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Special Issue 1

Special Issue  1  Recent Trends in Analysis of Algorithms and Complexity Theory

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 Mishra Sambit Kumar ,  Patnaik Dulu(Dr.)  ,  Mishra Bibhuti Bhusan(Dr.) 

Performance Analysis of Bubble Sort and Insertion Sort With Computational Complexity

[Abstract] [Full-Text PDF]

Abstract: The complexity of a problem, algorithm or structure, and to obtain bounds for complexity arises in computer science. The traditional branches of mathematics, statistical physics, biology, medicine, social sciences and engineering are also confronted more and more frequently with this problem. In the approach taken by computer science, complexity is measured by the quantity of computational resources, e.g. time, storage, program, communication used up by a particular task. Many results on the computational complexity of sorting algorithms are usually obtained using incompressibility method. Usually hard average-case analysis is applicable to this method. The results about bubble sort, insertion sort in sequential or parallel mode are being already surveyed. Especially in the case of bubble sort the uses of incompressibility easily resolved problems that had stayed open for a long time. Also in the case of insertion sort it is also possible to resolve problems by applying incompressibility method.

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Rout, Sushri Samita ,Misra, Bijan Bihari, Samanta, Sasmita

Hybrid Research: A methodological paradigm for interdisciplinary research

[Abstract] [Full-Text PDF] 

Abstract: There have been several classifications about the type of research. But considering the fact that most of the research carried out nowadays, is inter-disciplinary in nature, they cannot be classified under any crisp classification. So this necessitates for clear understanding of the methodology to carry out such a research so that there would be proper monitoring and control over the, otherwise meandering course of research. This study is an attempt to give shape to a class of research where the domain of application is management (Academic) and nature of solution is technical. The work highlights the methodology that can be adopted under such circumstance, including the existing paradigms, the available methodological choices and the rationale behind the current methodology.

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Satapathy, Lokanath, Misra, Bijan B., Biswal, Bhabendra N.

SFLANN for Classification of Life Science Databases

[Abstract] [Full-Text PDF]

Abstract: This paper presents SFLANN, a hybrid model of Particle Swarm Optimization (PSO) and Functional Link Artificial Neural Network (FLANN) for classification of life science databases. Backpropagation neural networks (BPN) are most commonly used technique for data classification. BPN usually suffers from many drawbacks, such as how many layers to be taken, how many neurons in each hidden layer, what activation function to be used, how to overcome local traps etc. FLANN is a single layer network and to avoid the drawbacks of single layer network, the input values are functionally expanded to map complex non-linear problems. Further to get rid of the local traps in backpropagation, here PSO technique is used to optimize the weights. Four different standard classifiers BPN, naïve Bayes classifier, k-nearest neighbor, multiple linear regression (MLR) classifiers are compared to evaluate the performance of SFLANN. 6 bench marked life science databases are considered to evaluate the performance of these models. Simulation results show that the classification accuracy obtained by SFLANN is better in comparison to other classifier models at most of the instances.

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Dash, Rasmita, Misra, Bijan Bihhari.

Analysis Two Stage Feature Selection for Classification of Microarray Databases

[Abstract] [Full-Text PDF]

Abstract: Classification of microarray data with high dimension and small sample size is a complex task. This work explores the optimal search space appropriate for classification. Here the crush of dimensionality is handled with a two stages feature selection technique. At the first stage, statistical measures are used to remove genes that do not contribute for classification. In the second stage, attributes are arranged in a non-increasing order of signal to noise ratio (SNR). The number of attributes to be considered from this stage is a challenging task. Selection of very few numbers of genes may not help representing the properties of each class properly, while selection of a large numbers of genes also leads to diminishing classifier performance. A set of four classifiers such as artificial neural network, naïve Bayes, k-nearest neighbor, multiple linear regression classifier and ten microarray databases are considered for this experimentation. For each microarray data and for each classifier, selection for different set of genes improves the performance. However, the analysis shows that a favorable set of genes can be suggested to improve performance and another set of genes can be suggested to avoid which degrades the performance.

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Mishra Sambit Kumar, Champati Pratap Kumar, Sahoo Rajesh Kumar

Analysis of time complexity of algorithm (dependent and independent loops)

[Abstract] [Full-Text PDF]

Abstract: The pragmatic aspects of computing require one to be cognizant of the resource usage aspects of a program. While such concerns should be secondary to those of the correctness of the program, correctness can make the difference between success and failure in computer problem solving. The general term used to resource usage is complexity. The amount of time required to execute an algorithm is known as time complexity. Similarly, the amount of memory required to execute an algorithm is known as space complexity. There are several ways to measure time complexity, (a) the average case, which is more to compute because it requires some knowledge that is expected on average and (b) the best case, not exactly the best measure of an algorithm’s performance because unless it is likely to continually be the best case comparisons between algorithms.

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Sethi, Purna Chandra, Behera, Prafulla Kumar

An Efficient Dynamic Bandwidth Allocation Algorithm for improving the Quality of Service of Networks

[Abstract] [Full-Text PDF]

Abstract: During networking, the bandwidth is equally assigned to individual nodes. But each node can’t utilize the same amount of bandwidth. The requirement of bandwidth also differs from time to time. For proper utilization of bandwidth, the dynamic bandwidth allocation algorithm can be implemented. Efficient dynamic resource provisioning algorithms are necessary to the development and automation of Quality of Service (QoS) networks. The main goal of these algorithms is to offer services that satisfy the QoS requirements of individual users while guaranteeing at the same time an efficient utilization of network resources. In this paper, we introduce a new service model that provides quantitative assignment of bandwidth guaranteeing the improvement in QoS in terms of network services. We propose an efficient bandwidth allocation algorithm that takes traffic statistics for dynamic bandwidth allocation. We demonstrate through simulation in realistic network scenarios that the proposed dynamic provisioning model is superior to static provisioning in providing resource allocation both in terms of total accepted load and network revenue.

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Dixit P. K., Sahoo Archana , Sahoo Bikash Kumar

Performance Analysis Of Sorting Algorithm

[Abstract] [Full-Text PDF]

Abstract: Sorting is a classic subject in computer science. There are mainly 3 reasons for studying sorting. First sorting algorithm gives a creative way for problem solving. Second sorting algorithm goods to practicing programming technique by using method, loop, array, statement. Third It is best to demonstrate the algorithm performance. This paper introduce bubble sort, merge sort, quick sort, bucket sort, radix sort, external sort.

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Jena Manoj Kumar , Balabantaray Rakesh Ch.

Opinion Mining for online Oriya Text

[Abstract] [Full-Text PDF]

Abstract: The paper aims at discussing the opinion mining technique can be applicable for analyzing online oriya text. The Oriya language is a classical language belongs to Indo Aryan family. The opinions in oriya are subjective information which represents user’s sentiments, feelings or appraisal related to the same. The concept of opinion is very broad. It can be positive, negative and neutral. In this paper we focus on the various opinion mining techniques that can facilitate the task of opinion mining. The precise method for predicting opinions enable us, to extract sentiments from the web and foretell the feeling of the person, which could prove valuable for research at various level. Much of the research work had been done on the processing of opinions or sentiments recently because opinions are so important that whenever we need to make a decision we want to know others’ opinions. This opinion is not only important for a user but is also useful for an organization.

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Dixit P. K. , Sahoo Archana , Sahoo Bikash Kumar.

Performance Analysis Of Sorting Algorithm

[Abstract] [Full-Text PDF]

Abstract: Sorting is a classic subject in computer science. There are mainly 3 reasons for studying sorting. First sorting algorithm gives a creative way for problem solving. Second sorting algorithm goods to practicing programming technique by using method, loop, array, statement. Third It is best to demonstrate the algorithm performance. This paper introduce bubble sort, merge sort, quick sort, bucket sort, radix sort, external sort.

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