, and then recursively sorting the subarrays.
Quick sort
Quicksort is a divide and conquer algorithm that works by partitioning an array around a pivot value and recursively sorting the sub-partitions. It first chooses a pivot element and partitions the array by placing all elements less than the pivot before it and all elements greater than it after it. It then recursively quicksorts the two partitions. This continues until the individual partitions only contain single elements at which point they are sorted. Quicksort has average case performance of O(n log n) time making it very efficient for large data sets.
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This document discusses different sorting algorithms including bubble sort, insertion sort, and selection sort. It provides details on each algorithm, including time complexity, code examples, and graphical examples. Bubble sort is an O(n2) algorithm that works by repeatedly comparing and swapping adjacent elements. Insertion sort also has O(n2) time complexity but is more efficient than bubble sort for small or partially sorted lists. Selection sort finds the minimum value and swaps it into place at each step.
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Selection sort is an in-place comparison sorting algorithm where the minimum element from the unsorted section of the list is selected in each pass and swapped with the first element. It has a time complexity of O(n2) making it inefficient for large lists. The algorithm involves dividing the list into sorted and unsorted sublists, finding the minimum element in the unsorted sublist, swapping it with the first element and moving the imaginary wall between the two sublists by one element. This process is repeated for n-1 passes to completely sort an input list of n elements. Pseudocode for the algorithm using a nested for loop to find the minimum element and swap it is also provided.
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1. A SkipList is a data structure that maintains sorted keys across multiple levels, with each level being a sorted linked list. Keys in higher levels point to the same key in lower levels.
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3. The number of levels a key is inserted into is determined randomly, with the expected number of levels being O(log n).
It elective cs366 barizo radix.docx
Radix sort is a non-comparative integer sorting algorithm that sorts data by grouping keys based on individual digits. It treats integers as strings of digits, sorting first by least significant digit then by most significant digit in multiple passes. Radix sort runs faster than comparison-based sorting for short keys due to avoiding comparisons, but requires more space and is less flexible since it only works on integer keys. The document then provides a step-by-step example of radix sort to sort a list of 2-digit numbers.
Radix sorting
This document discusses radix sorting and provides details on its implementation. Radix sorting is a non-comparative sorting algorithm that uses bucket sorting to sort integers by their individual digits in multiple passes. Pseudocode and C code examples are provided to demonstrate how radix sorting works by distributing numbers into buckets based on their digits and recombining the buckets in sorted order. The time complexity of radix sorting is linear for a constant number of digits.
Radix and shell sort
The document describes the radix sort algorithm. It begins with a brief history of sorting algorithms that led to radix sort. It then defines radix sort as an integer sorting algorithm that groups keys by individual digit place values using counting sort as a subroutine. The operation of radix sort is explained and a C++ program implementing radix sort on an array of integers is provided, along with sample output.
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The document describes the bucket sorting algorithm. It works by dividing the input range into buckets and distributing elements into the buckets based on their values. Each bucket is then sorted individually, usually with insertion sort, and concatenated together in order. The time complexity is O(n) when the number of buckets k is Θ(n), as distributing elements takes O(n) time, sorting each bucket takes O(n log(n/k)) time, and concatenating takes O(k) time. Bucket sort assumes uniform distribution of input elements across the range.
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Quicksort is a divide and conquer algorithm that works by partitioning an array around a pivot value and recursively sorting the subarrays. It first selects a pivot element and partitions the array by moving all elements less than the pivot before it and greater elements after it. The subarrays are then recursively sorted through this process. When implemented efficiently with an in-place partition, quicksort is one of the fastest sorting algorithms in practice, with average case performance of O(n log n) time but worst case of O(n^2) time.
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Quicksort is a recursive divide-and-conquer algorithm that works by selecting a pivot element and partitioning the array into two subarrays of elements less than and greater than the pivot. It recursively sorts the subarrays. The divide step does all the work by partitioning, while the combine step does nothing. It has average case performance of O(n log n) but worst case of O(n^2). Bubble sort repeatedly swaps adjacent elements that are out of order until the array is fully sorted. It has a simple implementation but poor performance of O(n^2).
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This presentation discusses several sorting algorithms: insertion sort, merge sort, quick sort, and counting sort. Insertion sort iterates through a list and inserts each element into the sorted position. Merge sort and quick sort are divide-and-conquer algorithms that split the list into halves, sort the halves, and merge the results. Counting sort works by counting the number of objects that have each distinct key value. The algorithms are analyzed and their time and space complexities are compared.
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Radix sort is a non-comparative integer sorting algorithm that sorts data by grouping keys based on individual digits in specific positions. It works by making multiple passes over the data, sorting by one digit on each pass from the least significant to the most significant digit. Radix sort has advantages of being fast for short integer keys and being useful for suffix array construction. Its disadvantages include being less flexible than other sorts since it depends on digits, having a greater constant than some other algorithms, and using more space than in-place sorting algorithms like quicksort. Radix sort can operate on either the least significant digit (LSD) or most significant digit (MSD) and examples are provided to illustrate the sorting process.
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This document provides an overview of the Radix Sort algorithm presented by Ratul Hasan Shaon, Mostofa Rahat, and Jannatul Ferdaous. It begins by explaining that Radix Sort is a non-comparative sorting algorithm that groups keys based on their individual digit values at specific positions. The document then provides an example of Radix Sort using a 4 pass Least Significant Digit approach to sort a list of numbers. It analyzes the time complexity of Radix Sort and notes its applications in parallel computing.
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Quicksort is a divide and conquer algorithm that works by picking an element as a pivot and partitioning the array around it. It recursively sorts elements before and after the pivot. The average runtime is O(n log n) but it can be O(n^2) in the worst case if the pivot selection is poor. The algorithm involves picking a pivot element, partitioning the array around it, and then recursively sorting the subarrays.
Quick sort
Quicksort is a divide and conquer algorithm that works by partitioning an array around a pivot value and recursively sorting the sub-partitions. It first chooses a pivot element and partitions the array by placing all elements less than the pivot before it and all elements greater than it after it. It then recursively quicksorts the two partitions. This continues until the individual partitions only contain single elements at which point they are sorted. Quicksort has average case performance of O(n log n) time making it very efficient for large data sets.
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This document discusses different sorting algorithms including bubble sort, insertion sort, and selection sort. It provides details on each algorithm, including time complexity, code examples, and graphical examples. Bubble sort is an O(n2) algorithm that works by repeatedly comparing and swapping adjacent elements. Insertion sort also has O(n2) time complexity but is more efficient than bubble sort for small or partially sorted lists. Selection sort finds the minimum value and swaps it into place at each step.
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Selection sort is an in-place comparison sorting algorithm where the minimum element from the unsorted section of the list is selected in each pass and swapped with the first element. It has a time complexity of O(n2) making it inefficient for large lists. The algorithm involves dividing the list into sorted and unsorted sublists, finding the minimum element in the unsorted sublist, swapping it with the first element and moving the imaginary wall between the two sublists by one element. This process is repeated for n-1 passes to completely sort an input list of n elements. Pseudocode for the algorithm using a nested for loop to find the minimum element and swap it is also provided.
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1. A SkipList is a data structure that maintains sorted keys across multiple levels, with each level being a sorted linked list. Keys in higher levels point to the same key in lower levels.
2. Searching, inserting, and deleting keys takes O(log n) time on average where n is the number of keys, by traversing the appropriate levels starting from the top level.
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It elective cs366 barizo radix.docx
Radix sort is a non-comparative integer sorting algorithm that sorts data by grouping keys based on individual digits. It treats integers as strings of digits, sorting first by least significant digit then by most significant digit in multiple passes. Radix sort runs faster than comparison-based sorting for short keys due to avoiding comparisons, but requires more space and is less flexible since it only works on integer keys. The document then provides a step-by-step example of radix sort to sort a list of 2-digit numbers.
Radix sorting
This document discusses radix sorting and provides details on its implementation. Radix sorting is a non-comparative sorting algorithm that uses bucket sorting to sort integers by their individual digits in multiple passes. Pseudocode and C code examples are provided to demonstrate how radix sorting works by distributing numbers into buckets based on their digits and recombining the buckets in sorted order. The time complexity of radix sorting is linear for a constant number of digits.
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The document describes the radix sort algorithm. It begins with a brief history of sorting algorithms that led to radix sort. It then defines radix sort as an integer sorting algorithm that groups keys by individual digit place values using counting sort as a subroutine. The operation of radix sort is explained and a C++ program implementing radix sort on an array of integers is provided, along with sample output.
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The document describes the bucket sorting algorithm. It works by dividing the input range into buckets and distributing elements into the buckets based on their values. Each bucket is then sorted individually, usually with insertion sort, and concatenated together in order. The time complexity is O(n) when the number of buckets k is Θ(n), as distributing elements takes O(n) time, sorting each bucket takes O(n log(n/k)) time, and concatenating takes O(k) time. Bucket sort assumes uniform distribution of input elements across the range.
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This document discusses binary search trees, including:
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- New nodes are inserted by recursively searching the tree and placing the node in the proper position to maintain ordering - left subtrees must be less than the root and right subtrees greater than or equal.
- The insert function recursively moves down the tree until an unused leaf node is found in the correct position based on comparing its data to the data being inserted.
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The document provides an overview of the quick sort algorithm through diagrams and explanations. It begins by introducing quick sort and stating that it is one of the fastest sorting algorithms because it runs in O(n log n) time and uses less memory than other algorithms like merge sort. It then provides step-by-step examples to demonstrate how quick sort works by picking a pivot element, partitioning the array around the pivot, and recursively sorting the subarrays. The summary concludes by restating that quick sort is an efficient sorting algorithm due to its speed and memory usage.
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Quicksort is a divide and conquer algorithm that works by partitioning an array around a pivot value and recursively sorting the subarrays. It first selects a pivot element and partitions the array by moving all elements less than the pivot before it and greater elements after it. The subarrays are then recursively sorted through this process. When implemented efficiently with an in-place partition, quicksort is one of the fastest sorting algorithms in practice, with average case performance of O(n log n) time but worst case of O(n^2) time.
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Watch the video lesson and access the hands-on exercises here: https://softuni.org/code-lessons/java-foundations-certification-maps-lambda-and-stream-api/
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Bucket sort is a distribution sorting algorithm that works by distributing elements of an array into buckets. It then sorts the elements within each bucket using a simpler sorting algorithm like insertion sort. The sorted buckets are then concatenated together to produce the final sorted array. Radix sort is a multiple pass sorting algorithm that distributes elements into buckets based on the value of each digit of the key. It processes keys digit-by-digit until the array is fully sorted. Address calculation sort uses a hash function to distribute elements into buckets (subfiles) based on the result of the hash function applied to each key. Elements are inserted into the buckets and sorted within using another sorting algorithm like insertion sort before concatenating the buckets to get the final sorted list
Counting sort
Counting sort is an algorithm that sorts a collection of objects by their integer keys in linear time. It works by counting the number of objects with each key value, calculating the positions of each key based on the counts, and copying the objects to the output array in sorted order based on these positions. Counting sort is only suitable when the key values are close to the number of items being sorted.
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Basic of array and data structure, data structure basics, array, address calc...
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Compute skillspowerpoint lect2
This document discusses various animation and transition features in Microsoft PowerPoint. It explains how to add transitions between slides, including adding sound and duration. It also covers removing mouse actions, adding time after transitions, and animating objects on slides. Customized animations can be created to specify effects, start time, direction, and speed. The overall document provides instructions for applying various transitions and animations in PowerPoint presentations.
Computer skills powerpoint intro
This document provides an overview of Microsoft PowerPoint, including how to open PowerPoint, create a new presentation, work with themes and slides, add drawings, and save a presentation. PowerPoint is a presentation program that allows users to convey information to an audience. It has tools for creating slides, applying themes, drawing objects, and saving presentations in different file formats. The document outlines the basic functions and features of PowerPoint.
Filter
This document discusses how to limit the data shown on a Microsoft Excel worksheet using filters and advanced filters. It explains that filters allow you to select rows to display based on rules, and that advanced filters allow finding unique values within a data set. Key steps include clicking the filter arrow in the column header, which displays filtering options and unique values. Options include sorting, clearing filters, and filtering by color or date. Advanced filters copy filtered data to a new location based on criteria in a separate range table. The overall goal is to summarize and analyze data by only viewing relevant rows.
Table
This document provides an overview of using tables in Microsoft Excel. It defines what a table is as an organized collection of rows and columns of data with records as rows and fields as columns. It describes how to create a table by selecting data and clicking "Insert->Table", and how to add and modify table data by adding new rows and columns. The document also summarizes how to sort and filter table data, as well as use formulas within a table.
List
This document discusses how to define valid sets of values for ranges of cells in Microsoft Excel using a list. It introduces data validation in Excel, which allows you to set up validation rules to ensure data entered into a worksheet is accurate. The document explains that to create a validation rule, you select the cells you want to validate, open the Data Validation dialog box from the Data tab, and use the controls there to define what type of data is allowed in the selected cells.
Computer skills excel2010 5
Microsoft Excel allows users to create charts to visualize data. Charts make it easier to see trends, comparisons, and outliers in data. A chart contains a title, axes, data series, and legend. To create a chart, select the data range and insert a chart type. Chart tools allow modification of the type, layout, style, and location of the chart. Charts are a useful tool for communicating insights from data in Excel workbooks.
Computer skills excel2010 data
This document discusses key concepts related to data and Microsoft Excel. It defines data as existing information that is coded for processing and analysis. Quantitative data can be expressed as numbers while qualitative data uses descriptions. Primary data is collected directly by researchers while secondary data was previously collected. Common primary data collection methods include observation, interviews, questionnaires, tests, and surveys. The document also covers sorting data in Excel, functions like COUNT and SQRT, and copying or moving formulas with relative and absolute cell references.
Computer skills excel2010
This document provides an overview of Microsoft Excel and its basic functions. It discusses how to tour the Excel window, edit cell entries, format values, change fonts and alignment, insert and delete rows and columns, and apply colors and borders. The objectives are to understand spreadsheet software like Excel, enter and edit data, perform calculations with formulas, and change the appearance and layout of worksheets.
Computer skills excel2010 3
This document provides an overview of basic mathematical functions in Microsoft Excel including SUM, MAX, MIN, and AVERAGE. It explains that Excel uses formulas beginning with "=" to perform calculations and functions. The SUM function adds the values in a selected range, while the MAX and MIN functions find the largest and smallest numbers respectively. The AVERAGE function calculates the mean of a range by summing the values and dividing by the count.
Computer skills excel2010-4
This document discusses basic mathematical functions in Microsoft Excel, including sum, max, min, and average functions. It explains that Excel reads expressions starting with an equal sign as calculations or formulas. Functions like SUM, MAX, MIN, and AVERAGE can be used to calculate values across a range of cells, for example to find the total, highest, lowest, or average of numbers. The document provides examples of using the SUM, MAX, MIN, and AVERAGE functions in Excel.
Computer skills excel2010
This document provides an overview of Microsoft Excel and its basic functions. It discusses how to tour the Excel window, edit cell entries, format values, change fonts and alignment, insert and delete rows and columns, and apply colors and borders. The objectives are to understand spreadsheet software like Excel, enter and edit data, perform calculations with formulas, and change the appearance and layout of worksheets.
Genetic algorithms
This document discusses genetic algorithms and provides an example of using them to solve a knapsack problem. It describes 4 combinations of items (C1-C4) along with their values and weights and whether they were accepted into the knapsack. A function is also defined to calculate the value of each combination as a percentage of the total possible value. Links to YouTube videos about genetic algorithms are included at the end.
Internet search techniques
This document discusses techniques for conducting effective internet searches, including the use of truncation and wildcard symbols to broaden searches and find variants of words. It also covers the use of Boolean search operators like AND, OR and NOT to combine or exclude terms. Phrase searching and proximity searching are described as ways to make searches more specific by finding terms that appear near each other or in a specified order.
Nearest neighbor search
The document discusses nearest neighbor search (NNS), which is an optimization problem to find the closest point in a given set to a query point. Closeness is typically expressed in terms of a dissimilarity function like distance. The document outlines different approaches to solving NNS like linear search, which directly compares all points and has complexity of O(dN), and space partitioning methods like k-d trees and R-trees, which partition the space and have faster query times of O(log N) on average.
Search methods
Search algorithms can be used to retrieve information from data structures or search problem domains. They are classified based on their search mechanism, such as linear searches that check every record sequentially or binary searches that repeatedly target the center of the search space and divide it in half. Binary search algorithms have a maximum complexity of O(log n), meaning the number of operations needed to find the target is a logarithmic function of the search space size. Search algorithms are also used to find solutions to constraint satisfaction problems by assigning values to variables to satisfy equations or optimize functions. Local search methods view the search space as a graph and move between items along heuristic edges.
Hash function
A hash function maps data of arbitrary size to data of fixed size by generating hash values or codes that can be used to detect duplicated records. Specifically, hash functions are used to map a search key to an index in a hash table, which then indicates where the corresponding record should be stored to allow for quickly locating data records in the hash table dictionary.
Pigeonhole sort
The document describes how to sort numbers using a pigeonhole sorting algorithm. It involves finding the range of numbers to determine the number of "pigeonholes", subtracting the minimum number from each value to assign it to a pigeonhole position, then copying the values from the pigeonholes into a sorted list. The algorithm is demonstrated by sorting the list (12,10,8,3,7,5) into ascending order using 10 pigeonholes.
Gnome sort
The gnome sort algorithm sorts a list by finding the first pair of adjacent elements in the wrong order and swapping them, moving forward until no swaps are needed. It compares each element to the one before it, swapping and moving backward if out of order, or moving forward if in order. This continues until the list is fully sorted with no out of order pairs remaining. The algorithm runs through an example list step-by-step to demonstrate how it works.
Puzzle (1000 coins and 10 bags)
The dealer had 1000 coins that needed to be divided among 10 bags so that any number of coins could be obtained by taking a specific number of bags. The optimal solution was to place 500 coins in the first bag, 250 in the second, 125 in the third, 62 in the fourth, 31 in the fifth, 16 in the sixth, 8 in the seventh, 4 in the eighth, 3 in the ninth bag, and 1 coin in the tenth bag, allowing the dealer to represent any coin amount from 1 to 1000 by selecting the appropriate bags.
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办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
原版一模一样【微信：741003700 】【(uts毕业证书)悉尼科技大学毕业证学历证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Population Growth in Bataan: The effects of population growth around rural pl...
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ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
毕业原版【微信:176555708】【(UCSB毕业证书)圣芭芭拉分校毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
毕业原版【微信:176555708】【(UMN毕业证书)明尼苏达大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Learn SQL from basic queries to Advance queries
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
毕业原版【微信:41543339】【(爱大毕业证书)爱丁堡大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness in Kansas City, MO
To: Tom Tresser
From: Roger Warren
Analysis insight about a Flyball dog competition team's performance
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
The Building Blocks of QuestDB, a Time Series Database
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
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06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
by
Timothy Spann
Principal Developer Advocate
https://budapestdata.hu/2024/en/
https://budapestml.hu/2024/en/
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://www.youtube.com/@flank-stack
milvus
vector database
gen ai
generative ai
deep learning
machine learning
apache nifi
apache pulsar
apache kafka
apache flink
Intelligence supported media monitoring in veterinary medicine
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Global Situational Awareness of A.I. and where its headed
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
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Radix sort
- 2. Radix Sort • radix sort is a non-comparative integer sorting algorithm that sorts data with integer keys by grouping keys by the individual digits which share the same significant position and value. A positional notation is required
- 3. • Most digital computers internally represent all of their data as electronic representations of binary numbers, so processing the digits of integer representations by groups of binary digit representations is most convenient. Two classifications of radix sorts are least significant digit (LSD) radix sorts and most significant digit (MSD) radix sorts. LSD radix sorts process the integer representations starting from the least digit and move towards the most significant digit. MSD radix sorts work the other way around. Radix Sort
- 4. • def radix_sort(array, base=10): • def list_to_buckets(array, base, iteration): • buckets = [[] for _ in range(base)] • for number in array: • # Isolate the base-digit from the number • digit = (number // (base ** iteration)) % base • # Drop the number into the correct bucket buckets[digit].append(number) • return buckets • def buckets_to_list(buckets): • numbers = [] • for bucket in buckets: • # append the numbers in a bucket • # sequentially to the returned array • for number in bucket: • numbers.append(number) • return numbers • maxval = max(array) • it = 0 • # Iterate, sorting the array by each base-digit • while base ** it <= maxval: • array = buckets_to_list(list_to_buckets(array, base, it)) • it += 1 • return array
- 6. sorting least significant digit (1's place)
- 7. sorting least significant digit (1's place)
- 8. Sorting by next digit (10's place)
- 9. Sorting by next digit (10's place)
- 10. Sorting by next digit (10's place)
- 11. Sorting by next digit (10's place)
- 12. Sorting by next digit (10's place)
- 13. Sorting by next digit (10's place)
- 14. Sorting by most significant digit (100's place)
- 15. Sorting by most significant digit (100's place)
- 16. Sorting by most significant digit (100's place)
- 17. Radix Sort