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This paper describes a sorting algorithm for Bengali texts which is one of the most vital tasks for Bengali Natural Language Processing. As Unicode is much more preferable than ASCII encoding, we need to use this representation for Bengali Language. But due to some distinct properties of Bengali Language, they cannot be sorted directly using the order in Unicode character scheme. A few works have been done on this topics – some of them are for ASCII encoding whether some are for Unicode. But still they have some drawbacks and still there is no standard to sort Bengali texts. In this paper, we have discussed about the previous approaches and proposing a revised and easier procedure to sort Unicode Bengali texts. We used a mapping to simplify the sorting process. The efficiency depends on the efficiency of the sorting algorithm. This method is able to sort any Unicode Bengali texts. It will also work for Unicode text of any language if we just change the mapping part. So the process is both keyboard and language independent. General Terms Theoretical Informatics

Sorting algorithms and their implementations in modern computing requires improvements in sorting large data sets effectively, both with respect to time and memory consumed. This paper is aimed at reviewing multiple adaptive sorting algorithms, on the basis of selection of an algorithm based on the characteristics of the data set. Machine Learning allows us to construct an adaptive algorithm based on the analysis of the experimental data. A review of algorithms designed using Systems of Algorithmic Algebra and Genetic Algorithms was performed. Both methods are designed to target different use cases. Systems of Algorithmic Algebra is a representation of pseudo code that can be converted to high level code using Integrated toolkit for Design and Synthesis of programs, while the Genetic Algorithm attempts to optimize its fitness function and generate the most successful algorithm.

Sorting algorithms are the class of algorithms that result in the ordered arrangement of a list of given elements. The arrangement can be in ascending or descending order based on the requirement given. Time complexity, space complexity and optimality are used to assess the algorithms. In this paper, a new sorting algorithm called Matrix sort is introduced. This algorithm aims to sort the elements of a matrix without disturbing the matrix structure. It has a time complexity of O(n p nlog p n) and hence takes lesser time than existing O(n 2 ) algorithms. A pseudocode for the algorithm is provided and the best, average and worst case time complexities are derived.

Sorting algorithms, their implementations and their applications in modern computing necessitates improvements for sorting large data sets quickly and efficiently. This paper will analyze the performance of a multi-threaded quick sort implemented using the thread pool pattern. The analysis will be done by comparing the time required to sort various data sets and their memory constraints, against the native sorting implementations of the Dual Pivot Quicksort and Merge Sort using the Fork-Join framework in the Oracle Java 8 programming language. Analysis is done of the effect of different number of processor (cores) of the test machine, as well as the performance barrier due to the initial time taken to create “p” threads, p being the number of processors. This paper also analyzes the limitations of the inbuilt Java method Arrays.parallelSort() and how the proposed system overcomes this problem. Finally, it also discuss possible improvements to the proposed system to further improve its performance.

In this study, we propose an optical character recognition technique using Intro Sort. Main feature of this proposed technique is that we segment images using intro sort. It reduces the comparison time for matching the pixels of an image. It reflects reduction in OCR time. Intro sort algorithm begins with quick sort and when recursion depth exceeds a level it switches to heap sort, based on the number of pixels being sorted. This approach also has advantage of recognizing number plates and text documents in very nominal time. Our approach is able to extract characters of different font sizes. Our technique is performed well in noisy images too. General Terms Optical character recognition

Sorting a list of items is one basic task in many applications used on the computer. The term describes the arrangement of a set of items in a certain order to make analysis and processing very easy. Numerous sorting algorithms exist however its efficiency and memory space consumption become a major issue when it has to be implemented.Essentially, programmers select sort algorithms that perform well even as the size of the input data increases. In this study, a new algorithm, Magnetic Bubble Sort Algorithm (MBS) is proposed. The MBS is an enhancement of the bubble sort algorithm which offers a far better performance in the case where redundancies occur in the list. The run time of the MBS depends on the number of distinct values that are found in the list to be sorted.The improved bubble sort algorithm is very simple to analyse, considering the fact that the time complexity of the algorithm depends on two main factors that is the size of list (n) and number of distinct values in the list.

Data Structure is one of the fundamental areas of the computer science. Sorting is crucial in data structure, which creates the list of sequence items. In this paper, we present two techniques of sorting algorithm for natural numbers, which uses the array indexing methodology and insert that number into the proper index of the array without performing any element comparisons and swapping. The first algorithm improves ArrayIndexed Sorting Algorithm for natural numbers [1] by adding negative numbers. The second algorithm is a new sorting algorithm that refers to Two Arrays-Indexed Sorting Algorithm for Natural Numbers (TAISN). The two techniques of sorting algorithm for natural numbers are efficient to give a much better performance than the existing sorting algorithms of the O(n) class, for large array size with same length of digits of input data.

Batchers bitonic sorting algorithm is a parallel sorting algorithm, which is used for sorting the numbers in modern parallel machines. There are various parallel sorting algorithms such as radix sort, bitonic sort, etc. It is one of the efficient parallel sorting algorithm because of load balancing property. It is widely used in various scientific and engineering applications. However, Various researches have worked on a bitonic sorting algorithm in order to improve up the performance of original batchers bitonic sorting algorithm. In this paper, tried to review the contribution made by these researchers.

One of the basic problems of Computer Science is sorting a list of items. It refers to the arrangement of numerical or alphabetical or character data in statistical order. Bubble, Insertion, Selection, Merge, and Quick sort are most common ones and they all have different performances based on the size of the list to be sorted. As the size of a list increases, some of the sorting algorithm turns to perform better than others and most cases programmers select algorithms that perform well even as the size of the input data increases. As the size of dataset increases, there is always the chance of duplication or some form of redundancies occurring in the list. For example, list of ages of students on a university campus is likely to have majority of them repeating. A new algorithm is proposed which can perform sorting faster than most sorting algorithms in such cases. The improved selection sort algorithm is a modification of the existing selection sort, but here the number of passes needed to sort the list is not solely based on the size of the list, but the number of distinct values in the dataset. This offers a far better performance as compared with the old selection sort in the case where there are redundancies in the list. General Terms Algorithms, Sorting Algorithms

aim of this paper if to show that the great part of the execution time is consumed in computations. So as the number of processors increase, the amount of work done by each processor will be decrease regardless the effect of the number of physical cores used. Still the time taken to solve the computations dominates over the communication time as by increasing number of processors; tasks are more divided so overall time decreases. The total overhead generated from process initializations and inter-process communication negatively affects the execution time. Using MPI, parallelization on five sorting techniques which are selection sort, bubble sort, quick sort, insertion sort and shell sort have been implemented. KeywordsParallel Programming, Selection sort, Bubble sort, Quick sort, Insertion Sort, Shell Sort, Bucket sort, Sequential Programming.

is a concept in MapReduce Analytics based on the following two conditions: (a) a mapper should be cautious, that is, should not exclude any reducer's shuffle and sort strategy from consideration; and (b) a mapper should respect the reducers' shuffle and sort preferences, that is, should deem a reducer's shuffle and sort strategy ki infinitely more likely than k'i if it premises the reducer to prefer ki to k'i. A shuffle and sort strategy is quantifiable if it can optimally be chosen under common shuffle and sort conjecture in the events (a) and (b). In this paper we present an algorithm that for every finite MapReduce operation computes the set of all quantifiable shuffle and sort strategies. The algorithm is based on the new idea of a key-value preference limitation, which is a pair (ki, Vi) consisting of a shuffle and sort strategy ki, and a subset of shuffle and sort strategies Vi, for mapper i. The interpretation is that mapper i prefers some shuffle and sort strategy in Vi to ki. The algorithm proceeds by successively adding key-value preference limitations to the MapReduce. Keywordsanalytics, quantifiability, key-value, preference limitation, shuffle and sort, Totally Ordered Data-Intensive Systems.

paper is based on an easily comprehendible algorithm to sort Bangla words in the linguistic order. Though a few works has been done on this project, only a few served the purpose. Since Unicode serves as a standard and a fixed representation for all characters of most of the language, Unicode representation of Bangla characters has been used to sort thousands of words in a linguistic order in this method. This method which requires a mapping can sort any Bangla word without keyboard dependency. This method is open for future modification so that changing the sorting algorithm to be used does not affect the whole algorithm.

Ordering is a very important for mankind .If anything is in unordered then it will not easily understand by anyone but if it is in order then it will easily understand and used by anyone. So ordering is a very important issue in computer science also. In computer science many programming applications use ordering to solving a problem either it is in ascending or descending order. In this paper we discuss four sorting algorithms which are already existed named as Insertion Sort, Bubble Sort, Selection Sort, Merge Sort and we design a new sorting algorithm named as index sort also. In this paper we check the performance and comparison of all five sorting algorithm on the basis of increasing the no of elements in bulk. We check how much processing time is taken by all four sorting algorithms with Index Sort and compared them and finding which sorting algorithm takes less time to sort the elements like 10, 100, 1000, 10000 . If any algorithm takes less processing time it means that it sorts the element faster than others. The processing time of a sorting algorithm is based on the processing speed of a Processor as well as internal memory (RAM) used by the system.

Sorting is integral part of many computer based systems and applications, as it involves rearranging information into either ascending or descending order. There are many sorting algorithms like Quick sort, Heap sort, Merge sort, Insertion sort, Selection sort, Bubble sort and Freezing sort. However, efforts have been made to improve the performance of the algorithm in terms of efficiency, indeed a big issue to be considered. Major Emphasis has been placed on complexity by reducing the Number of comparisons, hence reducing complexity. This paper presents new sorting algorithm EIS, “ENHANCED INSERTION SORT”.It is basically an enhancement toINSERTION SORT (a kind of Hybrid sorting technique) by making it impressively faster algorithm with O(n)complexity as compared to O(n) of insertion sort in worst case and less than O(n) in average case which is much better than insertion sort O(n). It works flawlessly with huge lists of elements. To prove the effectiveness of the algorithm, the new algorithm is analyzed, implemented, tested and results has been carried out and compared with other major sorting algorithms and the results were promising. General Terms Sorting Algorithm, Hybrid technique, EIS-Enhanced Insertion sort, NOCNumber of Comparisons, NOENumber of elements.

Recently the lower bound for integer sorting has considerably improved and achieved with comparison sorting to [1] for a deterministic algorithms or to for a radix sort algorithm in space that depends only on the number of input integers. Andersson et al. [2] presented signature sort in the expected linear time and space which gives very bad performance than randomized quick sort. We earlier presented in [14] that performance of signature sort can be enhanced using hashing and bitwise operators. This paper gives the implementation of that idea and later we have compared the performance of algorithm with existing randomized signature sort and randomized quick Sort. General Terms Algorithms, Complexity.

Sorting is one of the frequent used operations in computer science. Due to highly parallel computing nature of GPU architecture; it can be utilized for sorting purpose. We have considered the input array that is to be sorted in a 2D matrix form and applied a modified version of merge sort on that matrix. This modification leads to a much efficient sorting algorithm with reduced complexity. Therefore a lot of work has already been done to improve the efficiency of sorting algorithms. In this paper We have used the GPU architecture for solving the sorting problem.

To perform searching operation we have different kinds of searching techniques. These all searching algorithms works on data, which are previously sorted. An efficient algorithm is required to make searching fast and efficient. This paper presents a new sorting algorithm named as “Find and Place Sorting Technique for Unique Numbers (FPSTUN)”. This FPSTUN is designed to perform sorting quickly and easily and also efficient as existing algorithms in sorting.

sort is a simple, stable and efficient sorting algorithm with linear running time, which is a fundamental building block for many applications. Counting sort algorithm has been widely used in data processing systems, because of its high efficiency, fast speed and stable nature. Therefore, a thorough study of its time complexity is required. This paper presents a modified version of counting sort E-Counting Sort with some efficiency improvements. An analysis of the E- Counting sort algorithm in comparison with original counting sort algorithm clearly shows that E-Counting sort algorithm having a reduced time complexity approximately to half of the original one. The new version can be applied to many real world applications providing the required result as efficient and as effective as original counting sort without affecting its real nature and improve the efficiency of application program.