innovations

The main objectives behind the "Veeresh's PAIR Sort" technique is to sort the list of unordered data elements efficiently and to allow efficient and simple arrangement of data elements within the data structure with optimization of comparisons and iterations in the sorting method.

In this sorting technique it effectively terminates the iterations when there is no need of comparison if the elements are all sorted in between the iterations. Unlike Quick sort, Merge sorting technique, this new sorting technique is based on the iterative method of sorting elements within the data structure. So it will be advantageous for optimization of iterations when there is no need for sorting elements.

Finally, the "Veeresh's PAIR Sort" technique is more efficient and simple method of arranging elements within a data structure and it is easy to implement when comparing to the other sorting technique. By the introduction of optimization of comparison and iterations, it will never allow the arranging task on the ordered elements.

Scope and Life

There are plenty of applications and uses of the sorting technique are exist in the field of computer science and engineering technology. Some of the important applications of the sorting technique are as mentioned below:

For Sorting data elements or names of entities

1. In Binary Searching Technique
2. For tuple or records ordering in the tables of DBMS.
3. In the field of operating systems, for ordering the files and directory structure
4. In the field of Graph Theory
5. In the field of communication network, as a Frame sorting method at the receiver side usually.

The main objectives behind the "Veeresh's String Search" technique is to search the key string from the list of given strings efficiently and to reduce the cost of comparisons. For this technique a new kind of linked list will be used as a data structure, which is called ‘Self Linked List'. Here the self-liked list is purely based on ‘Direct Indexing' method of handling nodes of the list.

This data structure is motivated by practical applications in search engines, compilers (symbol tables), neural networks, disk file systems and data base management system. A technique for compact representation of strings is presented. The technique can be seen as an application and extension of existing linked lists by means of finite-state automata.

It is more efficient than Hashing string searching technique, by without computing the location or indexes for the strings every time when it needs to deposit strings in data structure or to search string in that data structure.

Scopes and Life

In recent years, the rapid proliferation of applications dealing with non-numerical data has intensified interest of researchers and computing practitioners in string handling algorithms. However string-processing algorithms have been very important for computer science for a long time in conjunction with computer languages and compiling issues. String searching algorithms are an important class of string algorithms that try to find a place where one or several strings (also called patterns) are found within a larger collection of string or text. The Veeresh's string searching algorithm can be widely used in the following fields:

1. Search Engines - for searching a desired topic or data from large collection of data.
2. Compilers - for storing and locating symbols in the Symbol Tables.
3. Dictionaries - for implementing the large dictionaries on the disks.
4. Data base management system - for tuple dictionaries.
5. Pattern Recognition - for string matching and processing.
6. Disk File System (FAT32, NTFS, etc) - for files and directory tree representations.
7. Lexical Analysis – for analyzing the syntactical and lexical elements of a language.

This is to introduce a new method for drawing a line of a given set of co-ordinates in an area. It is based on the method of generating multiple points or pixels to form a line of two co-ordinates in a space. It is done using the recursive method of generating set of points between co-ordinates to form that line. It has the wide scope in the domain of computer graphics, because most of the objects to be drawn may start by drawing a line.

Advantages

1. Recursive method
2. Less cost of computations
3. It is a new and faster method of drawing a line

For all these applications, this new method of finding the power of a matrix can be used to obtain an alternative way of finding the matrix multiplications by eliminating the row and column grids of the matrix.

The main objectives behind this new technique are to find the power of a matrix with the intention of reducing the number of multiplications and to eliminate the addition operations completely if the elements are all equal. It is also introduced to give the new way of performing matrix operations irrespective of their row and column grids i.e., elimination of row and column grids of the matrix.

Applications

Since the matrix multiplication is analogous to matrix addition, here the way of multiplications can be done easily by the new method of finding the power of a matrix. The four by four matrices are commonly used to transform geometry for 3D rendering. These matrices may also be used to transform RGB colors, to scale RGB colors, and to control hue, saturation and contrast. The most important advantage of using matrices is that any number of color transformations can be composed using standard matrix multiplication.

1. Color Transformation
2. Changing Brightness
3. Modifying Saturation
4. Converting to Luminance
5. Modifying Saturation
6. Applying Offsets to Color Components
7. Simple Hue Rotation
8. Hue Rotation While Preserving Luminance
9. 3D Object Transformation
10. Scaling of a Object
11. Rotation of a Object

The goal here is to introduce a new alterntive method of generating permutational group of elements. This is done based on the concept of Binary Subset Construction. It is quite complex recursive algorithm and as its nature it is easier method to understand the new procedure to do the ReIndexing of a set.

Features

1. Is a Recursive algorithm
2. Binay Subset Construction based Reindexing a set of elements
3. Easier method to achive n!=n/(n-1)!, n>0

This is to define a new approach to improve the performance of a microprocessor, irrespective of the usual dependecy on its physical memory space and procssor execution frequency speed. It is a reserach at the core level of Microprocessor. Here the goal is to introduce a some technique and theorm to Optimize some important basic binary operations. It also defines some principle, based on those, new Digital Functinal Units will be introduced. Here, most of the binary operations to be optimized and it will be done in the Arithmetic & Logic Unit (ALU) of the Microprocessor.

Features

1. To introduce some new methodologies and reduce some time in doing basic binary operations.
2. It may take a wide influence over digital units performing binary opertions
3. Its scope would be great in the next generation of ALU units
4. It proves that, the execution performance will also depends on the method of doing binary operations.
5. Here the focus is on some basic binary operations like additions, substraction, multiplications.

This is again a new sorting technique from me. The circular sorting technique is based on the concept of circular linked list. Unlike some exisitng sorting technique having some fixed number of iterations in it, this algorithm works by taking finite number iterations (comparision cycles) for sorting data elements. It gives a average good best case effeciency. It is also a In place algorithm

Features

1. A new sorting technique from me.
2. It is a relative cyclic iterative sorting technique
3. It gives a average bestcase effeciency.

The Random Data Structure is a new concept, that defines a another approach for accessing data elements randomly and effeciently from the data structure. It is a under reserach concept. It has a goal to achive a new data structure model that is relative to the Stack and Queue data structures.

Features

1. A new data structure model.
2. It is a relative to the Stack and Queue data structure.